diff --git a/data/compare_french_ships_to_marseille_accross_time.csv b/data/compare_french_ships_to_marseille_accross_time.csv
index 100286e..7475fd3 100644
--- a/data/compare_french_ships_to_marseille_accross_time.csv
+++ b/data/compare_french_ships_to_marseille_accross_time.csv
@@ -1,18 +1,4 @@
 year,state,tonnage_french,share_of_french
-1749,Péninsule italienne,18550,0.4166198764738911
-1749,Espagne,14025,0.6936201780415431
-1749,Empire ottoman,21170,0.9657846715328468
-1749,Provinces-Unies,0,0.0
-1749,Grande-Bretagne et colonies (Terre-Neuve),9000,0.16638935108153077
-1749,France,42885,0.930866073366616
-1749,autre,4345,0.26056971514242877
-1769,Péninsule italienne,18504.0,0.49090040855308537
-1769,Espagne,15225.0,0.5542409901710957
-1769,France,70501.0,0.9716100935764391
-1769,autre,7970,0.4540017089148391
-1769,Empire ottoman,29070,0.9603567888999008
-1769,Grande-Bretagne et colonies (Terre-Neuve),8460,0.5980911983032874
-1769,Provinces-Unies,0,0.0
 1787,Péninsule italienne,21554.499999999996,0.3689591276922615
 1787,Empire ottoman,42457.541666666664,0.9161677400444695
 1787,Grande-Bretagne et colonies (Terre-Neuve),8847.0,0.5783108903124592
@@ -20,6 +6,13 @@ year,state,tonnage_french,share_of_french
 1787,France,94552.0,0.9594122899586005
 1787,Espagne,17266.708333333332,0.44376349946939125
 1787,Provinces-Unies,150,0.04285714285714286
+1749,Péninsule italienne,18550,0.4166198764738911
+1749,Espagne,14025,0.6936201780415431
+1749,Empire ottoman,21170,0.9657846715328468
+1749,Provinces-Unies,0,0.0
+1749,Grande-Bretagne et colonies (Terre-Neuve),9000,0.16638935108153077
+1749,France,42885,0.930866073366616
+1749,autre,4345,0.26056971514242877
 1789,Péninsule italienne,28632.416666666668,0.41081030023829196
 1789,France,79964.33333333334,0.9772325465818268
 1789,Espagne,11410.5,0.40188430043145196
@@ -27,3 +20,10 @@ year,state,tonnage_french,share_of_french
 1789,Empire ottoman,41393.25000000001,0.971370407091691
 1789,autre,11065.0,0.4869086908690869
 1789,Grande-Bretagne et colonies (Terre-Neuve),10290.0,0.6500315855969678
+1769,Péninsule italienne,18504.0,0.49090040855308537
+1769,Espagne,15225.0,0.5542409901710957
+1769,France,70501.0,0.9716100935764391
+1769,autre,7970,0.4540017089148391
+1769,Empire ottoman,29070,0.9603567888999008
+1769,Grande-Bretagne et colonies (Terre-Neuve),8460,0.5980911983032874
+1769,Provinces-Unies,0,0.0
diff --git a/data/evolution-exports-levant.csv b/data/evolution-exports-levant.csv
index 4a5db07..94f6a8b 100644
--- a/data/evolution-exports-levant.csv
+++ b/data/evolution-exports-levant.csv
@@ -1,313 +1,313 @@
 year,group,value
 1725,"Nord, Hollande & Flandres",125796
-1725,Italie & Espagne,1924148
 1725,Levant & Barbarie,2896626
+1725,Italie & Espagne,1924148
 1725,total,4946572.30855334
 1726,"Nord, Hollande & Flandres",121992
-1726,Italie & Espagne,2655918
 1726,Levant & Barbarie,2463485
+1726,Italie & Espagne,2655918
 1726,total,5241396.102523374
-1727,Angleterre & Amérique du Nord,6892
 1727,"Nord, Hollande & Flandres",217896
+1727,Levant & Barbarie,3543962
+1727,Angleterre & Amérique du Nord,6892
 1727,Colonies françaises,3172479
 1727,Italie & Espagne,3039549
-1727,Levant & Barbarie,3543962
 1727,total,9980779.917532297
-1728,Angleterre & Amérique du Nord,8324
 1728,"Nord, Hollande & Flandres",221720
+1728,Levant & Barbarie,3474014
+1728,Angleterre & Amérique du Nord,8324
 1728,Colonies françaises,1318732
 1728,Italie & Espagne,3337230
-1728,Levant & Barbarie,3474014
 1728,total,8360022.2490085745
 1729,"Nord, Hollande & Flandres",233464
+1729,Levant & Barbarie,2638840
 1729,Colonies françaises,2318735
 1729,Italie & Espagne,3304026
-1729,Levant & Barbarie,2638840
 1729,total,8495067.3833482
 1730,"Nord, Hollande & Flandres",193550
+1730,Levant & Barbarie,2540378
 1730,Colonies françaises,1691047
 1730,Italie & Espagne,2372282
-1730,Levant & Barbarie,2540378
 1730,total,6797259.133108479
 1731,"Nord, Hollande & Flandres",259992
+1731,Levant & Barbarie,3015091
 1731,Colonies françaises,2298264
 1731,Italie & Espagne,3117086
-1731,Levant & Barbarie,3015091
 1731,total,8690435.210432697
 1732,"Nord, Hollande & Flandres",269472
+1732,Levant & Barbarie,3155912
 1732,Colonies françaises,2382649
 1732,Italie & Espagne,3742373
-1732,Levant & Barbarie,3155912
 1732,total,9550408.90760288
 1733,"Nord, Hollande & Flandres",301946
+1733,Levant & Barbarie,3333111
 1733,Colonies françaises,1530975
 1733,Italie & Espagne,5594543
-1733,Levant & Barbarie,3333111
 1733,total,10760576.18320176
 1735,"Nord, Hollande & Flandres",287963
+1735,Levant & Barbarie,3394796
 1735,Colonies françaises,3827881
 1735,Italie & Espagne,4570927
-1735,Levant & Barbarie,3394796
 1735,total,12081569.7535745
 1736,"Nord, Hollande & Flandres",432201
+1736,Levant & Barbarie,3541775
 1736,Colonies françaises,4372470
 1736,Italie & Espagne,5737106
-1736,Levant & Barbarie,3541775
 1736,total,14083554.565514365
 1737,"Nord, Hollande & Flandres",375051
+1737,Levant & Barbarie,4006428
 1737,Colonies françaises,7895668
 1737,Italie & Espagne,6634446
-1737,Levant & Barbarie,4006428
 1737,total,18911595.556100316
 1738,"Nord, Hollande & Flandres",335288
+1738,Levant & Barbarie,4010867
 1738,Colonies françaises,4089489
 1738,Italie & Espagne,8213492
-1738,Levant & Barbarie,4010867
 1738,total,16649138.651283223
 1739,"Nord, Hollande & Flandres",1779040
+1739,Levant & Barbarie,14365740
 1739,Colonies françaises,6419144
 1739,Italie & Espagne,12111192
-1739,Levant & Barbarie,14365740
 1739,total,34675117.0147956
-1740,Angleterre & Amérique du Nord,250048
 1740,"Nord, Hollande & Flandres",3802383
+1740,Levant & Barbarie,18271510
+1740,Angleterre & Amérique du Nord,250048
 1740,Colonies françaises,6075980
 1740,Italie & Espagne,21085769
-1740,Levant & Barbarie,18271510
 1740,total,49485692.83599193
-1741,Angleterre & Amérique du Nord,229534
 1741,"Nord, Hollande & Flandres",2794348
+1741,Levant & Barbarie,16148356
+1741,Angleterre & Amérique du Nord,229534
 1741,Colonies françaises,9959662
 1741,Italie & Espagne,22849542
-1741,Levant & Barbarie,16148356
 1741,total,51981444.31035002
-1742,Angleterre & Amérique du Nord,734061
 1742,"Nord, Hollande & Flandres",2705192
+1742,Levant & Barbarie,16708807
+1742,Angleterre & Amérique du Nord,734061
 1742,Colonies françaises,9139656
 1742,Italie & Espagne,22888502
-1742,Levant & Barbarie,16708807
 1742,total,52176220.79880458
-1743,Angleterre & Amérique du Nord,544242
 1743,"Nord, Hollande & Flandres",4749436
+1743,Levant & Barbarie,20749423
+1743,Angleterre & Amérique du Nord,544242
 1743,Colonies françaises,10464361
 1743,Italie & Espagne,27731392
-1743,Levant & Barbarie,20749423
 1743,total,64238856.881133206
-1744,Angleterre & Amérique du Nord,240211
 1744,"Nord, Hollande & Flandres",2785809
+1744,Levant & Barbarie,13077707
+1744,Angleterre & Amérique du Nord,240211
 1744,Colonies françaises,3923791
 1744,Italie & Espagne,12171228
-1744,Levant & Barbarie,13077707
 1744,total,32198747.948294297
-1745,Angleterre & Amérique du Nord,94151
 1745,"Nord, Hollande & Flandres",3094146
+1745,Levant & Barbarie,14612617
+1745,Angleterre & Amérique du Nord,94151
 1745,Colonies françaises,2550504
 1745,Italie & Espagne,15283744
-1745,Levant & Barbarie,14612617
 1745,total,35635165.03908121
-1746,Angleterre & Amérique du Nord,99150
 1746,"Nord, Hollande & Flandres",2864526
+1746,Levant & Barbarie,12184386
+1746,Angleterre & Amérique du Nord,99150
 1746,Colonies françaises,2306952
 1746,Italie & Espagne,15425285
-1746,Levant & Barbarie,12184386
 1746,total,32880300.461018704
-1747,Angleterre & Amérique du Nord,177510
 1747,"Nord, Hollande & Flandres",2908742
-1747,Italie & Espagne,18352892
 1747,Levant & Barbarie,14160895
+1747,Angleterre & Amérique du Nord,177510
+1747,Italie & Espagne,18352892
 1747,total,35600040.11585111
-1748,Angleterre & Amérique du Nord,1769513
 1748,"Nord, Hollande & Flandres",2634979
+1748,Levant & Barbarie,12198221
+1748,Angleterre & Amérique du Nord,1769513
 1748,Colonies françaises,1605173
 1748,Italie & Espagne,21914216
-1748,Levant & Barbarie,12198221
 1748,total,40122103.95795721
-1749,Angleterre & Amérique du Nord,9786990
 1749,"Nord, Hollande & Flandres",10568690
+1749,Levant & Barbarie,24155996
+1749,Angleterre & Amérique du Nord,9786990
 1749,Colonies françaises,8789419
 1749,Italie & Espagne,34932356
-1749,Levant & Barbarie,24155996
 1749,total,88233454.24000002
-1751,Angleterre & Amérique du Nord,4074300
 1751,"Nord, Hollande & Flandres",7823028
+1751,Levant & Barbarie,27875163
+1751,Angleterre & Amérique du Nord,4074300
 1751,Colonies françaises,5039098
 1751,Italie & Espagne,22812623
-1751,Levant & Barbarie,27875163
 1751,total,67624214.96659152
-1752,Angleterre & Amérique du Nord,2473009
 1752,"Nord, Hollande & Flandres",8742215
+1752,Levant & Barbarie,25527907
+1752,Angleterre & Amérique du Nord,2473009
 1752,Colonies françaises,8608372
 1752,Italie & Espagne,27185325
-1752,Levant & Barbarie,25527907
 1752,total,72536829.71123928
-1753,Angleterre & Amérique du Nord,1205231
 1753,"Nord, Hollande & Flandres",6637508
+1753,Levant & Barbarie,30340669
+1753,Angleterre & Amérique du Nord,1205231
 1753,Colonies françaises,8477208
 1753,Italie & Espagne,21070695
-1753,Levant & Barbarie,30340669
 1753,total,67731312.8675276
-1754,Angleterre & Amérique du Nord,1169744
 1754,"Nord, Hollande & Flandres",7928888
+1754,Levant & Barbarie,27282001
+1754,Angleterre & Amérique du Nord,1169744
 1754,Colonies françaises,12803822
 1754,Italie & Espagne,25028305
-1754,Levant & Barbarie,27282001
 1754,total,74212763.01663025
-1755,Angleterre & Amérique du Nord,1033654
 1755,"Nord, Hollande & Flandres",6055680
+1755,Levant & Barbarie,31934232
+1755,Angleterre & Amérique du Nord,1033654
 1755,Colonies françaises,12388405
 1755,Italie & Espagne,28008476
-1755,Levant & Barbarie,31934232
 1755,total,79420447.92118071
-1756,Angleterre & Amérique du Nord,130505
 1756,"Nord, Hollande & Flandres",4175714
+1756,Levant & Barbarie,20853924
+1756,Angleterre & Amérique du Nord,130505
 1756,Colonies françaises,2234501
 1756,Italie & Espagne,23422989
-1756,Levant & Barbarie,20853924
 1756,total,50817634.884949565
-1757,Angleterre & Amérique du Nord,459068
 1757,"Nord, Hollande & Flandres",5433575
+1757,Levant & Barbarie,21684462
+1757,Angleterre & Amérique du Nord,459068
 1757,Colonies françaises,146688
 1757,Italie & Espagne,25634708
-1757,Levant & Barbarie,21684462
 1757,total,53358505.38187696
-1758,Angleterre & Amérique du Nord,205665
 1758,"Nord, Hollande & Flandres",3219678
+1758,Levant & Barbarie,11199276
+1758,Angleterre & Amérique du Nord,205665
 1758,Colonies françaises,18950
 1758,Italie & Espagne,22193706
-1758,Levant & Barbarie,11199276
 1758,total,36837276.13591482
 1759,"Nord, Hollande & Flandres",4861973
+1759,Levant & Barbarie,8711328
 1759,Colonies françaises,263367
 1759,Italie & Espagne,24404740
-1759,Levant & Barbarie,8711328
 1759,total,38241410.691821605
 1760,total,0
-1761,Angleterre & Amérique du Nord,121369
 1761,"Nord, Hollande & Flandres",6781378
-1761,Italie & Espagne,30500493
 1761,Levant & Barbarie,10576596
+1761,Angleterre & Amérique du Nord,121369
+1761,Italie & Espagne,30500493
 1761,total,47979838.72922086
-1762,Angleterre & Amérique du Nord,303926
 1762,"Nord, Hollande & Flandres",4850808
+1762,Levant & Barbarie,25847254
+1762,Angleterre & Amérique du Nord,303926
 1762,Colonies françaises,1536270
 1762,Italie & Espagne,25818088
-1762,Levant & Barbarie,25847254
 1762,total,58356347.295732476
-1763,Angleterre & Amérique du Nord,927393
 1763,"Nord, Hollande & Flandres",6888374
+1763,Levant & Barbarie,28660119
+1763,Angleterre & Amérique du Nord,927393
 1763,Colonies françaises,21107810
 1763,Italie & Espagne,32183428
-1763,Levant & Barbarie,28660119
 1763,total,89767126.8384973
-1764,Angleterre & Amérique du Nord,1121381
 1764,"Nord, Hollande & Flandres",5683173
+1764,Levant & Barbarie,33671074
+1764,Angleterre & Amérique du Nord,1121381
 1764,Colonies françaises,16032339
 1764,Italie & Espagne,28590139
-1764,Levant & Barbarie,33671074
 1764,total,85098107.90470757
-1765,Angleterre & Amérique du Nord,833800
 1765,"Nord, Hollande & Flandres",4878080
+1765,Levant & Barbarie,26961958
+1765,Angleterre & Amérique du Nord,833800
 1765,Colonies françaises,16772142
 1765,Italie & Espagne,30482798
-1765,Levant & Barbarie,26961958
 1765,total,79928781.17570402
-1766,Angleterre & Amérique du Nord,996199
 1766,"Nord, Hollande & Flandres",6621421
+1766,Levant & Barbarie,28727120
+1766,Angleterre & Amérique du Nord,996199
 1766,Colonies françaises,15233184
 1766,Italie & Espagne,29332831
-1766,Levant & Barbarie,28727120
 1766,total,80910757.86589214
-1767,Angleterre & Amérique du Nord,1453545
 1767,"Nord, Hollande & Flandres",5833989
+1767,Levant & Barbarie,30196666
+1767,Angleterre & Amérique du Nord,1453545
 1767,Colonies françaises,15713062
 1767,Italie & Espagne,33149524
-1767,Levant & Barbarie,30196666
 1767,total,86346788.65913217
-1768,Angleterre & Amérique du Nord,631801
 1768,"Nord, Hollande & Flandres",5325117
+1768,Levant & Barbarie,36841976
+1768,Angleterre & Amérique du Nord,631801
 1768,Colonies françaises,14832167
 1768,Italie & Espagne,35541952
-1768,Levant & Barbarie,36841976
 1768,total,93173015.27424042
-1769,Angleterre & Amérique du Nord,980424
 1769,"Nord, Hollande & Flandres",4953545
+1769,Levant & Barbarie,34880045
+1769,Angleterre & Amérique du Nord,980424
 1769,Colonies françaises,15723153
 1769,Italie & Espagne,26225262
-1769,Levant & Barbarie,34880045
 1769,total,82762431.8833999
-1770,Angleterre & Amérique du Nord,1244772
 1770,"Nord, Hollande & Flandres",6221725
+1770,Levant & Barbarie,32728211
+1770,Angleterre & Amérique du Nord,1244772
 1770,Colonies françaises,16921071
 1770,Italie & Espagne,31745826
-1770,Levant & Barbarie,32728211
 1770,total,88861607.23503114
-1771,Angleterre & Amérique du Nord,1303138
 1771,"Nord, Hollande & Flandres",7323122
+1771,Levant & Barbarie,35888750
+1771,Angleterre & Amérique du Nord,1303138
 1771,Colonies françaises,13073987
 1771,Italie & Espagne,39938354
-1771,Levant & Barbarie,35888750
 1771,total,97527353.57682055
-1772,Angleterre & Amérique du Nord,989058
 1772,"Nord, Hollande & Flandres",10147713
+1772,Levant & Barbarie,32023956
+1772,Angleterre & Amérique du Nord,989058
 1772,Colonies françaises,18598717
 1772,Italie & Espagne,30335002
-1772,Levant & Barbarie,32023956
 1772,total,92094448.76964861
-1773,Angleterre & Amérique du Nord,2097400
 1773,"Nord, Hollande & Flandres",7815008
+1773,Levant & Barbarie,36308973
+1773,Angleterre & Amérique du Nord,2097400
 1773,Colonies françaises,21230042
 1773,Italie & Espagne,40757653
-1773,Levant & Barbarie,36308973
 1773,total,108209078.53882226
-1774,Angleterre & Amérique du Nord,1633440
 1774,"Nord, Hollande & Flandres",9304648
+1774,Levant & Barbarie,25656920
+1774,Angleterre & Amérique du Nord,1633440
 1774,Colonies françaises,20112082
 1774,Italie & Espagne,24326918
-1774,Levant & Barbarie,25656920
 1774,total,81034010.6166285
-1775,Angleterre & Amérique du Nord,2397020
 1775,"Nord, Hollande & Flandres",5770921
+1775,Levant & Barbarie,25163443
+1775,Angleterre & Amérique du Nord,2397020
 1775,Colonies françaises,16936774
 1775,Italie & Espagne,29859782
-1775,Levant & Barbarie,25163443
 1775,total,80127942.99381651
-1776,Angleterre & Amérique du Nord,1273574
 1776,"Nord, Hollande & Flandres",7446812
+1776,Levant & Barbarie,27351699
+1776,Angleterre & Amérique du Nord,1273574
 1776,Colonies françaises,22254355
 1776,Italie & Espagne,46582556
-1776,Levant & Barbarie,27351699
 1776,total,104908999.16201356
-1777,Angleterre & Amérique du Nord,282045
 1777,"Nord, Hollande & Flandres",7108189
+1777,Levant & Barbarie,27604526
+1777,Angleterre & Amérique du Nord,282045
 1777,Colonies françaises,19473531
 1777,Italie & Espagne,35374780
-1777,Levant & Barbarie,27604526
 1777,total,89843072.74581158
-1778,Angleterre & Amérique du Nord,141865
 1778,"Nord, Hollande & Flandres",5556925
+1778,Levant & Barbarie,13749698
+1778,Angleterre & Amérique du Nord,141865
 1778,Colonies françaises,15356258
 1778,Italie & Espagne,29731856
-1778,Levant & Barbarie,13749698
 1778,total,64536603.70214123
 1779,"Nord, Hollande & Flandres",4775101
+1779,Levant & Barbarie,19823847
 1779,Colonies françaises,3447214
 1779,Italie & Espagne,27444088
-1779,Levant & Barbarie,19823847
 1779,total,55490251.31357412
 1780,"Nord, Hollande & Flandres",3905881
+1780,Levant & Barbarie,23148652
 1780,Colonies françaises,6205315
 1780,Italie & Espagne,32168394
-1780,Levant & Barbarie,23148652
 1780,total,65428244.06186197
-1789,Angleterre & Amérique du Nord,2101373
 1789,"Nord, Hollande & Flandres",6365855
+1789,Levant & Barbarie,39501030
+1789,Angleterre & Amérique du Nord,2101373
 1789,Colonies françaises,31862823
 1789,Italie & Espagne,83851184
-1789,Levant & Barbarie,39501030
 1789,total,163682267.68456197
-1750,Angleterre & Amérique du Nord,6165935
 1750,"Nord, Hollande & Flandres",10720290
+1750,Levant & Barbarie,27495758
+1750,Angleterre & Amérique du Nord,6165935
 1750,Colonies françaises,8107783
 1750,Italie & Espagne,23492869
-1750,Levant & Barbarie,27495758
 1750,total,75982636.59665269
diff --git a/data/intro_data_world.csv b/data/intro_data_world.csv
index 3192e20..1abd98b 100644
--- a/data/intro_data_world.csv
+++ b/data/intro_data_world.csv
@@ -1,138 +1,138 @@
 partner,latitude,longitude,toflit_value,navigo_mean_tonnage,navigo_nb_ships,scope,navigo_nb_ships_pointcalls
 Levant et Barbarie,28.597,35.147,52741732.21563774,129.44983818770226,309,world,
+Malte,14.2135409,35.9426153,0,98.25,20,world,
+Nord,18.479,56.475,4461602.916140361,184.25531914893617,47,world,
+États ecclésiastiques,12.3711899,41.9102088,3373112.912473769,101.29310344827586,116,world,
 Angleterre,-1.835,52.829,2187052.80401517,157.74193548387098,31,world,
+Gênes,8.7260246,44.8,7478607.33071344,24.171122994652407,561,world,
+Venise,12.2225255,45.4046658,405739.75908807997,87.5,2,world,
 Espagne,-3.867,40.33,18703965.105788324,65.58241758241758,455,world,
-Amériques,-98.569,37.545,46283041.0,207.75510204081633,98,world,
-Royaume de Piemont et Sardaigne,9,38.5,9865451.315200962,49.025,200,world,
-République de Raguse,18.073,42.645,0,150.0,1,world,
 Flandre et autres états de l'Empereur,4.2764,50.8242,1106624.8602758902,167.22222222222223,36,world,
+Amériques,-98.569,37.545,46283041.0,207.75510204081633,98,world,
 Afrique,-15.414,13.454,419308.0,0,0,world,
-États ecclésiastiques,12.3711899,41.9102088,3373112.912473769,101.29310344827586,116,world,
 Naples,16,40.8,28949988.944752116,94.93957703927492,331,world,
+République de Raguse,18.073,42.645,0,150.0,1,world,
+Royaume de Piemont et Sardaigne,9,38.5,9865451.315200962,49.025,200,world,
+Inconnu,-16.414,43.87,24915187.0,31.85185185185185,27,world,
 Allemagne,10.4478,51.6,2052.0,0,0,world,
-Asie,76.64,-7.8,1660684.0,0,0,world,
-Duché de Massa et Carrare,10.0272806,44,0,30.0,35,world,
 "Milanais, Toscane et Lucques",9.0953317,46,6671111.456386602,70.26785714285714,112,world,
-Gênes,8.7260246,44.8,7478607.33071344,24.171122994652407,561,world,
 Portugal,-8.102,38.139,304088.001869,156.53846153846155,13,world,
-Venise,12.2225255,45.4046658,405739.75908807997,87.5,2,world,
-Malte,14.2135409,35.9426153,0,98.25,20,world,
-Hollande,4.9878,52.2984,2942041.4251656006,242.30769230769232,13,world,
-Nord,18.479,56.475,4461602.916140361,184.25531914893617,47,world,
 États-Unis d'Amérique,-98.569,43.87,1197882.6939885,184.44444444444446,9,world,
-Inconnu,-16.414,43.87,24915187.0,31.85185185185185,27,world,
+Duché de Massa et Carrare,10.0272806,44,0,30.0,35,world,
 Maroc,-8.1521827,31.6703932,0,74.44444444444444,9,world,
-Port-Bail,-1.69982,49.335336,0,14.59073359073359,75,france,259
-Le Canet,3.007307,42.705814,0,41.77777777777778,9,france,9
-La Flotte-en-Ré,-1.328716,46.188459,0,24.16923076923077,194,france,195
-île de Bouin,-1.998682,46.975134,0,30.27173913043478,192,france,184
-Argenton,-4.75,48.516667,0,45.833333333333336,6,france,6
+Asie,76.64,-7.8,1660684.0,0,0,world,
+Hollande,4.9878,52.2984,2942041.4251656006,242.30769230769232,13,world,
+Saint-Pierre-et-Miquelon,-56.333333,46.833333,0,71.9192546583851,160,france,161
+La Teste,-1.15,44.633333,0,30.25,70,france,20
 Mortagne,-0.783333,45.483333,0,31.76923076923077,13,france,13
-Montpellier,3.8329698,43.6100709,10218661.455983007,0,0,france,0
-Bastia,9.45,42.702778,0,1.7769516728624535,268,france,269
-La Tremblade,-1.133333,45.766667,0,91.84033613445378,120,france,119
-Saint-Denis d'Oléron,-1.383333,46.033333,0,19.417721518987342,79,france,79
-Portsall,-4.7,48.55,0,8.869565217391305,22,france,23
-La Rochelle,-1.2176732,46.1621033,23933450.373430237,51.02047502047502,1224,france,1221
-Quillebeuf,0.516667,49.466667,0,47.163333333333334,306,france,300
-Dunkerque,2.366667,51.05,0,49.04993252361673,2231,france,2223
-Amiens,2.2022809,49.8987918,17380138.10063795,0,0,france,0
-Les Sables-d'Olonne,-1.783333,46.5,0,42.82857142857143,282,france,280
-Saint-Malo,-2.0890353,48.6463833,10363013.126826983,57.35334088335221,883,france,883
-Lorient,-3.4214692,47.7494125,7925424.063117171,50.61230541141586,906,france,1349
-Champagné-les-Marais,-1.133333,46.366667,0,39.0,3,france,3
-Le Château-d'Oléron,-1.2,45.9,0,9.608695652173912,92,france,92
-Isigny,-1.1,49.316667,0,28.150234741784036,203,france,213
-Moricq,-1.374028,46.396209,0,27.744897959183675,96,france,98
-Saint-Martin-de-Ré,-1.366667,46.2,0,34.509761388286336,461,france,461
-Étaples,1.65,50.516667,0,47.28,25,france,25
+Calvi,8.75,42.566667,0,15.0,4,france,4
+Abbeville,1.833333,50.1,0,50.303030303030305,60,france,33
+Saint-Jean-de-Luz,-1.654143,43.388103,0,47.54545454545455,33,france,33
+île de Bouin,-1.998682,46.975134,0,30.27173913043478,192,france,184
+Penpoul,-3.966667,48.683333,0,27.8,20,france,20
 Caudebec,0.725362,49.524483,0,73.34615384615384,26,france,26
-Marans,-0.995682,46.312468,0,24.244642857142857,570,france,560
-Charleville,4.6480131,49.2,8979295.42119739,0,0,france,0
-Cherbourg,-1.615534,49.640322,0,54.73691275167785,745,france,745
-Touques,0.1,49.333333,0,48.95175438596491,228,france,228
-Pornic,-2.1,47.116667,0,15.0,19,france,19
 Le Tréport,1.366667,50.066667,0,40.3859649122807,57,france,57
 Bourgneuf,-1.952934,47.045002,0,41.0,45,france,45
-Saint-Laurent-de-la-Salanque,2.983333,42.766667,0,6.235294117647059,51,france,51
-Rochefort,-0.97043,45.943666,0,64.20181405895691,441,france,441
-Soubise,-1,45.933333,0,32.891891891891895,37,france,37
+Tonnay-Charente,-0.9,45.95,0,44.37516869095816,711,france,741
+Bordeaux,-0.6684127,44.8638098,250634332.2361999,123.8234456573327,2225,france,2107
+Marennes,-1.116667,45.816667,0,62.352088661551576,1172,france,1173
+îles Chausey,-1.833333,48.883333,0,38.666666666666664,6,france,6
+La Hougue,-1.266667,49.6,0,17.21556886227545,333,france,334
+Châlons,4.338868,48.9656081,10480557.666354734,0,0,france,0
+Saint-Nazaire,-2.2,47.283333,0,50.30769230769231,13,france,13
+Soisson,3.302947,49.3765829,63867.0,0,0,france,0
+Saint-Denis d'Oléron,-1.383333,46.033333,0,19.417721518987342,79,france,79
+Le Conquet,-4.766667,48.366667,0,30.0,38,france,38
+Saint-Tropez,6.633333,43.266667,0,32.49719626168224,535,france,535
 Saint-Gilles-sur-Vie,-1.945124,46.697882,0,35.227586206896554,145,france,145
-Ribérou,-0.935826,45.6755,0,15.270833333333334,480,france,480
-Saint-Jean-de-Luz,-1.654143,43.388103,0,47.54545454545455,33,france,33
+La Tranche-sur-Mer,-1.433333,46.333333,0,14.282051282051283,38,france,39
 Chaillevette,-1.05,45.733333,0,42.38775510204081,0,france,49
 Le Crotoy,1.616667,50.216667,0,56.92,0,france,25
-Besançon,5.9298594,47.2602913,19867619.263392746,0,0,france,0
-Noirmoutier,-2.25,47,0,46.85130111524163,272,france,269
-Le Conquet,-4.766667,48.366667,0,30.0,38,france,38
-Roscoff,-3.983333,48.733333,0,23.273858921161825,242,france,241
-Lyon,4.7527295,45.7580409,7725437.628687239,0,0,france,0
-Rouen,1.0499721,49.4412841,150323252.0,62.82879177377892,1945,france,1945
-Soisson,3.302947,49.3765829,63867.0,0,0,france,0
-Gravelines,2.116667,50.983333,0,54.027027027027025,37,france,37
-Saint-Quentin,3.2377845,49.847577,11615.0,0,0,france,0
-Landerneau,-4.25,48.45,0,39.15686274509804,102,france,102
+Pornic,-2.1,47.116667,0,15.0,19,france,19
+La Tremblade,-1.133333,45.766667,0,91.84033613445378,120,france,119
+Charleville,4.6480131,49.2,8979295.42119739,0,0,france,0
+Granville,-1.597853,48.838204,0,41.15596330275229,572,france,545
+Langres,5.2951516,47.8597242,1283994.241844011,0,0,france,0
+Genêts,-1.475315,48.683934,0,13.0,3,france,3
+Port-Bail,-1.69982,49.335336,0,14.59073359073359,75,france,259
+Barfleur,-1.25,49.666667,0,20.70967741935484,93,france,93
+Blaye,-0.666667,45.133333,0,38.66315789473684,0,france,95
 Grenoble,5.6743405,45.1842864,33979992.02184212,0,0,france,0
-Narbonne,2.8688814,43.1494672,1496874.1524529597,0,0,france,0
-Honfleur,0.231886,49.420164,0,65.66214382632293,737,france,737
-îles Chausey,-1.833333,48.883333,0,38.666666666666664,6,france,6
-Flandre,2.260707,50.016986,82110099.0,0,0,france,0
-La Teste,-1.15,44.633333,0,30.25,70,france,20
-Cayenne,-52.333333,4.933333,0,16.333333333333332,24,france,24
-Bordeaux,-0.6684127,44.8638098,250634332.2361999,123.8234456573327,2225,france,2107
+Cherbourg,-1.615534,49.640322,0,54.73691275167785,745,france,745
+Nantes,-1.642735,47.2383198,99155476.17309566,100.56303116147309,1412,france,1412
+Saint-Valery-en-Caux,0.733333,49.866667,0,44.977777777777774,180,france,180
+Saint-Malo,-2.0890353,48.6463833,10363013.126826983,57.35334088335221,883,france,883
+Argenton,-4.75,48.516667,0,45.833333333333336,6,france,6
 Ars-en-Ré,-1.516667,46.216667,0,75.91076115485565,381,france,381
-Granville,-1.597853,48.838204,0,41.15596330275229,572,france,545
-Le Havre,0.133333,49.5,0,93.45357751277683,2248,france,2348
-Marseille,5.2158406,43.280477,213669273.7414957,66.98986602542082,4681,france,5822
+Mesquer,-2.458978,47.399761,0,29.5,24,france,24
+La Roche-Bernard,-2.3,47.516667,0,49.8,20,france,20
+Valenciennes,3.4729976,50.3620936,10350989.0,0,0,france,0
+Rouen,1.0499721,49.4412841,150323252.0,62.82879177377892,1945,france,1945
+Beauvoir-sur-Mer,-2.05,46.916667,0,31.65573770491803,122,france,122
+Ribérou,-0.935826,45.6755,0,15.270833333333334,480,france,480
+Caen,-0.4134422,49.1846898,1079239.8172033997,0,0,france,0
+Pont-Audemer,0.516667,49.35,0,20.235955056179776,89,france,89
+Moricq,-1.374028,46.396209,0,27.744897959183675,96,france,98
+Grandcamp,-1.033333,49.383333,0,7.631578947368421,19,france,19
+Toulon,5.8922396,43.1364193,5522175.132875492,0,0,france,0
+Amiens,2.2022809,49.8987918,17380138.10063795,0,0,france,0
+Saint-Valery-sur-Somme,1.633333,50.183333,0,66.77622377622377,282,france,286
+Boulogne-sur-Mer,1.616667,50.716667,0,12.77577045696068,1872,france,1882
 Talmont,-1.618967,46.466277,0,16.952380952380953,21,france,21
+Cayenne,-52.333333,4.933333,0,16.333333333333332,24,france,24
+Soubise,-1,45.933333,0,32.891891891891895,37,france,37
+Champagné-les-Marais,-1.133333,46.366667,0,39.0,3,france,3
+Dunkerque,2.366667,51.05,0,49.04993252361673,2231,france,2223
+La Flotte-en-Ré,-1.328716,46.188459,0,24.16923076923077,194,france,195
+Saint-Laurent-de-la-Salanque,2.983333,42.766667,0,6.235294117647059,51,france,51
+Noirmoutier,-2.25,47,0,46.85130111524163,272,france,269
+Landerneau,-4.25,48.45,0,39.15686274509804,102,france,102
 Diélette,-1.85,49.55,0,3.0485436893203883,103,france,103
-Marennes,-1.116667,45.816667,0,62.352088661551576,1172,france,1173
-Nantes,-1.642735,47.2383198,99155476.17309566,100.56303116147309,1412,france,1412
-Bourg,-0.566667,45.05,0,36.666666666666664,0,france,3
-Grandcamp,-1.033333,49.383333,0,7.631578947368421,19,france,19
 Harfleur,0.199013,49.509294,0,23.03846153846154,131,france,104
-Calvi,8.75,42.566667,0,15.0,4,france,4
-Royan,-1.033333,45.633333,0,19.1,21,france,20
-Le Passage,-4.383333,48.383333,0,5.392156862745098,51,france,51
-Genêts,-1.475315,48.683934,0,13.0,3,france,3
-Bayonne,-1.5022883,43.4844312,27236435.20782915,63.85758039816233,675,france,653
-Socoa,-1.683333,43.383333,0,116.78260869565217,0,france,23
-Barfleur,-1.25,49.666667,0,20.70967741935484,93,france,93
-La Hougue,-1.266667,49.6,0,17.21556886227545,333,france,334
-Pont-Audemer,0.516667,49.35,0,20.235955056179776,89,france,89
-Le Croisic,-2.516667,47.3,0,74.868,250,france,250
-La Tranche-sur-Mer,-1.433333,46.333333,0,14.282051282051283,38,france,39
-Aber-Ildut,-4.75,48.466667,0,32.53846153846154,39,france,39
-Saint-Tropez,6.633333,43.266667,0,32.49719626168224,535,france,535
-Saint-Michel-en-l'Herm,-1.25,46.35,0,9.568181818181818,44,france,44
-Abbeville,1.833333,50.1,0,50.303030303030305,60,france,33
 Courtils,-1.433333,48.633333,0,31.157894736842106,19,france,19
-La Perrotine,-1.243436,45.964614,0,18.11842105263158,76,france,76
-Baie d'Authie,1.583333,50.366667,0,46.0,0,france,2
-Langres,5.2951516,47.8597242,1283994.241844011,0,0,france,0
-Calais,1.833333,50.95,0,25.17488789237668,1117,france,1115
-Omonville,-1.85,49.7,0,2.3636363636363638,33,france,33
-Le Pouliguen,-2.433333,47.266667,0,50.348837209302324,86,france,86
-Penpoul,-3.966667,48.683333,0,27.8,20,france,20
-Ajaccio,8.736863,41.918584,0,2.504424778761062,113,france,113
+Saint-Quentin,3.2377845,49.847577,11615.0,0,0,france,0
+La Rochelle,-1.2176732,46.1621033,23933450.373430237,51.02047502047502,1224,france,1221
+Besançon,5.9298594,47.2602913,19867619.263392746,0,0,france,0
 Collioure,3.082595,42.524957,0,51.54961832061068,262,france,262
-Mesquer,-2.458978,47.399761,0,29.5,24,france,24
+Le Pouliguen,-2.433333,47.266667,0,50.348837209302324,86,france,86
+Les Sables-d'Olonne,-1.783333,46.5,0,42.82857142857143,282,france,280
+Narbonne,2.8688814,43.1494672,1496874.1524529597,0,0,france,0
+Saint-Martin-de-Ré,-1.366667,46.2,0,34.509761388286336,461,france,461
+Gravelines,2.116667,50.983333,0,54.027027027027025,37,france,37
+Marans,-0.995682,46.312468,0,24.244642857142857,570,france,560
+Rochefort,-0.97043,45.943666,0,64.20181405895691,441,france,441
+Touques,0.1,49.333333,0,48.95175438596491,228,france,228
+Socoa,-1.683333,43.383333,0,116.78260869565217,0,france,23
+Auch,0.484152,43.6626547,2369490.40109293,0,0,france,0
+Quillebeuf,0.516667,49.466667,0,47.163333333333334,306,france,300
+Isigny,-1.1,49.316667,0,28.150234741784036,203,france,213
+La Perrotine,-1.243436,45.964614,0,18.11842105263158,76,france,76
+Lorient,-3.4214692,47.7494125,7925424.063117171,50.61230541141586,906,france,1349
+Le Havre,0.133333,49.5,0,93.45357751277683,2248,france,2348
+Bayonne,-1.5022883,43.4844312,27236435.20782915,63.85758039816233,675,france,653
+Lyon,4.7527295,45.7580409,7725437.628687239,0,0,france,0
+Le Croisic,-2.516667,47.3,0,74.868,250,france,250
 Fécamp,0.366667,49.75,0,42.86725663716814,226,france,226
-Meschers,-0.95,45.566667,0,25.0,0,france,1
-Brest,-4.483333,48.4,0,77.2,530,france,530
-Saint-Nazaire,-2.2,47.283333,0,50.30769230769231,13,france,13
-Beauvoir-sur-Mer,-2.05,46.916667,0,31.65573770491803,122,france,122
-Toulon,5.8922396,43.1364193,5522175.132875492,0,0,france,0
-Valenciennes,3.4729976,50.3620936,10350989.0,0,0,france,0
-La Roche-Bernard,-2.3,47.516667,0,49.8,20,france,20
-Blaye,-0.666667,45.133333,0,38.66315789473684,0,france,95
-Saint-Pierre-et-Miquelon,-56.333333,46.833333,0,71.9192546583851,160,france,161
+Bourg,-0.566667,45.05,0,36.666666666666664,0,france,3
 Esnandes,-1.083333,46.25,0,28.0,1,france,1
-Châlons,4.338868,48.9656081,10480557.666354734,0,0,france,0
-Auch,0.484152,43.6626547,2369490.40109293,0,0,france,0
+Omonville,-1.85,49.7,0,2.3636363636363638,33,france,33
+Honfleur,0.231886,49.420164,0,65.66214382632293,737,france,737
+Royan,-1.033333,45.633333,0,19.1,21,france,20
+Calais,1.833333,50.95,0,25.17488789237668,1117,france,1115
+Meschers,-0.95,45.566667,0,25.0,0,france,1
+Ajaccio,8.736863,41.918584,0,2.504424778761062,113,france,113
+Le Château-d'Oléron,-1.2,45.9,0,9.608695652173912,92,france,92
+Saint-Michel-en-l'Herm,-1.25,46.35,0,9.568181818181818,44,france,44
+Aber-Ildut,-4.75,48.466667,0,32.53846153846154,39,france,39
 Dieppe,1.083333,49.933333,0,57.61073825503356,756,france,745
-Boulogne-sur-Mer,1.616667,50.716667,0,12.77577045696068,1872,france,1882
-Caen,-0.4134422,49.1846898,1079239.8172033997,0,0,france,0
-Tonnay-Charente,-0.9,45.95,0,44.37516869095816,711,france,741
-Saint-Valery-sur-Somme,1.633333,50.183333,0,66.77622377622377,282,france,286
-Saint-Valery-en-Caux,0.733333,49.866667,0,44.977777777777774,180,france,180
+Brest,-4.483333,48.4,0,77.2,530,france,530
+Le Canet,3.007307,42.705814,0,41.77777777777778,9,france,9
+Bastia,9.45,42.702778,0,1.7769516728624535,268,france,269
+Étaples,1.65,50.516667,0,47.28,25,france,25
+Baie d'Authie,1.583333,50.366667,0,46.0,0,france,2
+Marseille,5.2158406,43.280477,213669273.7414957,66.98986602542082,4681,france,5822
+Montpellier,3.8329698,43.6100709,10218661.455983007,0,0,france,0
+Flandre,2.260707,50.016986,82110099.0,0,0,france,0
+Roscoff,-3.983333,48.733333,0,23.273858921161825,242,france,241
+Portsall,-4.7,48.55,0,8.869565217391305,22,france,23
+Le Passage,-4.383333,48.383333,0,5.392156862745098,51,france,51
diff --git a/data/share_of_strangers_1787_french_ports.csv b/data/share_of_strangers_1787_french_ports.csv
index 928e278..242c22d 100644
--- a/data/share_of_strangers_1787_french_ports.csv
+++ b/data/share_of_strangers_1787_french_ports.csv
@@ -1,11 +1,11 @@
 port,share_of_strangers
-Nantes,0.2616634929270947
+Rouen,0.14707355267446204
+Marennes,0.15979851224198235
 Bordeaux,0.4868977364442108
-La Rochelle,0.08350746932242575
-Le Havre,0.3310994539239973
+Nantes,0.2616634929270947
+Marseille,0.3721170395869191
+Dunkerque,0.5573914096936826
 Saint Malo,0.15947060909820612
+Le Havre,0.3310994539239973
 Lorient,0.2895682775563108
-Dunkerque,0.5573914096936826
-Rouen,0.14707355267446204
-Marseille,0.3721170395869191
-Marennes,0.15979851224198235
+La Rochelle,0.08350746932242575
diff --git a/data/tradeDynamics.csv b/data/tradeDynamics.csv
index 3daabf4..e338c2a 100644
--- a/data/tradeDynamics.csv
+++ b/data/tradeDynamics.csv
@@ -1,253 +1,253 @@
 year,direction_ferme,total_value,total_relative,total_slope,total_reg,total_relative,total_peace_reg_memory,total_peace_reg_no_memory,total_avg_war_loss_memory,total_avg_war_loss_no_memory,imports_value,imports_relative,imports_slope,imports_reg,imports_relative,imports_peace_reg_memory,imports_peace_reg_no_memory,imports_avg_war_loss_memory,imports_avg_war_loss_no_memory,exports_value,exports_relative,exports_slope,exports_reg,exports_relative,exports_peace_reg_memory,exports_peace_reg_no_memory,exports_avg_war_loss_memory,exports_avg_war_loss_no_memory,total_no_colonial_product_value,total_no_colonial_product_relative,total_no_colonial_product_slope,total_no_colonial_product_reg,total_no_colonial_product_relative,total_no_colonial_product_peace_reg_memory,total_no_colonial_product_peace_reg_no_memory,total_no_colonial_product_avg_war_loss_memory,total_no_colonial_product_avg_war_loss_no_memory,total_no_colonial_trade_value,total_no_colonial_trade_relative,total_no_colonial_trade_slope,total_no_colonial_trade_reg,total_no_colonial_trade_relative,total_no_colonial_trade_peace_reg_memory,total_no_colonial_trade_peace_reg_no_memory,total_no_colonial_trade_avg_war_loss_memory,total_no_colonial_trade_avg_war_loss_no_memory,imports_no_colonial_product_value,imports_no_colonial_product_relative,imports_no_colonial_product_slope,imports_no_colonial_product_reg,imports_no_colonial_product_relative,imports_no_colonial_product_peace_reg_memory,imports_no_colonial_product_peace_reg_no_memory,imports_no_colonial_product_avg_war_loss_memory,imports_no_colonial_product_avg_war_loss_no_memory,exports_no_colonial_product_value,exports_no_colonial_product_relative,exports_no_colonial_product_slope,exports_no_colonial_product_reg,exports_no_colonial_product_relative,exports_no_colonial_product_peace_reg_memory,exports_no_colonial_product_peace_reg_no_memory,exports_no_colonial_product_avg_war_loss_memory,exports_no_colonial_product_avg_war_loss_no_memory,imports_no_colonial_trade_value,imports_no_colonial_trade_relative,imports_no_colonial_trade_slope,imports_no_colonial_trade_reg,imports_no_colonial_trade_relative,imports_no_colonial_trade_peace_reg_memory,imports_no_colonial_trade_peace_reg_no_memory,imports_no_colonial_trade_avg_war_loss_memory,imports_no_colonial_trade_avg_war_loss_no_memory,exports_no_colonial_trade_value,exports_no_colonial_trade_relative,exports_no_colonial_trade_slope,exports_no_colonial_trade_reg,exports_no_colonial_trade_relative,exports_no_colonial_trade_peace_reg_memory,exports_no_colonial_trade_peace_reg_no_memory,exports_no_colonial_trade_avg_war_loss_memory,exports_no_colonial_trade_avg_war_loss_no_memory
-1760,Marseille,,0.0,1.1,123892979.00876981,0.0,175520624.09041402,131780937.83901428,-39.5%,-30.6%,,0.0,1.8,64954201.62291968,0.0,92198626.5761469,67484642.45121136,-40.0%,-29.8%,30709015.25629021,0.17186536089365806,0.4,56535331.52712239,0.17186536089365806,78231122.41457492,60257995.12915271,-41.6%,-33.6%,,,0.9,105537411.15647595,,151115573.60370654,108219691.23582856,-38.2%,-27.0%,,,1.5,107448222.1503217,,170853261.36391908,107973316.1887696,-35.9%,-21.0%,,,1.6,55824081.2649951,,79506817.46128605,53975187.13919997,-38.0%,-24.8%,29649339.857185278,,0.1,47835613.22268079,,65708676.116741836,49276088.73624019,-40.0%,-29.9%,,,1.5,53500382.66948323,,78062480.50982556,48822774.86461871,-35.4%,-19.2%,,,1.5,53724111.07516076,,85426630.68195939,53986658.09438469,-35.9%,-21.0%
-1760,Rouen,,0.0,2.5,51668206.01283718,0.0,39453050.01983488,39453050.01983488,30.0%,25.3%,,0.0,3.3,29087715.366060898,0.0,17286221.883924425,17286221.883924425,53.9%,47.8%,,0.0,1.3,22324476.214413438,0.0,23200403.08610315,23200403.08610315,6.6%,3.6%,,,2.0,36962207.21275573,,21418740.399368092,21418740.399368092,97.5%,93.3%,,,3.1,33095254.492183924,,13452880.620263124,13452880.620263124,157.2%,145.3%,,,3.0,21185163.367722426,,9497049.687802944,9497049.687802944,126.8%,119.7%,,,0.1,15517769.151010163,,12469872.108450146,12469872.108450146,71.2%,70.8%,,,3.1,16547627.246091932,,6726440.310131549,6726440.310131549,157.2%,145.3%,,,3.1,16547627.246091932,,6726440.310131549,6726440.310131549,157.2%,145.3%
-1760,Bordeaux,31965375.94073119,0.10772491972702726,3.7,70997473.2018887,0.10772491972702726,132267690.78987925,159614108.09390193,-49.2%,-57.2%,8626459.70177719,0.07307410999487797,4.2,26499265.270215746,0.07307410999487797,39259516.40805945,32425250.825401787,-38.5%,-53.8%,23338916.238954,0.13061803606525843,3.2,43215424.585944355,0.13061803606525843,91637344.64837465,135774288.27225086,-56.9%,-60.6%,29107079.0354503,,2.2,38639791.52370855,,68767400.49275187,78880859.98457246,-53.2%,-55.5%,11609573.402116718,,3.0,15882189.956602307,,22949308.612395998,11990108.150441632,-46.2%,-38.5%,6461837.951410677,,2.9,11985433.137891503,,14932295.717559388,8506544.158407161,-47.7%,-40.4%,22645241.08403962,,1.9,26220289.62355639,,52053509.64216892,79411194.62699646,-53.5%,-55.1%,5804786.701058359,,3.0,8162610.039296977,,11570314.018524181,5995054.075220805,-47.0%,-41.8%,5804786.701058359,,3.0,7941094.978301251,,11474654.306197977,5995054.075220805,-46.2%,-38.5%
-1760,Nantes,6693610.976483328,0.02255780462155644,1.2,31354411.511561878,0.02255780462155644,28041679.727632638,23576494.797469735,-41.9%,-38.6%,2325837.7275272883,0.019702001493909705,1.1,13535899.981942363,0.019702001493909705,15068155.072210982,11593085.504074853,-48.6%,-46.3%,4367773.2489560405,0.024444578227878336,0.6,15718358.966728695,0.024444578227878336,16972996.659406405,19289695.501967203,-24.4%,13.7%,6433357.474504799,,0.6,18894342.2509815,,13060535.30661466,8557749.16522071,-23.1%,6.9%,4243199.748488137,,-0.2,9415540.224489396,,7433905.836643499,1788295.297258121,-30.2%,53.9%,2172818.8743801382,,0.0,6846522.769027732,,5737444.098259895,1913510.86779608,-34.6%,31.5%,4260538.600124661,,0.6,10505595.110719873,,9129002.848321784,13286620.936208714,-6.7%,42.0%,2121599.8742440683,,-0.1,4733427.616830001,,3716952.9183217427,894147.6486290587,-31.5%,56.8%,2121599.8742440683,,-0.2,4707770.112244707,,3716952.9183217427,894147.6486290587,-30.2%,53.9%
-1760,Bayonne,20134008.34647001,0.0678526176863467,0.1,17973239.235413305,0.0678526176863467,17860826.442271613,17860826.442271613,22.6%,40.3%,5435098.078555205,0.0460403188046506,0.3,6441251.604562715,0.0460403188046506,6673947.3408975145,6673947.3408975145,13.4%,23.8%,14698910.267914804,0.08226357950117658,-0.4,11792018.47503929,0.08226357950117658,11269401.518039,11269401.518039,29.2%,49.7%,18944021.15999452,,0.3,15785036.946339013,,14904191.271557426,14904191.271557426,31.5%,49.0%,9336532.650077432,,0.5,10538001.443034157,,8766739.803926297,8766739.803926297,29.0%,37.4%,4820746.325038716,,0.4,5386417.142016147,,4734594.569263341,4734594.569263341,28.9%,36.9%,14123274.834955806,,0.2,10373447.742260098,,10468183.944072206,10468183.944072206,31.3%,52.7%,4668266.325038716,,0.5,5255335.598113508,,4383369.90196314,4383369.90196314,30.1%,37.3%,4668266.325038716,,0.5,5269000.721517087,,4383369.90196314,4383369.90196314,29.0%,37.4%
-1760,La Rochelle,6173162.77964594,0.020803868101919146,-0.7,14672083.634626262,0.020803868101919146,21027559.41635285,14665036.560721654,47.4%,42.5%,2857492.65888236,0.024205611581505204,-0.5,6424609.318307889,0.024205611581505204,10704296.723639173,7916840.138371825,149.9%,144.1%,3315670.12076358,0.01855640231878252,-0.8,8147421.000166069,0.01855640231878252,10321235.869733535,6855745.557451918,-0.4%,-1.6%,4803365.6951494,,-1.3,11241933.519917035,,16053108.770779466,13376406.798079938,44.1%,34.1%,2256211.15045086,,1.8,3969528.3599198293,,4745652.563204216,8361587.919887865,8.1%,-17.7%,1732702.4252254302,,-1.0,4258185.010830802,,7701332.669708904,7438366.668504211,99.7%,86.6%,3070663.26992397,,-1.4,6788423.571362341,,8352339.082439775,6097959.758600874,7.4%,2.2%,1128105.57522543,,1.8,1961254.6436518442,,2372826.2816021037,4180793.959943984,9.3%,-17.2%,1128105.57522543,,1.8,1984764.179959918,,2372826.2816021037,4180793.959943984,8.1%,-17.7%
-1755,Marseille,142798869.80244273,0.27637413106055086,1.1,117077406.12039375,0.27637413106055086,,,-39.5%,-30.6%,79420447.92118071,0.3135523337871422,1.8,59364798.24712162,0.3135523337871422,,,-40.0%,-29.8%,63378421.881262034,0.24062180912136327,0.4,55356490.140885204,0.24062180912136327,,,-41.6%,-33.6%,120718025.2021401,,0.9,100923480.75118335,,,,-38.2%,-27.0%,127785562.12080182,,1.5,99825694.18319511,,,,-35.9%,-21.0%,67530864.66140786,,1.6,51534504.25009565,,,,-38.0%,-24.8%,53187160.540732235,,0.1,47567885.824717306,,,,-40.0%,-29.9%,63892781.06040091,,1.5,49537961.70159948,,,,-35.4%,-19.2%,63892781.06040091,,1.5,49912847.09159746,,,,-35.9%,-21.0%
-1755,Rouen,48031151.68087739,0.092959894066423,2.5,45502385.845641196,0.092959894066423,,,30.0%,25.3%,24352828.677996635,0.09614509192748923,3.3,24635692.648613825,0.09614509192748923,,,53.9%,47.8%,23678323.002880752,0.08989685682908495,1.3,20959583.38392964,0.08989685682908495,,,6.6%,3.6%,31761797.162419,,2.0,33460963.978876054,,,,97.5%,93.3%,25616680.321453337,,3.1,28321662.866721146,,,,157.2%,145.3%,16248958.761210268,,3.0,18207591.000960305,,,,126.8%,119.7%,15512838.401208732,,0.1,15433641.317481143,,,,71.2%,70.8%,12808340.160726668,,3.1,14160831.433360547,,,,157.2%,145.3%,12808340.160726668,,3.1,14160831.433360547,,,,157.2%,145.3%
-1755,Bordeaux,70406283.96697909,0.13626491287708623,3.7,58987349.19979014,0.13626491287708623,,,-49.2%,-57.2%,28538401.98042751,0.1126697566903576,4.2,21527163.990778353,0.1126697566903576,,,-38.5%,-53.8%,41867881.98655157,0.15895513344522502,3.2,36882805.14974975,0.15895513344522502,,,-56.9%,-60.6%,34930179.671590865,,2.2,34550402.31698442,,,,-53.2%,-55.5%,13715763.562669301,,3.0,13687247.596389068,,,,-46.2%,-38.5%,9987974.531700868,,2.9,10355060.788166244,,,,-47.7%,-40.4%,24942205.13989,,1.9,23856919.410671473,,,,-53.5%,-55.1%,6857881.781334651,,3.0,7009906.366952718,,,,-47.0%,-41.8%,6857881.781334651,,3.0,6843623.798194619,,,,-46.2%,-38.5%
-1755,Nantes,30841541.54817666,0.05969097835114233,1.2,29557976.097433817,0.05969097835114233,,,-41.9%,-38.6%,15820236.834144201,0.06245837577413501,1.1,12827605.074138116,0.06245837577413501,,,-48.6%,-46.3%,15021304.714032458,0.05702971781824018,0.6,15249804.530000072,0.05702971781824018,,,-24.4%,13.7%,14876759.088964075,,0.6,18378201.952173512,,,,-23.1%,6.9%,6284780.831677182,,-0.2,9509642.859250639,,,,-30.2%,53.9%,5296486.928409721,,0.0,6838741.484050795,,,,-34.6%,31.5%,9580272.160554353,,0.6,10188459.370978396,,,,-6.7%,42.0%,3142390.415838591,,-0.1,4768626.145935852,,,,-31.5%,56.8%,3142390.415838591,,-0.2,4754821.429625328,,,,-30.2%,53.9%
-1755,Bayonne,18386550.5705723,0.035585484284105094,0.1,17886079.92804008,0.035585484284105094,,,22.6%,40.3%,7318646.034677398,0.028894051902257224,0.3,6354096.141425431,0.028894051902257224,,,13.4%,23.8%,11067904.535894904,0.04202028282747364,-0.4,12031460.211712789,0.04202028282747364,,,29.2%,49.7%,15999202.915834371,,0.3,15528547.327946216,,,,31.5%,49.0%,11198336.659063749,,0.5,10273815.253216485,,,,29.0%,37.4%,5949910.367980328,,0.4,5281661.857356226,,,,28.9%,36.9%,10049292.547854042,,0.2,10295060.32494334,,,,31.3%,52.7%,5599168.3295318745,,0.5,5134077.154186765,,,,30.1%,37.3%,5599168.3295318745,,0.5,5136907.626608232,,,,29.0%,37.4%
-1755,La Rochelle,,0.0,-0.7,15220389.367326215,0.0,,,47.4%,42.5%,,0.0,-0.5,6597320.402219525,0.0,,,149.9%,144.1%,,0.0,-0.8,8491126.893424744,0.0,,,-0.4%,-1.6%,,,-1.3,11980290.1466066,,,,44.1%,34.1%,,,1.8,3620011.19913971,,,,8.1%,-17.7%,,,-1.0,4468133.481145648,,,,99.7%,86.6%,,,-1.4,7266037.5944377165,,,,7.4%,2.2%,,,1.8,1790217.6575915313,,,,9.3%,-17.2%,,,1.8,1810005.599569858,,,,8.1%,-17.7%
-1780,Marseille,95011300.43057716,0.2102003969982643,1.1,155360678.9809802,0.2102003969982643,177858080.09946787,165796396.3765717,-39.5%,-30.6%,65428244.06186197,0.3026626953454921,1.8,93093693.34256062,0.3026626953454921,102971661.22121336,94417266.65641995,-40.0%,-29.8%,29583056.368715186,0.12544336869302708,0.4,61507139.82008072,0.12544336869302708,77778157.35447113,73468061.76107332,-41.6%,-33.6%,84088793.57815945,,0.9,126201146.81635578,,143476981.071206,130619501.17687808,-38.2%,-27.0%,115675003.22457734,,1.5,144220439.35275578,,149928846.00842616,136703959.3214379,-35.9%,-21.0%,59098273.96229381,,1.6,76862677.90173697,,83650388.55865665,75361773.32149582,-38.0%,-24.8%,24990519.615865637,,0.1,48921676.425342634,,62535817.585945085,57482324.882127084,-40.0%,-29.9%,57837501.61228867,,1.5,72783328.0021056,,77759143.22072354,70835665.74953486,-35.4%,-19.2%,57837501.61228867,,1.5,72110219.67637776,,74964423.00421321,68351979.66071858,-35.9%,-21.0%
-1780,Rouen,,0.0,2.5,85897443.31303592,0.0,70366163.10957097,79867615.88042514,30.0%,25.3%,,0.0,3.3,56531297.068402745,0.0,45316523.92865779,52904256.150025964,53.9%,47.8%,,0.0,1.3,28732658.22561316,0.0,24646877.070586648,26959325.78478123,6.6%,3.6%,,,2.0,55034584.66046734,,42283872.71888897,46309814.64162124,97.5%,93.3%,,,3.1,61709727.70656949,,44798943.21786077,57000171.8897382,157.2%,145.3%,,,3.0,38828367.370374836,,29797286.740127616,34846432.707909815,126.8%,119.7%,,,0.1,15858891.30668527,,12575181.644967714,12640433.564962285,71.2%,70.8%,,,3.1,30854863.853284687,,22399471.608930424,28500085.94486925,157.2%,145.3%,,,3.1,30854863.853284687,,22399471.608930424,28500085.94486925,157.2%,145.3%
-1780,Bordeaux,,0.0,3.7,148997486.43266582,0.0,153120795.8909721,228695701.79638478,-49.2%,-57.2%,32531869.528393723,0.1504882708877534,4.2,60844578.44359869,0.1504882708877534,68344272.59058487,199895051.14215633,-38.5%,-53.8%,,0.0,3.2,81451323.2643818,0.0,86332867.48406138,84533072.09778437,-56.9%,-60.6%,,,2.2,60445146.92518969,,61478007.657121785,61317497.059465215,-53.2%,-55.5%,,,3.0,28793034.39626824,,27146565.087033257,86330546.09106256,-46.2%,-38.5%,18009549.7860847,,2.9,21510874.009813897,,25347720.9773876,61041559.06664655,-47.7%,-40.4%,,,1.9,38258678.816267155,,36698847.06924672,25353646.535847593,-53.5%,-55.1%,12413681.046296002,,3.0,15007086.19259742,,15557166.656016389,51468113.244374044,-47.0%,-41.8%,,,3.0,14396517.198134195,,13573282.543516653,43165273.0455312,-46.2%,-38.5%
-1780,Nantes,,0.0,1.2,39700364.608895436,0.0,50817136.664814845,54520712.405822225,-41.9%,-38.6%,,0.0,1.1,16782372.64936562,0.0,18559389.425348256,21640040.670996133,-48.6%,-46.3%,,0.0,0.6,17741033.0775604,0.0,18681046.70635985,6011515.008847204,-24.4%,13.7%,,,0.6,21107986.6689656,,23137265.027346533,16884780.459455322,-23.1%,6.9%,,,-0.2,9048349.917007957,,7797704.880398656,22557297.654288273,-30.2%,53.9%,,,0.0,6877736.547069685,,6623468.5609585615,9247343.134184109,-34.6%,31.5%,,,0.6,11875973.583838856,,11534020.160000216,3091434.859548668,-6.7%,42.0%,,,-0.1,4595212.493153747,,4059239.2366264793,9137970.065656086,-31.5%,56.8%,,,-0.2,4524174.958503986,,3898852.4401993207,11278648.827144116,-30.2%,53.9%
-1780,Bayonne,21189102.21787706,0.046878188994886744,0.1,18326144.5070385,0.046878188994886744,14578417.209688835,9768777.207313351,22.6%,40.3%,8029685.778411877,0.037144300222602414,0.3,6801993.170243185,0.037144300222602414,5182287.291909951,4198744.616755915,13.4%,23.8%,13159416.439465184,0.05580091210408651,-0.4,10880964.615766058,0.05580091210408651,9291899.859900393,5734496.250215612,29.2%,49.7%,19624503.716763504,,0.3,16854066.12622462,,13349802.048229951,9061163.099810928,31.5%,49.0%,13661573.939025719,,0.5,11664449.87406238,,8721469.16006067,7292652.842231999,29.0%,37.4%,6874541.969512859,,0.4,5826631.394129358,,4351782.479845685,3719743.729983517,28.9%,36.9%,12749961.747250644,,0.2,10693011.510293104,,8960200.762544202,5469280.730532648,31.3%,52.7%,6830786.969512859,,0.5,5769693.057950459,,4335816.186037538,3755229.339180913,30.1%,37.3%,6830786.969512859,,0.5,5832224.93703118,,4360734.580030312,3646326.4211159665,29.0%,37.4%
-1780,La Rochelle,7694879.291011558,0.017023940041807996,-0.7,12669396.234794552,0.017023940041807996,14205047.622171113,30256841.807577323,47.4%,42.5%,3697571.203999307,0.017104491842638927,-0.5,5777810.730029467,0.017104491842638927,6268741.397501469,11315019.808775969,149.9%,144.1%,3997308.087012251,0.016950100959445737,-0.8,6906205.007297434,0.016950100959445737,7964362.342377235,15893884.862093108,-0.4%,-1.6%,4534275.061012156,,-1.3,8716371.234782198,,10195979.336607676,28503486.098193467,44.1%,34.1%,3082827.7191817546,,1.8,5739246.6438288735,,6808054.017476993,28855398.205552198,8.1%,-17.7%,2086377.8581137871,,-1.0,3512514.1241753977,,3919022.2829681407,10636643.184545847,99.7%,86.6%,2447897.2028983696,,-1.4,5171947.427449631,,6138070.634358033,15840680.734483471,7.4%,2.2%,1541413.8595908773,,1.8,2825182.963356145,,3242540.5680037225,13170261.200398115,9.3%,-17.2%,1541413.8595908773,,1.8,2869623.3219144414,,3404027.0087384963,14427699.102776071,8.1%,-17.7%
-1751,Marseille,138986808.4911104,0.29573526778480674,1.1,111895909.07830423,0.29573526778480674,,,-39.5%,-30.6%,67624214.96659152,0.31899430396494133,1.8,55241618.446420506,0.31899430396494133,,,-40.0%,-29.8%,71362593.52451889,0.27662232233148176,0.4,54431139.752838,0.27662232233148176,,,-41.6%,-33.6%,120241210.20059922,,0.9,97377999.32789785,,,,-38.2%,-27.0%,121368956.53832643,,1.5,94118895.68834531,,,,-35.9%,-21.0%,61522770.47357665,,1.6,48341410.40603268,,,,-38.0%,-24.8%,58718439.72702257,,0.1,47354783.17377838,,,,-40.0%,-29.9%,60684478.26916321,,1.5,46580390.89976433,,,,-35.4%,-19.2%,60684478.26916321,,1.5,47059447.84417257,,,,-35.9%,-21.0%
-1751,Rouen,,0.0,2.5,41103877.9911512,0.0,,,30.0%,25.3%,,0.0,3.3,21569938.636433113,0.0,,,53.9%,47.8%,,0.0,1.3,19928001.173449438,0.0,,,6.6%,3.6%,,,2.0,30900313.760020647,,,,97.5%,93.3%,,,3.1,25003520.847042214,,,,157.2%,145.3%,,,3.0,16129801.644193344,,,,126.8%,119.7%,,,0.1,15366667.55401524,,,,71.2%,70.8%,,,3.1,12501760.423521174,,,,157.2%,145.3%,,,3.1,12501760.423521174,,,,157.2%,145.3%
-1751,Bordeaux,60095279.15993086,0.12787036171207272,3.7,50859451.26798977,0.12787036171207272,,,-49.2%,-57.2%,26737232.39556796,0.12612382771743358,4.2,18230106.611455105,0.12612382771743358,,,-38.5%,-53.8%,33358046.7643629,0.129305563442419,3.2,32491672.882743992,0.129305563442419,,,-56.9%,-60.6%,36672930.18995942,,2.2,31592775.124542758,,,,-53.2%,-55.5%,26849151.44184756,,3.0,12151802.810083793,,,,-46.2%,-38.5%,16425674.82652786,,2.9,9211954.582191404,,,,-47.7%,-40.4%,20247255.363431558,,1.9,22120547.236557465,,,,-53.5%,-55.1%,13424575.72092378,,3.0,6206099.746754283,,,,-47.0%,-41.8%,13424575.72092378,,3.0,6075901.405041928,,,,-46.2%,-38.5%
-1751,Nantes,,0.0,1.2,28195222.447184302,0.0,,,-41.9%,-38.6%,,0.0,1.1,12287749.127954174,0.0,,,-48.6%,-46.3%,15755534.798751967,0.06107306938203977,0.6,14885037.613159008,0.06107306938203977,,,-24.4%,13.7%,,,0.6,17975459.99522696,,,,-23.1%,6.9%,,,-0.2,9585601.676477347,,,,-30.2%,53.9%,,,0.0,6832522.823995082,,,,-34.6%,31.5%,8942077.851577858,,0.6,9941657.68212455,,,,-6.7%,42.0%,,,-0.1,4796973.330188454,,,,-31.5%,56.8%,,,-0.2,4792800.838238681,,,,-30.2%,53.9%
-1751,Bayonne,20085182.79129176,0.04273712718332816,0.1,17816656.902903322,0.04273712718332816,,,22.6%,40.3%,8806950.52970627,0.041543802847326776,0.3,6285221.625540479,0.041543802847326776,,,13.4%,23.8%,11278232.26158549,0.043717732861288286,-0.4,12226509.503517043,0.043717732861288286,,,29.2%,49.7%,16501515.797100969,,0.3,15326359.62669531,,,,31.5%,49.0%,15033397.056981536,,0.5,10067242.971124763,,,,29.0%,37.4%,7516698.528490768,,0.4,5199326.3882153975,,,,28.9%,36.9%,8984817.2686102,,0.2,10232777.089781402,,,,31.3%,52.7%,7516698.528490768,,0.5,5039087.967216063,,,,30.1%,37.3%,7516698.528490768,,0.5,5033621.485562364,,,,29.0%,37.4%
-1751,La Rochelle,20647303.85387986,0.04393320488866381,-0.7,15673750.804663036,0.04393320488866381,,,47.4%,42.5%,8930031.69923278,0.042124396529984634,-0.5,6738826.247586925,0.042124396529984634,,,149.9%,144.1%,11717272.154647084,0.04541958012911686,-0.8,8776502.271053104,0.04541958012911686,,,-0.4%,-1.6%,15569207.777239926,,-1.3,12605741.441664513,,,,44.1%,34.1%,4521448.841936559,,1.8,3362689.115388239,,,,8.1%,-17.7%,6264287.17146678,,-1.0,4643521.15320319,,,,99.7%,86.6%,9304920.605773145,,-1.4,7672212.211312532,,,,7.4%,2.2%,2260724.4209682797,,1.8,1664191.5696673796,,,,9.3%,-17.2%,2260724.4209682797,,1.8,1681344.557694134,,,,8.1%,-17.7%
-1773,Marseille,191943367.39045423,0.2887568111190186,1.1,143528473.3163917,0.2887568111190186,,,-39.5%,-30.6%,108209078.53882226,0.32690122493666757,1.8,82074965.06564157,0.32690122493666757,,,-40.0%,-29.8%,83734288.85163195,0.2509203397872683,0.4,59719144.27264253,0.2509203397872683,,,-41.6%,-33.6%,154538138.9824246,,0.9,118545043.06973015,,,,-38.2%,-27.0%,167201810.77750617,,1.5,130102955.13825357,,,,-35.9%,-21.0%,89319211.58882771,,1.6,68723083.40989304,,,,-38.0%,-24.8%,65218927.39359687,,0.1,48538777.730622515,,,,-40.0%,-29.9%,83600905.38875309,,1.5,65350009.07984855,,,,-35.4%,-19.2%,83600905.38875309,,1.5,65051477.56912689,,,,-35.9%,-21.0%
-1773,Rouen,69964917.04095003,0.10525420393325946,2.5,71897756.40252814,0.10525420393325946,,,30.0%,25.3%,44410546.42205017,0.1341649168583055,3.3,44800842.5569746,0.1341649168583055,,,53.9%,47.8%,25554370.61889986,0.0765768891893941,1.3,26303753.250326045,0.0765768891893941,,,6.6%,3.6%,39331512.477778554,,2.0,47877169.24795584,,,,97.5%,93.3%,42688616.16647629,,3.1,49618983.53443595,,,,157.2%,145.3%,26628464.283342242,,3.0,31409286.47092644,,,,126.8%,119.7%,12703048.194436308,,0.1,15738653.896581242,,,,71.2%,70.8%,21344308.083238143,,3.1,24809491.767217927,,,,157.2%,145.3%,21344308.083238143,,3.1,24809491.767217927,,,,157.2%,145.3%
-1773,Bordeaux,144954494.45848155,0.2180674338804072,3.7,114947974.94736898,0.2180674338804072,,,-49.2%,-57.2%,75613889.3156951,0.22843067673529938,4.2,45485824.11015015,0.22843067673529938,,,-38.5%,-53.8%,69340605.14278643,0.20778785420046803,3.2,65246522.29095541,0.20778785420046803,,,-56.9%,-60.6%,66530868.97102955,,2.2,51682927.48687178,,,,-53.2%,-55.5%,51819951.16812219,,3.0,23380590.125463914,,,,-46.2%,-38.5%,36732577.483376175,,2.9,17528975.88281916,,,,-47.7%,-40.4%,29798291.487653375,,1.9,33519505.196434766,,,,-53.5%,-55.1%,25909975.584061094,,3.0,12126425.755704427,,,,-47.0%,-41.8%,25909975.584061094,,3.0,11690295.062732019,,,,-46.2%,-38.5%
-1773,Nantes,,0.0,1.2,36552825.30658612,0.0,,,-41.9%,-38.6%,,0.0,1.1,15565933.904070942,0.0,,,-48.6%,-46.3%,2342934.25,0.007020897486224615,0.6,17005085.09814776,0.007020897486224615,,,-24.4%,13.7%,,,0.6,20305166.244957294,,,,-23.1%,6.9%,,,-0.2,9175208.388408864,,,,-30.2%,53.9%,,,0.0,6866795.570590443,,,,-34.6%,31.5%,2342157.25,,0.6,11377117.031658996,,,,-6.7%,42.0%,,,-0.1,4643122.570306698,,,,-31.5%,56.8%,,,-0.2,4587604.194204439,,,,-30.2%,53.9%
-1773,Bayonne,13977718.417804584,0.021027876357063185,0.1,18201846.33819041,0.021027876357063185,,,22.6%,40.3%,5139273.952221456,0.01552582253681751,0.3,6673491.578809601,0.01552582253681751,,,13.4%,23.8%,8838444.465583127,0.02648551171700548,-0.4,11191535.110493366,0.02648551171700548,,,29.2%,49.7%,12241626.234269615,,0.3,16471911.936258398,,,,31.5%,49.0%,8630619.87742167,,0.5,11257116.445965266,,,,29.0%,37.4%,4323016.038751706,,0.4,5668607.645315081,,,,28.9%,36.9%,7918610.195517911,,0.2,10580059.632284055,,,,31.3%,52.7%,4315309.938710835,,0.5,5584180.149180947,,,,30.1%,37.3%,4315309.938710835,,0.5,5628558.222982623,,,,29.0%,37.4%
-1773,La Rochelle,27086761.95964256,0.04074893086092281,-0.7,13337163.498301856,0.04074893086092281,,,47.4%,42.5%,10656918.011046315,0.032194706755688744,-0.5,5996426.369984411,0.032194706755688744,,,149.9%,144.1%,16429843.948596243,0.049234096124448255,-0.8,7317499.614943727,0.049234096124448255,,,-0.4%,-1.6%,22992573.483803757,,-1.3,9528237.453427076,,,,44.1%,34.1%,12268785.949076332,,1.8,5044455.508701947,,,,8.1%,-17.7%,7923580.668951896,,-1.0,3757338.615458018,,,,99.7%,86.6%,15068992.81485186,,-1.4,5688454.550895298,,,,7.4%,2.2%,6134392.974538166,,1.8,2486378.094079029,,,,9.3%,-17.2%,6134392.974538166,,1.8,2522227.754350978,,,,8.1%,-17.7%
-1743,Marseille,128194438.10974611,0.31081663332592446,1.1,102210718.92636839,0.31081663332592446,,,-39.5%,-30.6%,64238856.881133206,0.33771264574799886,1.8,47834494.547690324,0.33771264574799886,,,-40.0%,-29.8%,63955581.22861291,0.287794654481292,0.4,52626585.44259682,0.287794654481292,,,-41.6%,-33.6%,111400675.93140121,,0.9,90656323.30001871,,,,-38.2%,-27.0%,102514428.9526298,,1.5,83665380.5525663,,,,-35.9%,-21.0%,56034306.568348326,,1.6,42536499.42578717,,,,-38.0%,-24.8%,55366369.36305288,,0.1,46931437.67467495,,,,-40.0%,-29.9%,51257214.4763149,,1.5,41184435.74716796,,,,-35.4%,-19.2%,51257214.4763149,,1.5,41832690.27628307,,,,-35.9%,-21.0%
-1743,Rouen,,0.0,2.5,33541312.724449933,0.0,,,30.0%,25.3%,,0.0,3.3,16535494.008618398,0.0,,,53.9%,47.8%,,0.0,1.3,18014654.13809418,0.0,,,6.6%,3.6%,,,2.0,26351890.117509488,,,,97.5%,93.3%,,,3.1,19487943.225297816,,,,157.2%,145.3%,,,3.0,12658495.794249749,,,,126.8%,119.7%,,,0.1,15233590.657033354,,,,71.2%,70.8%,,,3.1,9743971.61264889,,,,157.2%,145.3%,,,3.1,9743971.61264889,,,,157.2%,145.3%
-1743,Bordeaux,61082613.590605564,0.14809918894240223,3.7,37809179.28826319,0.14809918894240223,,,-49.2%,-57.2%,22053274.816009477,0.11593714687830374,4.2,13073563.689174838,0.11593714687830374,,,-38.5%,-53.8%,39029338.77459609,0.17562869184344032,3.2,25215543.19574546,0.17562869184344032,,,-56.9%,-60.6%,39163301.752728835,,2.2,26415395.10737786,,,,-53.2%,-55.5%,16038198.739381852,,3.0,9578332.159206722,,,,-46.2%,-38.5%,11291055.367959525,,2.9,7290378.203794275,,,,-47.7%,-40.4%,27872246.384769306,,1.9,19017738.574113443,,,,-53.5%,-55.1%,8019099.369690926,,3.0,4864428.455286106,,,,-47.0%,-41.8%,8019099.369690926,,3.0,4789166.079603421,,,,-46.2%,-38.5%
-1743,Nantes,40443761.38795564,0.09805880769085955,1.2,25655305.39457165,0.09805880769085955,,,-41.9%,-38.6%,22062462.899250045,0.11598544991561131,1.1,11275241.342898563,0.11598544991561131,,,-48.6%,-46.3%,18381298.488705598,0.08271427365447546,0.6,14181470.15236688,0.08271427365447546,,,-24.4%,13.7%,24729044.711199727,,0.6,17196259.869071037,,,,-23.1%,6.9%,18598105.724679545,,-0.2,9739344.333399437,,,,-30.2%,53.9%,12284609.430581493,,0.0,6820102.463149281,,,,-34.6%,31.5%,12444435.280618234,,0.6,9465844.79909767,,,,-6.7%,42.0%,9299052.862339772,,-0.1,4854174.231452817,,,,-31.5%,56.8%,9299052.862339772,,-0.2,4869672.166699727,,,,-30.2%,53.9%
-1743,Bayonne,,0.0,0.1,17678618.18227893,0.0,,,22.6%,40.3%,,0.0,0.3,6149704.174424137,0.0,,,13.4%,23.8%,,0.0,-0.4,12626145.536004044,0.0,,,29.2%,49.7%,,,0.3,14929847.633779537,,,,31.5%,49.0%,,,0.5,9666475.340512328,,,,29.0%,37.4%,,,0.4,5038486.007359001,,,,28.9%,36.9%,,,0.2,10109338.746473791,,,,31.3%,52.7%,,,0.5,4854349.463309146,,,,30.1%,37.3%,,,0.5,4833237.670256156,,,,29.0%,37.4%
-1743,La Rochelle,,0.0,-0.7,16621388.006162459,0.0,,,47.4%,42.5%,,0.0,-0.5,7031008.510858903,0.0,,,149.9%,144.1%,,0.0,-0.8,9376348.619935522,0.0,,,-0.4%,-1.6%,,,-1.3,13956306.94917137,,,,44.1%,34.1%,,,1.8,2901618.5978671545,,,,8.1%,-17.7%,,,-1.0,5015220.214614657,,,,99.7%,86.6%,,,-1.4,8553946.688734096,,,,7.4%,2.2%,,,1.8,1438130.444400133,,,,9.3%,-17.2%,,,1.8,1450809.29893359,,,,8.1%,-17.7%
-1754,Marseille,,0.0,1.1,115759960.84636731,0.0,,,-39.5%,-30.6%,74212763.01663025,0.29940464312969123,1.8,58306013.064919606,0.29940464312969123,,,-40.0%,-29.8%,,0.0,0.4,55123688.08120715,0.0,,,-41.6%,-33.6%,,,0.9,100025188.2149806,,,,-38.2%,-27.0%,,,1.5,98367347.32771826,,,,-35.9%,-21.0%,60963457.2636041,,1.6,50716982.47076674,,,,-38.0%,-24.8%,,,0.1,47514520.42486865,,,,-40.0%,-29.9%,56397374.95040833,,1.5,48781413.68233134,,,,-35.4%,-19.2%,,,1.5,49183673.66385903,,,,-35.9%,-21.0%
-1754,Rouen,,0.0,2.5,44360489.120365426,0.0,,,30.0%,25.3%,,0.0,3.3,23830645.72569081,0.0,,,53.9%,47.8%,,0.0,1.3,20696786.488361266,0.0,,,6.6%,3.6%,,,2.0,32801564.52707814,,,,97.5%,93.3%,,,3.1,27452971.139151543,,,,157.2%,145.3%,,,3.0,17664307.796258196,,,,126.8%,119.7%,,,0.1,15416870.56083955,,,,71.2%,70.8%,,,3.1,13726485.569575746,,,,157.2%,145.3%,,,3.1,13726485.569575746,,,,157.2%,145.3%
-1754,Bordeaux,121966756.17763133,0.22341063559300056,3.7,56841048.13453862,0.22341063559300056,,,-49.2%,-57.2%,31255901.0252594,0.12609909012642048,4.2,20650825.48198282,0.12609909012642048,,,-38.5%,-53.8%,90710855.15237193,0.30433443725196857,3.2,35732300.38388651,0.30433443725196857,,,-56.9%,-60.6%,66310170.35933566,,2.2,33785999.83990045,,,,-53.2%,-55.5%,14039651.849969631,,3.0,13286092.47791907,,,,-46.2%,-38.5%,11602374.678187165,,2.9,10056629.178974777,,,,-47.7%,-40.4%,54707795.6811485,,1.9,23410448.783815417,,,,-53.5%,-55.1%,7019825.9249848155,,3.0,6799685.88375158,,,,-47.0%,-41.8%,7019825.9249848155,,3.0,6643046.2389595695,,,,-46.2%,-38.5%
-1754,Nantes,,0.0,1.2,29211233.85355808,0.0,,,-41.9%,-38.6%,,0.0,1.1,12690457.224587822,0.0,,,-48.6%,-46.3%,23458883.695358895,0.07870443020291325,0.6,15157783.225556767,0.07870443020291325,,,-24.4%,13.7%,,,0.6,18276678.311546143,,,,-23.1%,6.9%,,,-0.2,9528575.946633369,,,,-30.2%,53.9%,,,0.0,6837186.288617744,,,,-34.6%,31.5%,13366967.626790376,,0.6,10126190.416033769,,,,-6.7%,42.0%,,,-0.1,4775697.198712083,,,,-31.5%,56.8%,,,-0.2,4764287.9733167,,,,-30.2%,53.9%
-1754,Bayonne,17289380.204127267,0.031669542926825174,0.1,17868698.8526713,0.031669542926825174,,,22.6%,40.3%,7119275.740170822,0.02872207051299327,0.3,6336807.076808006,0.02872207051299327,,,13.4%,23.8%,10170104.463956444,0.034120646461031474,-0.4,12079928.863853632,0.034120646461031474,,,29.2%,49.7%,14359334.10815467,,0.3,15477751.708460625,,,,31.5%,49.0%,11083195.916644104,,0.5,10221778.162544854,,,,29.0%,37.4%,5607412.158552832,,0.4,5260956.553784425,,,,28.9%,36.9%,8751921.949601838,,0.2,10279454.065760953,,,,31.3%,52.7%,5541597.958322052,,0.5,5110163.294220437,,,,30.1%,37.3%,5541597.958322052,,0.5,5110889.081272426,,,,29.0%,37.4%
-1754,La Rochelle,20361898.042909946,0.03729757784999354,-0.7,15332485.280570125,0.03729757784999354,,,47.4%,42.5%,10592659.154740712,0.04273512001310211,-0.5,6632415.826121904,0.04273512001310211,,,149.9%,144.1%,9769238.888169235,0.03277574458334592,-0.8,8561588.804606143,0.03277574458334592,,,-0.4%,-1.6%,17077246.642831936,,-1.3,12133681.780905012,,,,44.1%,34.1%,4919767.484134648,,1.8,3553891.09419421,,,,8.1%,-17.7%,8679417.712880714,,-1.0,4511349.369058378,,,,99.7%,86.6%,8397828.929951223,,-1.4,7365519.474447964,,,,7.4%,2.2%,2459883.742067324,,1.8,1757843.4972208354,,,,9.3%,-17.2%,2459883.742067324,,1.8,1776945.547097108,,,,8.1%,-17.7%
-1759,Marseille,71379103.67011715,0.22306151204096866,1.1,122498839.65183604,0.22306151204096866,171965055.33507904,133668077.30714491,-39.5%,-30.6%,38241410.691821605,0.29136142641986695,1.8,63795728.11284683,0.29136142641986695,89688878.3328242,68360945.72524603,-40.0%,-29.8%,33137692.97829555,0.17556706907647257,0.4,56297571.84274555,0.17556706907647257,77382271.19886729,61532109.271137156,-41.6%,-33.6%,66455656.26762006,,0.9,104598051.2768286,,147953742.02875647,110316131.54013811,-38.2%,-27.0%,68534364.5690725,,1.5,105878518.29620236,,165206508.86452913,110377642.20014322,-35.9%,-21.0%,34296920.28453625,,1.6,54938511.43349554,,77346747.86838622,55220238.798502125,-38.0%,-24.8%,32158735.983083803,,0.1,47781947.46515621,,64985119.71096804,50464362.066855825,-40.0%,-29.9%,34267182.28453625,,1.5,52683320.215793915,,75767057.18542577,50382895.84354095,-35.4%,-19.2%,34267182.28453625,,1.5,52939259.148101084,,82603254.4322644,55188821.100071505,-35.9%,-21.0%
-1759,Rouen,,0.0,2.5,50371576.085626796,0.0,41036382.24448445,41036382.24448445,30.0%,25.3%,,0.0,3.3,28137184.92698167,0.0,18512707.924201306,18512707.924201306,53.9%,47.8%,,0.0,1.3,22044565.925316937,0.0,23295209.067592308,23295209.067592308,6.6%,3.6%,,,2.0,36233810.410179235,,23174808.560736734,23174808.560736734,97.5%,93.3%,,,3.1,32080145.5300281,,15302303.113639269,15302303.113639269,157.2%,145.3%,,,3.0,20553034.52399212,,10573921.342845844,10573921.342845844,126.8%,119.7%,,,0.1,15500906.978001308,,13026503.280225465,13026503.280225465,71.2%,70.8%,,,3.1,16040072.765014019,,7651151.55681962,7651151.55681962,157.2%,145.3%,,,3.1,16040072.765014019,,7651151.55681962,7651151.55681962,157.2%,145.3%
-1759,Bordeaux,31879684.77956994,0.09962482469918432,3.7,68414174.33474919,0.09962482469918432,124844978.78689165,146810430.65228266,-49.2%,-57.2%,8256959.730143646,0.06290980173962447,4.2,25420519.98723197,0.06290980173962447,37673046.826430656,31882137.656952836,-38.5%,-53.8%,23622725.049426295,0.1251557434382527,3.2,41867383.0868484,0.1251557434382527,85738244.4598055,120456542.04859142,-56.9%,-60.6%,30487823.266116474,,2.2,37784914.290044285,,65657538.37955273,73864848.92085092,-53.2%,-55.5%,13787801.04483759,,3.0,15416703.981519584,,22146011.28597632,12572633.032211687,-46.2%,-38.5%,7178133.522430795,,2.9,11640014.393244015,,14596110.5886835,8943412.150526652,-47.7%,-40.4%,23309689.743685678,,1.9,25729589.674285486,,49332177.65409501,71082057.7450794,-53.5%,-55.1%,6893900.522418795,,3.0,7917821.059699035,,11153512.069862496,6286316.516105832,-47.0%,-41.8%,6893900.522418795,,3.0,7708351.990759887,,11073005.642988138,6286316.516105832,-46.2%,-38.5%
-1759,Nantes,7052664.139287565,0.022039754577153813,1.2,30986595.428110115,0.022039754577153813,28885175.819388814,24802733.87982664,-41.9%,-38.6%,3829024.131588031,0.029173346709570322,1.1,13391179.31401399,0.029173346709570322,15516738.518660355,12303360.590956768,-48.6%,-46.3%,3223640.0076995343,0.017079192214139928,0.6,15623510.282407405,0.017079192214139928,17182654.03171949,19214843.33877062,-24.4%,13.7%,5643029.476544005,,0.6,18789967.382451385,,13697810.59367485,9451731.322183235,-23.1%,6.9%,5081892.675573802,,-0.2,9434285.959577907,,7895758.471382072,2251350.822947998,-30.2%,53.9%,2573879.8584496207,,0.0,6844965.804055813,,6060931.94769462,2307984.7934112814,-34.6%,31.5%,3069149.618094384,,0.6,10441387.912673922,,9336466.923641266,12944138.970836725,-6.7%,42.0%,2540946.337786901,,-0.1,4740446.476238721,,3947879.235691085,1125675.411473997,-31.5%,56.8%,2540946.337786901,,-0.2,4717142.979788962,,3947879.235691085,1125675.411473997,-30.2%,53.9%
-1759,Bayonne,28213363.30341639,0.08816747695944988,0.1,17955773.46163679,0.08816747695944988,17757566.962901812,17757566.962901812,22.6%,40.3%,5841264.294555447,0.04450461073919246,0.3,6423725.395841644,0.04450461073919246,6722046.40107941,6722046.40107941,13.4%,23.8%,22372099.008860942,0.11852979187920525,-0.4,11839522.537841922,0.11852979187920525,11097506.06113552,11097506.06113552,29.2%,49.7%,26752035.17090975,,0.3,15733402.320552142,,14831911.148371704,14831911.148371704,31.5%,49.0%,9834193.792521296,,0.5,10484626.243746152,,9070862.243390016,9070862.243390016,29.0%,37.4%,4933805.896260648,,0.4,5365301.174144319,,4859755.201057619,4859755.201057619,28.9%,36.9%,21818229.274649102,,0.2,10357722.655765094,,10191208.254351972,10191208.254351972,31.3%,52.7%,4917096.896260648,,0.5,5230856.932173153,,4535431.121695,4535431.121695,30.1%,37.3%,4917096.896260648,,0.5,5242313.121873067,,4535431.121695,4535431.121695,29.0%,37.4%
-1759,La Rochelle,5914391.078003212,0.018482622347824808,-0.7,14780141.357363967,0.018482622347824808,20908985.8012106,15236923.909221709,47.4%,42.5%,2537916.1779194237,0.019336391214532282,-0.5,6458785.979995767,0.019336391214532282,10586665.453861943,8124475.779072234,149.9%,144.1%,3376474.900083788,0.017888927946983383,-0.8,8215030.737021578,0.017888927946983383,10312149.137610322,7198703.730696986,-0.4%,-1.6%,5694046.725195842,,-1.3,11385871.482536672,,16034645.915478433,13662381.889050739,44.1%,34.1%,2261504.9502693475,,1.8,3897024.2660638737,,4742571.133952919,7802572.608410868,8.1%,-17.7%,2362073.0751120537,,-1.0,4299370.272398356,,7640654.697758683,7413371.857920398,99.7%,86.6%,3331973.650083788,,-1.4,6881366.269553439,,8387701.596069861,6362407.208827104,7.4%,2.2%,1130752.4751346738,,1.8,1925787.4633946666,,2371285.566976464,3901286.304205427,9.3%,-17.2%,1130752.4751346738,,1.8,1948512.133031954,,2371285.566976464,3901286.304205427,8.1%,-17.7%
-1747,Marseille,74418213.11469391,0.2349028236830506,1.1,106943729.65168639,0.2349028236830506,157918215.64789405,157918215.64789405,-39.5%,-30.6%,35600040.11585111,0.2652305599040694,1.8,51404813.941700846,0.2652305599040694,83515657.30117384,83515657.30117384,-40.0%,-29.8%,38818172.998842806,0.21260765671829318,0.4,53521257.71075132,0.21260765671829318,69240024.84175745,69240024.84175745,-41.6%,-33.6%,69839685.9997605,,0.9,93957072.05622636,,143568815.19998568,143568815.19998568,-38.2%,-27.0%,68075928.23187415,,1.5,88738341.3466393,,135728515.724472,135728515.724472,-35.9%,-21.0%,34037964.11593708,,1.6,45346161.64547945,,72979970.39535964,72979970.39535964,-38.0%,-24.8%,35801721.88382342,,0.1,47142635.216096245,,64320138.92377951,64320138.92377951,-40.0%,-29.9%,34037964.11593708,,1.5,43799396.29822887,,61266851.09179798,61266851.09179798,-35.4%,-19.2%,34037964.11593708,,1.5,44369170.67331973,,67864257.86223587,67864257.86223587,-35.9%,-21.0%
-1747,Rouen,,0.0,2.5,37130553.80530753,0.0,,,30.0%,25.3%,,0.0,3.3,18885698.05670441,0.0,,,53.9%,47.8%,,0.0,1.3,18947191.05311458,0.0,,,6.6%,3.6%,,,2.0,28535621.121689726,,,,97.5%,93.3%,,,3.1,22074129.534360103,,,,157.2%,145.3%,,,3.0,14289122.655891182,,,,126.8%,119.7%,,,0.1,15299984.420926163,,,,71.2%,70.8%,,,3.1,11037064.76718011,,,,157.2%,145.3%,,,3.1,11037064.76718011,,,,157.2%,145.3%
-1747,Bordeaux,41561901.25071488,0.13119110971372314,3.7,43851500.67550866,0.13119110971372314,136777273.831927,136777273.831927,-49.2%,-57.2%,20593033.58523307,0.15342403576401398,4.2,15438019.945747757,0.15342403576401398,36109939.61307012,36109939.61307012,-38.5%,-53.8%,20968867.665481817,0.11484677082888409,3.2,28623332.808687188,0.11484677082888409,108366457.06960236,108366457.06960236,-56.9%,-60.6%,17008904.476898536,,2.2,28888330.471893486,,94939465.31813589,94939465.31813589,-53.2%,-55.5%,8616353.575038956,,3.0,10788605.268901268,,55848997.020615384,55848997.020615384,-46.2%,-38.5%,7251971.785057778,,2.9,8195037.089626348,,19856833.858060952,19856833.858060952,-47.7%,-40.4%,9756932.691840757,,1.9,20510553.00232486,,78216630.69632474,78216630.69632474,-53.5%,-55.1%,4308176.787519478,,3.0,5494463.413697069,,26590273.181962773,26590273.181962773,-47.0%,-41.8%,4308176.787519478,,3.0,5394302.634450663,,27924498.51030764,27924498.51030764,-46.2%,-38.5%
-1747,Nantes,,0.0,1.2,26895297.777685836,0.0,49129073.4282306,49129073.4282306,-41.9%,-38.6%,,0.0,1.1,11770613.27963306,0.0,45343789.02018678,45343789.02018678,-48.6%,-46.3%,,0.0,0.6,14528995.719865622,0.0,13551994.805240542,13551994.805240542,-24.4%,13.7%,,,0.6,17581543.770215776,,33741712.93515794,33741712.93515794,-23.1%,6.9%,,,-0.2,9662167.219108943,,155148135.74107653,155148135.74107653,-30.2%,53.9%,,,0.0,6826309.818741934,,43860489.33209423,43860489.33209423,-34.6%,31.5%,,,0.6,9700834.431364555,,8271739.065752125,8271739.065752125,-6.7%,42.0%,,,-0.1,4825489.024789835,,77574067.87053372,77574067.87053372,-31.5%,56.8%,,,-0.2,4831083.609554488,,77574067.87053372,77574067.87053372,-30.2%,53.9%
-1747,Bayonne,,0.0,0.1,17747503.336274996,0.0,,,22.6%,40.3%,,0.0,0.3,6217093.667282734,0.0,,,13.4%,23.8%,12752367.735913675,0.06984488997005078,-0.4,12424720.85757836,0.06984488997005078,,,29.2%,49.7%,,,0.3,15126804.487632912,,,,31.5%,49.0%,,,0.5,9864824.171130637,,,,29.0%,37.4%,,,0.4,5118274.441129128,,,,28.9%,36.9%,9514095.241400063,,0.2,10170870.656819722,,,,31.3%,52.7%,,,0.5,4945856.242272204,,,,30.1%,37.3%,,,0.5,4932412.085565317,,,,29.0%,37.4%
-1747,La Rochelle,47706829.27353594,0.1505877181980615,-0.7,16140616.271883965,0.1505877181980615,6554848.815469976,6554848.815469976,47.4%,42.5%,11180400.85292304,0.08329720889422143,-0.5,6883367.2501169825,0.08329720889422143,1015652.3014705472,1015652.3014705472,149.9%,144.1%,36526428.4206129,0.20005574077446867,-0.8,9071468.732076941,0.20005574077446867,8908489.55381297,8908489.55381297,-0.4%,-1.6%,38153804.2132972,,-1.3,13263845.478659647,,5231504.456952391,5231504.456952391,44.1%,34.1%,1930034.9251064789,,1.8,3123658.316150477,,919954.6553990665,919954.6553990665,8.1%,-17.7%,5061472.217591039,,-1.0,4825793.318671586,,689849.0760232756,689849.0760232756,99.7%,86.6%,33092331.995706163,,-1.4,8101092.163419812,,7134931.393649759,7134931.393649759,7.4%,2.2%,965017.4625532394,,1.8,1547037.3497924036,,459977.3276995324,459977.3276995324,9.3%,-17.2%,965017.4625532394,,1.8,1561829.1580752411,,459977.3276995324,459977.3276995324,8.1%,-17.7%
-1748,Marseille,,0.0,1.1,108160838.83336072,0.0,166379999.61753914,166379999.61753914,-39.5%,-30.6%,40122103.95795721,0.29481119863438454,1.8,52338279.50441622,0.29481119863438454,90349504.67389138,90349504.67389138,-40.0%,-29.8%,,0.0,0.4,53747292.27892585,0.0,70507480.88629614,70507480.88629614,-41.6%,-33.6%,,,0.9,94800868.884383,,153123497.42145857,153123497.42145857,-38.2%,-27.0%,,,1.5,90053933.20286769,,146422140.39803717,146422140.39803717,-35.9%,-21.0%,36626721.924818955,,1.6,46077109.60310916,,79216449.5684532,79216449.5684532,-38.0%,-24.8%,,,0.1,47195582.93725034,,66700527.03479432,66700527.03479432,-40.0%,-29.9%,36420566.623689994,,1.5,44478678.50866976,,65254319.91993697,65254319.91993697,-35.4%,-19.2%,,,1.5,45026966.60143376,,73211070.19901843,73211070.19901843,-35.9%,-21.0%
-1748,Rouen,,0.0,2.5,38086342.58578964,0.0,,,30.0%,25.3%,,0.0,3.3,19523694.74730237,0.0,,,53.9%,47.8%,,0.0,1.3,19187772.50721131,0.0,,,6.6%,3.6%,,,2.0,29109263.665746696,,,,97.5%,93.3%,,,3.1,22772619.093927357,,,,157.2%,145.3%,,,3.0,14728598.713397296,,,,126.8%,119.7%,,,0.1,15316628.026665144,,,,71.2%,70.8%,,,3.1,11386309.546963658,,,,157.2%,145.3%,,,3.1,11386309.546963658,,,,157.2%,145.3%
-1748,Bordeaux,32208934.610555325,0.10193106356926113,3.7,45507320.29357612,0.10193106356926113,166480179.7911622,166480179.7911622,-49.2%,-57.2%,12264367.507695038,0.09011673189484111,4.2,16093147.818956075,0.09011673189484111,40905167.30418812,40905167.30418812,-38.5%,-53.8%,19944567.102860287,0.11086893588643132,3.2,29544943.80091244,0.11086893588643132,138603523.43777716,138603523.43777716,-56.9%,-60.6%,19988647.22155146,,2.2,29541924.01585181,,117311500.25667997,117311500.25667997,-53.2%,-55.5%,15102973.890862776,,3.0,11114352.228134388,,75083990.44091326,75083990.44091326,-46.2%,-38.5%,8336408.944307788,,2.9,8438225.742853617,,22722825.43646227,22722825.43646227,-47.7%,-40.4%,11652238.277243672,,1.9,20901718.483203776,,100014789.58946195,100014789.58946195,-53.5%,-55.1%,7551486.945431388,,3.0,5664331.371350552,,35169584.62379305,35169584.62379305,-47.0%,-41.8%,7551486.945431388,,3.0,5557176.114067262,,37541995.220452294,37541995.220452294,-46.2%,-38.5%
-1748,Nantes,,0.0,1.2,27214549.472013187,0.0,49302112.42904861,49302112.42904861,-41.9%,-38.6%,,0.0,1.1,11897820.225026764,0.0,50187204.114292435,50187204.114292435,-48.6%,-46.3%,,0.0,0.6,14617199.721631464,0.0,12476886.259844212,12476886.259844212,-24.4%,13.7%,,,0.6,17679206.064259272,,34279025.8367247,34279025.8367247,-23.1%,6.9%,,,-0.2,9642968.688574005,,221555863.31853095,221555863.31853095,-30.2%,53.9%,,,0.0,6827862.540198768,,53159235.62927847,53159235.62927847,-34.6%,31.5%,,,0.6,9760487.745919598,,7501255.208370965,7501255.208370965,-6.7%,42.0%,,,-0.1,4818344.248614619,,110777931.65925898,110777931.65925898,-31.5%,56.8%,,,-0.2,4821484.344287011,,110777931.65925898,110777931.65925898,-30.2%,53.9%
-1748,Bayonne,,0.0,0.1,17764766.52346276,0.0,,,22.6%,40.3%,,0.0,0.3,6234056.1111197295,0.0,,,13.4%,23.8%,15283047.050639473,0.08495622666904923,-0.4,12374868.786429578,0.08495622666904923,,,29.2%,49.7%,,,0.3,15176448.351887867,,,,31.5%,49.0%,,,0.5,9915044.078243649,,,,29.0%,37.4%,,,0.4,5138418.197304254,,,,28.9%,36.9%,11998852.330056598,,0.2,10186312.064754985,,,,31.3%,52.7%,,,0.5,4969001.200032175,,,,30.1%,37.3%,,,0.5,4957522.039121815,,,,29.0%,37.4%
-1748,La Rochelle,23030805.99066665,0.07288519716254867,-0.7,16022612.106987804,0.07288519716254867,5605692.8009478105,5605692.8009478105,47.4%,42.5%,8188965.940917931,0.06017129279032662,-0.5,6846943.916922576,0.06017129279032662,734949.1250001653,734949.1250001653,149.9%,144.1%,14841840.04974872,0.08250362138350326,-0.8,8996810.506989026,0.08250362138350326,8785777.044530276,8785777.044530276,-0.4%,-1.6%,17366464.300394785,,-1.3,13096166.535714643,,4432533.922023923,4432533.922023923,44.1%,34.1%,2395405.608495061,,1.8,3181773.9449650906,,710791.7701116788,710791.7701116788,8.1%,-17.7%,4638988.30455933,,-1.0,4779565.255604671,,488243.6632729781,488243.6632729781,99.7%,86.6%,12727475.995835455,,-1.4,7991675.321695464,,6909290.400946994,6909290.400946994,7.4%,2.2%,1197702.8042475304,,1.8,1575529.0985407073,,355395.88505583873,355395.88505583873,9.3%,-17.2%,1197702.8042475304,,1.8,1590886.972482548,,355395.88505583873,355395.88505583873,8.1%,-17.7%
-1740,Marseille,109641515.25605261,0.28523013361346705,1.1,98798939.01304728,0.28523013361346705,,,-39.5%,-30.6%,49485692.83599193,0.2818418790151906,1.8,45320452.513854876,0.2818418790151906,,,-40.0%,-29.8%,60155822.42006069,0.28807907961719126,0.4,51965409.54808185,0.28807907961719126,,,-41.6%,-33.6%,92192853.92166692,,0.9,88257083.50985904,,,,-38.2%,-27.0%,83528473.58130832,,1.5,80051901.7628709,,,,-35.9%,-21.0%,42770046.7452086,,1.6,40544099.34903338,,,,-38.0%,-24.8%,49422807.176458314,,0.1,46773660.66720775,,,,-40.0%,-29.9%,41764236.79065416,,1.5,39326189.44957211,,,,-35.4%,-19.2%,41764236.79065416,,1.5,40025950.88143537,,,,-35.9%,-21.0%
-1740,Rouen,,0.0,2.5,31078963.58284068,0.0,,,30.0%,25.3%,,0.0,3.3,14966845.430650495,0.0,,,53.9%,47.8%,,0.0,1.3,17345497.041538548,0.0,,,6.6%,3.6%,,,2.0,24824476.65349712,,,,97.5%,93.3%,,,3.1,17749160.636562288,,,,157.2%,145.3%,,,3.0,11558846.722448621,,,,126.8%,119.7%,,,0.1,15183984.477056904,,,,71.2%,70.8%,,,3.1,8874580.31828119,,,,157.2%,145.3%,,,3.1,8874580.31828119,,,,157.2%,145.3%
-1740,Bordeaux,34215493.87234497,0.0890108994395804,3.7,33830377.422714256,0.0890108994395804,,,-49.2%,-57.2%,15215823.9939525,0.08666053114448698,4.2,11541062.126220552,0.08666053114448698,,,-38.5%,-53.8%,18999669.878392473,0.09098715953673855,3.2,22928699.587623805,0.09098715953673855,,,-56.9%,-60.6%,21168690.995450623,,2.2,24700634.624042217,,,,-53.2%,-55.5%,6814368.990277499,,3.0,8760589.604626507,,,,-46.2%,-38.5%,7509973.244910998,,2.9,6678046.063462188,,,,-47.7%,-40.4%,13658717.750539627,,1.9,17969872.69855383,,,,-53.5%,-55.1%,3407184.4951387495,,3.0,4439782.766523802,,,,-47.0%,-41.8%,3407184.4951387495,,3.0,4380294.802313276,,,,-46.2%,-38.5%
-1740,Nantes,40152182.6768143,0.10445507254286013,1.2,24762974.620542567,0.10445507254286013,,,-41.9%,-38.6%,15781864.300198868,0.08988436927563219,1.1,10917442.494525572,0.08988436927563219,,,-48.6%,-46.3%,24370318.37661544,0.11670655649738211,0.6,13926292.08946349,0.11670655649738211,,,-24.4%,13.7%,22862459.878206708,,0.6,16912847.951628882,,,,-23.1%,6.9%,5650909.661024557,,-0.2,9797631.450165277,,,,-30.2%,53.9%,6368852.277259383,,0.0,6815450.650953862,,,,-34.6%,31.5%,16493607.600947326,,0.6,9293345.749823222,,,,-6.7%,42.0%,2825454.8305122787,,-0.1,4875799.984690576,,,,-31.5%,56.8%,2825454.8305122787,,-0.2,4898815.725082655,,,,-30.2%,53.9%
-1740,Bayonne,,0.0,0.1,17627129.835701764,0.0,,,22.6%,40.3%,,0.0,0.3,6099641.854212352,0.0,,,13.4%,23.8%,,0.0,-0.4,12779354.09459814,0.0,,,29.2%,49.7%,,,0.3,14783814.750174012,,,,31.5%,49.0%,,,0.5,9520335.344774825,,,,29.0%,37.4%,,,0.4,4979462.002185,,,,28.9%,36.9%,,,0.2,10063434.23064838,,,,31.3%,52.7%,,,0.5,4786832.1540504815,,,,30.1%,37.3%,,,0.5,4760167.672387413,,,,29.0%,37.4%
-1740,La Rochelle,19592794.140117444,0.05097024860880286,-0.7,16991341.51241254,0.05097024860880286,,,47.4%,42.5%,9775962.24040329,0.05567822554588645,-0.5,7143813.949869218,0.05567822554588645,,,149.9%,144.1%,9816831.899714151,0.04701164051384077,-0.8,9611714.231449287,0.04701164051384077,,,-0.4%,-1.6%,16689691.98688759,,-1.3,14499275.657502744,,,,44.1%,34.1%,5596733.62152273,,1.8,2745509.3635243587,,,,8.1%,-17.7%,7754903.31077304,,-1.0,5162154.213606426,,,,99.7%,86.6%,8934788.67611455,,-1.4,8910124.325635679,,,,7.4%,2.2%,2798366.810761365,,1.8,1361511.7417657361,,,,9.3%,-17.2%,2798366.810761365,,1.8,1372754.6817621817,,,,8.1%,-17.7%
 1769,Marseille,151407884.4146128,0.26674802847375434,1.1,137176330.8784242,0.26674802847375434,,,-39.5%,-30.6%,82762431.8833999,0.28502429017967573,1.8,76374451.49372308,0.28502429017967573,,,-40.0%,-29.8%,68645452.5312129,0.24760599292228064,0.4,58720866.86766447,0.24760599292228064,,,-41.6%,-33.6%,124658608.35367642,,0.9,114380509.25759862,,,,-38.2%,-27.0%,129099151.37968625,,1.5,122665277.34764436,,,,-35.9%,-21.0%,68691452.99475726,,1.6,64464979.87762227,,,,-38.0%,-24.8%,55967155.35891916,,0.1,48321325.51410319,,,,-40.0%,-29.9%,64549575.689843126,,1.5,61448409.73834836,,,,-35.4%,-19.2%,64549575.689843126,,1.5,61332638.67382206,,,,-35.9%,-21.0%
 1769,Rouen,80927211.65017723,0.14257628815715478,2.5,64947728.60993005,0.14257628815715478,,,30.0%,25.3%,56522477.47787039,0.19465690719460407,3.3,39225664.916257866,0.19465690719460407,,,53.9%,47.8%,24404734.17230684,0.08802853231961319,1.3,25009143.361147434,0.08802853231961319,,,6.6%,3.6%,59443779.360499546,,2.0,44213297.4004397,,,,97.5%,93.3%,78152964.65368217,,3.1,43805665.47418813,,,,157.2%,145.3%,44485037.933381,,3.0,27824963.80410613,,,,126.8%,119.7%,14958741.427118551,,0.1,15670356.541364916,,,,71.2%,70.8%,39076482.326841086,,3.1,21902832.737094022,,,,157.2%,145.3%,39076482.326841086,,3.1,21902832.737094022,,,,157.2%,145.3%
 1769,Bordeaux,115393224.72488971,0.20329796769568007,3.7,99109232.90329209,0.20329796769568007,,,-49.2%,-57.2%,59462168.851319335,0.20478086595218453,4.2,38519306.26779931,0.20478086595218453,,,-38.5%,-53.8%,55931055.873570375,0.20174482233138327,3.2,57478509.305542104,0.20174482233138327,,,-56.9%,-60.6%,48318279.142484,,2.2,47258700.22845194,,,,-53.2%,-55.5%,16861498.370763928,,3.0,20757739.551886424,,,,-46.2%,-38.5%,17319323.935682368,,2.9,15593933.537251024,,,,-47.7%,-40.4%,30998955.206801634,,1.9,31079863.467707433,,,,-53.5%,-55.1%,8430749.185381964,,3.0,10735921.975549472,,,,-47.0%,-41.8%,8430749.185381964,,3.0,10378869.77594334,,,,-46.2%,-38.5%
 1769,Nantes,52252637.261229716,0.09205787417132709,1.2,34867578.1181696,0.09205787417132709,,,-41.9%,-38.6%,25702283.24397733,0.08851570538589963,1.1,14910834.068407848,0.08851570538589963,,,-48.6%,-46.3%,26550354.017252386,0.09576784078873467,0.6,16598332.83783723,0.09576784078873467,,,-24.4%,13.7%,29386168.490916498,,0.6,19860196.578669928,,,,-23.1%,6.9%,18781909.682765197,,-0.2,9248495.891137123,,,,-30.2%,53.9%,11900824.27066165,,0.0,6860551.400164483,,,,-34.6%,31.5%,17485344.220254846,,0.6,11101521.713911632,,,,-6.7%,42.0%,9390954.841382599,,-0.1,4670723.696287202,,,,-31.5%,56.8%,9390954.841382599,,-0.2,4624247.945568569,,,,-30.2%,53.9%
 1769,Bayonne,16898319.79707307,0.029771193936273067,0.1,18131197.69740632,0.029771193936273067,,,22.6%,40.3%,7607360.136374629,0.026198872769545137,0.3,6601155.011731832,0.026198872769545137,,,13.4%,23.8%,9290959.660698442,0.03351274129837026,-0.4,11372967.867539646,0.03351274129837026,,,29.2%,49.7%,15509793.641637886,,0.3,16257441.26239151,,,,31.5%,49.0%,13346173.770038698,,0.5,11030773.244661616,,,,29.0%,37.4%,6698594.885198349,,0.4,5580240.104480892,,,,28.9%,36.9%,8811198.756439537,,0.2,10516052.20335153,,,,31.3%,52.7%,6673086.885019349,,0.5,5480863.2888497645,,,,30.1%,37.3%,6673086.885019349,,0.5,5515386.622330798,,,,29.0%,37.4%
 1769,La Rochelle,10713790.469201192,0.018875387475293826,-0.7,13734430.313733384,0.018875387475293826,,,47.4%,42.5%,4993416.530806231,0.017196751833847126,-0.5,6125043.646535439,0.017196751833847126,,,149.9%,144.1%,5720373.938394961,0.0206335425971442,-0.8,7563430.955049716,0.0206335425971442,,,-0.4%,-1.6%,7920831.90714321,,-1.3,10025675.193409834,,,,44.1%,34.1%,4596418.751598899,,1.8,4685879.324407475,,,,8.1%,-17.7%,3374441.1247435994,,-1.0,3904825.452115396,,,,99.7%,86.6%,4546390.782399611,,-1.4,6006441.599240408,,,,7.4%,2.2%,2298209.3757994496,,1.8,2311344.347222431,,,,9.3%,-17.2%,2298209.3757994496,,1.8,2342939.6622037413,,,,8.1%,-17.7%
-1764,Marseille,170896325.58873504,0.30554280417795493,1.1,129630017.20397691,0.30554280417795493,,,-39.5%,-30.6%,85098107.90470757,0.36534786537439623,1.8,69802319.03211632,0.36534786537439623,,,-40.0%,-29.8%,85798217.6840275,0.26286468712892475,0.4,57496453.98762116,0.26286468712892475,,,-41.6%,-33.6%,142139358.7521294,,0.9,109379972.44649549,,,,-38.2%,-27.0%,131199525.23608553,,1.5,113963230.08743326,,,,-35.9%,-21.0%,70510017.87171552,,1.6,59511427.760278195,,,,-38.0%,-24.8%,71629340.88041389,,0.1,48050879.67104851,,,,-40.0%,-29.9%,65599762.61804277,,1.5,56897330.75458553,,,,-35.4%,-19.2%,65599762.61804277,,1.5,56981615.04371673,,,,-35.9%,-21.0%
-1764,Rouen,50161964.588806435,0.08968377330957358,2.5,57197197.94940773,0.08968377330957358,,,30.0%,25.3%,26470996.890193116,0.11364673605897337,3.3,33221977.479261473,0.11364673605897337,,,53.9%,47.8%,23690967.698613316,0.07258331210109495,1.3,23480113.06532652,0.07258331210109495,,,6.6%,3.6%,34558337.86020608,,2.0,40025195.0103482,,,,97.5%,93.3%,28335153.801840406,,3.1,37487226.13706798,,,,157.2%,145.3%,18982903.0009202,,3.0,23914168.22083972,,,,126.8%,119.7%,15575434.859285884,,0.1,15585401.47252588,,,,71.2%,70.8%,14167576.900920203,,3.1,18743613.068533953,,,,157.2%,145.3%,14167576.900920203,,3.1,18743613.068533953,,,,157.2%,145.3%
-1764,Bordeaux,,0.0,3.7,82343647.83047377,0.0,,,-49.2%,-57.2%,,0.0,4.2,31291864.675581228,0.0,,,-38.5%,-53.8%,68010327.70630482,0.20836695675767633,3.2,49055833.17360021,0.20836695675767633,,,-56.9%,-60.6%,,,2.2,42257140.66984378,,,,-53.2%,-55.5%,,,3.0,17888988.95960624,,,,-46.2%,-38.5%,,,2.9,13472698.720779458,,,,-47.7%,-40.4%,33894679.10345651,,1.9,28278474.749479115,,,,-53.5%,-55.1%,,,3.0,9219821.533700708,,,,-47.0%,-41.8%,,,3.0,8944494.47980323,,,,-46.2%,-38.5%
-1764,Nantes,42213765.42899639,0.07547331529599705,1.2,32869857.570511963,0.07547331529599705,,,-41.9%,-38.6%,18930458.92857633,0.08127328480508371,1.1,14130592.794768315,0.08127328480508371,,,-48.6%,-46.3%,23283306.50042006,0.07133433821550313,0.6,16103546.931119539,0.07133433821550313,,,-24.4%,13.7%,21095358.110057916,,0.6,19317671.85564252,,,,-23.1%,6.9%,6621347.041361558,,-0.2,9340929.018730896,,,,-30.2%,53.9%,7202041.48135166,,0.0,6852754.171214163,,,,-34.6%,31.5%,13893316.628706258,,0.6,10766396.54833146,,,,-6.7%,42.0%,3310673.520680779,,-0.1,4705455.948954298,,,,-31.5%,56.8%,3310673.520680779,,-0.2,4670464.509365455,,,,-30.2%,53.9%
-1764,Bayonne,20355339.127839807,0.036392984902908806,0.1,18043272.387313187,0.036392984902908806,,,22.6%,40.3%,7915937.524806063,0.03398513725315142,0.3,6511835.92320546,0.03398513725315142,,,13.4%,23.8%,12439401.603033744,0.038111274321508924,-0.4,11603900.610996615,0.038111274321508924,,,29.2%,49.7%,17378046.251813967,,0.3,15993275.589570442,,,,31.5%,49.0%,13107959.202115284,,0.5,10754233.336216584,,,,29.0%,37.4%,6643853.751051952,,0.4,5471715.342063995,,,,28.9%,36.9%,10734192.500762014,,0.2,10436587.189108448,,,,31.3%,52.7%,6553979.601057642,,0.5,5354401.155010062,,,,30.1%,37.3%,6553979.601057642,,0.5,5377116.668108282,,,,29.0%,37.4%
-1764,La Rochelle,,0.0,-0.7,14247695.304850005,0.0,,,47.4%,42.5%,8847346.48137101,0.03798391328296222,-0.5,6289701.585218914,0.03798391328296222,,,149.9%,144.1%,,0.0,-0.8,7882500.730927576,0.0,,,-0.4%,-1.6%,,,-1.3,10684149.441009328,,,,44.1%,34.1%,,,1.8,4273287.4271529,,,,8.1%,-17.7%,4220042.2111123195,,-1.0,4097351.640722254,,,,99.7%,86.6%,,,-1.4,6429037.612353454,,,,7.4%,2.2%,1375003.63684811,,1.8,2109776.7577326884,,,,9.3%,-17.2%,,,1.8,2136643.7135764537,,,,8.1%,-17.7%
-1762,Marseille,91016133.9788189,0.26937428234471167,1.1,126729037.71574524,0.26937428234471167,182853827.62657115,128086211.235678,-39.5%,-30.6%,58356347.295732476,0.41624421375959253,1.8,67334641.18980262,0.41624421375959253,97430777.83477102,65765591.299879216,-40.0%,-29.8%,32659786.68308642,0.16521339150133738,0.4,57013867.504530095,0.16521339150133738,79956861.620314,57788367.86121784,-41.6%,-33.6%,83512926.84020147,,0.9,107441514.90168874,,157643389.61980617,104145575.32830685,-38.2%,-27.0%,104288919.31019527,,1.5,110657789.89028654,,182732380.68259,103320641.67319992,-35.9%,-21.0%,52798052.655100636,,1.6,57638275.2993673,,84009614.70777196,51568667.47874629,-38.0%,-24.8%,30714874.18510083,,0.1,47943125.62770454,,67180047.26231286,46982823.27483692,-40.0%,-29.9%,52144459.65509763,,1.5,55172719.42040281,,82864059.0109073,45845965.78151364,-35.4%,-19.2%,52144459.65509763,,1.5,55328894.94514316,,91366190.34129548,51660320.8365995,-35.9%,-21.0%
-1762,Rouen,,0.0,2.5,54362455.85886483,0.0,36467300.542462386,36467300.542462386,30.0%,25.3%,,0.0,3.3,31086193.475793235,0.0,15071634.416163156,15071634.416163156,53.9%,47.8%,,0.0,1.3,22895004.381712183,0.0,23011947.066501983,23011947.066501983,6.6%,3.6%,,,2.0,38463223.36600816,,18295718.552034076,18295718.552034076,97.5%,93.3%,,,3.1,35222851.804082,,10397579.847890459,10397579.847890459,157.2%,145.3%,,,3.0,22508344.243006617,,7661150.24855807,7661150.24855807,126.8%,119.7%,,,0.1,15551548.545931702,,11426949.070002558,11426949.070002558,71.2%,70.8%,,,3.1,17611425.902040966,,5198789.923945219,5198789.923945219,157.2%,145.3%,,,3.1,17611425.902040966,,5198789.923945219,5198789.923945219,157.2%,145.3%
-1762,Bordeaux,33747414.055872545,0.0998799338632211,3.7,76460387.98090042,0.0998799338632211,148463315.31931362,188668762.62064198,-49.2%,-57.2%,8980650.366498953,0.06405719213214907,4.2,28796031.373054177,0.06405719213214907,42635694.96261548,33539390.616728876,-38.5%,-53.8%,24766763.68937359,0.1252856016892668,3.2,46043117.39027221,0.1252856016892668,104681109.04113433,172501081.12841737,-56.9%,-60.6%,28325568.2249012,,2.2,40408007.94237175,,75435996.32097644,89957894.60779068,-53.2%,-55.5%,6058120.5331324935,,3.0,16855750.377483282,,24644373.649146445,10904777.835518971,-46.2%,-38.5%,5192312.342161528,,2.9,12707325.828232257,,15628073.886994217,7695786.162349344,-47.7%,-40.4%,23133255.88273967,,1.9,27229943.041507974,,57954808.63822073,99111763.79442379,-53.5%,-55.1%,3029060.2665662467,,3.0,8675125.80954947,,12451227.102048958,5452388.9177595535,-47.0%,-41.8%,3029060.2665662467,,3.0,8427875.188741745,,12322186.824573288,5452388.9177595535,-46.2%,-38.5%
-1762,Nantes,5938902.339939631,0.017576966695914225,1.2,32103193.619829528,0.017576966695914225,26427862.808711413,21302893.94157235,-41.9%,-38.6%,1557436.64375888,0.01110888568773051,1.1,13830050.280296886,0.01110888568773051,14209518.436152332,10293181.047618628,-48.6%,-46.3%,4381465.696180751,0.022164162137276466,0.6,15909787.280190114,0.022164162137276466,16561325.221866306,19440275.73272309,-24.4%,13.7%,5173412.64467358,,0.6,19104834.55915443,,11873550.92404873,7015456.287049794,-23.1%,6.9%,1863709.5964669008,,-0.2,9378160.42249017,,6589666.826356168,1128317.574236423,-30.2%,53.9%,931854.7982334504,,0.0,6849637.761500059,,5141343.087163501,1315306.339448622,-34.6%,31.5%,4241557.84644013,,0.6,10635196.422174022,,8727802.333007133,13999009.256193846,-6.7%,42.0%,931854.7982334504,,-0.1,4719421.059680653,,3294833.413178078,564158.7871182105,-31.5%,56.8%,931854.7982334504,,-0.2,4689080.2112450935,,3294833.413178078,564158.7871182105,-30.2%,53.9%
-1762,Bayonne,25897658.81175834,0.07664754535112511,0.1,18008221.766929317,0.07664754535112511,18069150.24073928,18069150.24073928,22.6%,40.3%,10309375.272833945,0.07353472250493583,0.3,6476447.605670589,0.07353472250493583,6578779.264683277,6578779.264683277,13.4%,23.8%,15588283.538924394,0.07885517490179726,-0.4,11697581.39050085,0.07885517490179726,11621221.42773093,11621221.42773093,29.2%,49.7%,23933280.85693584,,0.3,15888815.124934653,,15049809.959321465,15049809.959321465,31.5%,49.0%,16314871.413473248,,0.5,10645568.393269416,,8188742.370332776,8188742.370332776,29.0%,37.4%,9150501.706736624,,0.4,5428898.720249463,,4493860.640866947,4493860.640866947,28.9%,36.9%,14782779.150199216,,0.2,10404969.572937602,,11044922.765369542,11044922.765369542,31.3%,52.7%,8157435.706736624,,0.5,5304637.122038086,,4094371.1851664092,4094371.1851664092,30.1%,37.3%,8157435.706736624,,0.5,5322784.196634699,,4094371.1851664092,4094371.1851664092,29.0%,37.4%
-1762,La Rochelle,4152304.1112779393,0.012289293020430768,-0.7,14458332.445805445,0.012289293020430768,21266727.731675316,13584850.161848653,47.4%,42.5%,1657889.8236691197,0.01182539823227845,-0.5,6356797.575334087,0.01182539823227845,10943494.883428385,7517352.750245811,149.9%,144.1%,2494414.2876088195,0.012618289527245013,-0.8,8013866.232286618,0.012618289527245013,10339433.361838326,6218068.076234282,-0.4%,-1.6%,3351031.7523052897,,-1.3,10959493.497999148,,16090098.282202514,12822289.043861156,44.1%,34.1%,1413327.42926282,,1.8,4118608.4582261858,,4751821.429373782,9602639.92708887,8.1%,-17.7%,869285.51485133,,-1.0,4176994.2950196248,,7824138.05587363,7488609.390159684,99.7%,86.6%,2481746.23745396,,-1.4,6606287.192430803,,8282060.691237678,5601582.5324442,7.4%,2.2%,706663.71463141,,1.8,2034160.628655465,,2375910.714686891,4801319.9635444265,9.3%,-17.2%,706663.71463141,,1.8,2059304.2291130961,,2375910.714686891,4801319.9635444265,8.1%,-17.7%
-1771,Marseille,,0.0,1.1,140316461.42247352,0.0,,,-39.5%,-30.6%,97527353.57682055,0.28966096717579226,1.8,79173420.02373561,0.28966096717579226,,,-40.0%,-29.8%,,0.0,0.4,59217902.02535612,0.0,,,-41.6%,-33.6%,,,0.9,116444159.99215975,,,,-38.2%,-27.0%,,,1.5,126329391.17949577,,,,-35.9%,-21.0%,83992829.23529848,,1.6,66559989.40164362,,,,-38.0%,-24.8%,,,0.1,48429929.57643149,,,,-40.0%,-29.9%,80349822.38526821,,1.5,63369189.15642921,,,,-35.4%,-19.2%,,,1.5,63164695.589747764,,,,-35.9%,-21.0%
-1771,Rouen,73327506.14141776,0.10838863509631849,2.5,68334442.05153278,0.10838863509631849,,,30.0%,25.3%,47961553.222477585,0.14244813771895437,3.3,41920673.15902633,0.14244813771895437,,,53.9%,47.8%,25365952.91894017,0.07464326419413904,1.3,25648281.345416684,0.07464326419413904,,,6.6%,3.6%,51453789.00759831,,2.0,46008776.58285473,,,,97.5%,93.3%,62977417.3674629,,3.1,46621803.846255615,,,,157.2%,145.3%,35994140.73476239,,3.0,29562852.68992697,,,,126.8%,119.7%,15459648.272835914,,0.1,15704468.091615528,,,,71.2%,70.8%,31488708.68373145,,3.1,23310901.923127763,,,,157.2%,145.3%,31488708.68373145,,3.1,23310901.923127763,,,,157.2%,145.3%
-1771,Bordeaux,,0.0,3.7,106735212.65646468,0.0,,,-49.2%,-57.2%,93415459.66051455,0.2774484429450052,4.2,41857883.24488141,0.2774484429450052,,,-38.5%,-53.8%,,0.0,3.2,61239471.24734967,0.0,,,-56.9%,-60.6%,,,2.2,49421331.19444386,,,,-53.2%,-55.5%,,,3.0,22030165.69147376,,,,-46.2%,-38.5%,53203407.53370418,,2.9,16533169.2331736,,,,-47.7%,-40.4%,,,1.9,32276642.406085275,,,,-53.5%,-55.1%,31251537.82019224,,3.0,11410011.426617254,,,,-47.0%,-41.8%,,,3.0,11015082.845737016,,,,-46.2%,-38.5%
-1771,Nantes,46403343.88607542,0.06859083817765257,1.2,35700258.9880969,0.06859083817765257,,,-41.9%,-38.6%,24093575.25181427,0.07155908628922289,1.1,15234863.227591015,0.07155908628922289,,,-48.6%,-46.3%,22309768.634261154,0.06564996629926921,0.6,16800478.040663056,0.06564996629926921,,,-24.4%,13.7%,20780052.006272167,,0.6,20081448.981271904,,,,-23.1%,6.9%,11113484.961163802,,-0.2,9211779.257045092,,,,-30.2%,53.9%,8921777.875814755,,0.0,6863672.775304593,,,,-34.6%,31.5%,11858274.13045741,,0.6,11238474.619301133,,,,-6.7%,42.0%,5556742.480581901,,-0.1,4656902.684606733,,,,-31.5%,56.8%,5556742.480581901,,-0.2,4605889.628522554,,,,-30.2%,53.9%
-1771,Bayonne,15032020.643571433,0.022219495603111872,0.1,18166487.674163703,0.022219495603111872,,,22.6%,40.3%,5366804.854854901,0.015939670542546955,0.3,6637224.749939479,0.015939670542546955,,,13.4%,23.8%,9665215.78871653,0.028441401666083155,-0.4,11281886.774829965,0.028441401666083155,,,29.2%,49.7%,13682754.93062103,,0.3,16364325.246798461,,,,31.5%,49.0%,9367509.497662019,,0.5,11143370.17711401,,,,29.0%,37.4%,4686539.7488310095,,0.4,5624250.32506148,,,,28.9%,36.9%,8996215.18179002,,0.2,10548007.366686417,,,,31.3%,52.7%,4683754.7488310095,,0.5,5532280.540425385,,,,30.1%,37.3%,4683754.7488310095,,0.5,5571685.088556995,,,,29.0%,37.4%
-1771,La Rochelle,10840840.44986194,0.016024326497499734,-0.7,13534339.387288002,0.016024326497499734,,,47.4%,42.5%,5076204.03314896,0.015076572016951065,-0.5,6060393.818836411,0.015076572016951065,,,149.9%,144.1%,5764636.416712981,0.01696333981265783,-0.8,7439449.112752218,0.01696333981265783,,,-0.4%,-1.6%,7820871.77738863,,-1.3,9773792.195138093,,,,44.1%,34.1%,5398855.7463514,,1.8,4861862.78818313,,,,8.1%,-17.7%,3614279.8251026403,,-1.0,3830372.2348952508,,,,99.7%,86.6%,4206591.95228599,,-1.4,5845286.139265206,,,,7.4%,2.2%,2699427.8731757,,1.8,2397264.264282786,,,,9.3%,-17.2%,2699427.8731757,,1.8,2430931.3940915694,,,,8.1%,-17.7%
 1776,Marseille,168894978.15374836,0.24089376611317118,1.1,148484878.3865498,0.24089376611317118,171884529.249406,164065633.58895093,-39.5%,-30.6%,104908999.16201356,0.28282848644098935,1.8,86627874.41793717,0.28282848644098935,97303894.21451236,91778169.22289327,-40.0%,-29.8%,63985978.99173481,0.1937852657567295,0.4,60478973.91658266,0.1937852657567295,76505480.22183841,73744599.52568355,-41.6%,-33.6%,136550528.42887792,,0.9,121767651.07974079,,139611255.82994252,131263070.53147468,-38.2%,-27.0%,161132795.97578165,,1.5,135975698.42749372,,144304982.55404317,135328002.90408492,-35.9%,-21.0%,86733626.53943223,,1.6,72100242.57384157,,79633465.01356189,74258761.65062998,-38.0%,-24.8%,49816901.889445685,,0.1,48702508.834564574,,61832162.201634586,58600366.11717354,-40.0%,-29.9%,80566397.98789082,,1.5,68437936.33952397,,74235371.49146512,69582002.3928786,-35.4%,-19.2%,80566397.98789082,,1.5,67987849.21374673,,72152491.2770217,67664001.4520421,-35.9%,-21.0%
 1776,Rouen,87589893.64933136,0.1249288734649763,2.5,77594129.7159278,0.1249288734649763,67257937.14660557,72459875.08523373,30.0%,25.3%,58601908.63290791,0.15798729616705623,3.3,49496339.566975296,0.15798729616705623,42299653.23643551,46362708.95879322,53.9%,47.8%,28987985.01642344,0.08779180171464322,1.3,27318503.25209025,0.08779180171464322,24431245.063275445,25733508.25984057,6.6%,3.6%,66420096.28092575,,2.0,50822980.91395222,,41727370.67198683,44075940.0191868,97.5%,93.3%,77290482.76659203,,3.1,54479868.30566885,,43059776.53796007,49671676.087864086,157.2%,145.3%,44884108.043494776,,3.0,34397404.017861985,,28321066.1965215,31101742.154575206,126.8%,119.7%,21535988.237430975,,0.1,15790072.18530253,,13192277.489003709,13243322.348960845,71.2%,70.8%,38645241.38329601,,3.1,27239934.152834374,,21529888.26898007,24835838.043931995,157.2%,145.3%,38645241.38329601,,3.1,27239934.152834374,,21529888.26898007,24835838.043931995,157.2%,145.3%
 1776,Bordeaux,143614739.71571714,0.20483673284819995,3.7,128467044.25738464,0.20483673284819995,137290190.20831585,170753893.2295039,-49.2%,-57.2%,65286989.572110236,0.17600988087258942,4.2,51525744.50731176,0.17600988087258942,59499309.60526719,110572158.92426251,-38.5%,-53.8%,78327750.14360689,0.23722015536663488,3.2,71754025.77509442,0.23722015536663488,78547875.76985112,76057558.91995628,-56.9%,-60.6%,45203182.21892609,,2.2,55270845.08763326,,58074538.01909492,57045068.19117637,-53.2%,-55.5%,27439217.129309606,,3.0,25563012.126683198,,24984556.41824593,48647507.895752415,-46.2%,-38.5%,15691429.014617555,,2.9,19136265.68258319,,22819793.963122327,38090904.641864076,-47.7%,-40.4%,29511753.204308536,,1.9,35474107.00414895,,35397537.84594554,27776869.31525236,-53.5%,-55.1%,13719608.564654803,,3.0,13286265.028941635,,14063662.754493631,27999714.683516428,-47.0%,-41.8%,13719608.564654803,,3.0,12781506.063341757,,12492278.209122986,24323753.94787616,-46.2%,-38.5%
 1776,Nantes,52611798.7043335,0.07503985299277342,1.2,37870001.913944006,0.07503985299277342,50033043.62997978,52910399.47667127,-41.9%,-38.6%,29713395.145949706,0.08010556428218142,1.1,16076078.402429305,0.08010556428218142,19056835.668643415,21068510.51014754,-48.6%,-46.3%,22898403.558383793,0.06934914943693254,0.6,17316677.347324885,0.06934914943693254,18949393.872771945,9427257.294540966,-24.4%,13.7%,23620859.807183765,,0.6,20645423.90682033,,23622635.35695363,19635939.116551425,-23.1%,6.9%,15606340.777539318,,-0.2,9120624.130427098,,8563653.007229969,16980435.322099775,-30.2%,53.9%,11110055.769272508,,0.0,6871482.427705949,,7151975.702905836,8855848.233273167,-34.6%,31.5%,12510804.037911259,,0.6,11588294.13883625,,11707407.92127175,5227672.111265211,-6.7%,42.0%,7803170.388769659,,-0.1,4622528.8168152915,,4434363.412340161,7340931.097866799,-31.5%,56.8%,7803170.388769659,,-0.2,4560312.065213556,,4281826.503614977,8490217.661049873,-30.2%,53.9%
 1776,Bayonne,15775298.451347623,0.022500201587077603,0.1,18255013.415380035,0.022500201587077603,14977623.64145483,11696522.067581084,22.6%,40.3%,6762369.2478743885,0.018230949436260885,0.3,6728263.724508335,0.018230949436260885,5435761.887723756,4797121.9624152845,13.4%,23.8%,9012929.203473235,0.02729618126444947,-0.4,11057362.526336025,0.02729618126444947,9436441.01655539,7002392.010806918,29.2%,49.7%,14343279.24695497,,0.3,16634619.65677545,,13548702.923853178,10667119.127501545,31.5%,49.0%,11629745.573351162,,0.5,11429916.551198201,,9102978.039401073,8164251.493026018,29.0%,37.4%,5843292.286714618,,0.4,5735800.431772662,,4552299.0369084375,4151361.170300549,28.9%,36.9%,8499986.960240353,,0.2,10628320.743122786,,8932568.331462393,6581149.730415791,31.3%,52.7%,5814872.786675581,,0.5,5662943.8922901265,,4529866.205060116,4165155.495917024,30.1%,37.3%,5814872.786675581,,0.5,5714958.27559909,,4551489.019700512,4082125.7465130016,29.0%,37.4%
 1776,La Rochelle,25260613.44092749,0.03602904226420876,-0.7,13046772.630928442,0.03602904226420876,14685867.274708187,22660369.383152675,47.4%,42.5%,9773015.388894258,0.026347474215599097,-0.5,5901738.92236807,0.026347474215599097,6540837.586178241,9240839.001475051,149.9%,144.1%,15487598.052033234,0.04690509314289535,-0.8,7138313.287702777,0.04690509314289535,8164278.863577452,12160080.123654038,-0.4%,-1.6%,21133608.122192893,,-1.3,9171424.126681034,,10670959.540280404,19289263.948365953,44.1%,34.1%,12613929.255310198,,1.8,5331282.462418426,,6427533.5091131525,14931851.698538931,8.1%,-17.7%,7120486.377575998,,-1.0,3650390.8635136327,,4162400.2534220708,7498947.064944609,99.7%,86.6%,14013121.744616896,,-1.4,5461061.506139394,,6366245.668276176,11016230.94588731,7.4%,2.2%,6306964.627655099,,1.8,2626298.344476481,,3070948.176733146,7120168.549845887,9.3%,-17.2%,6306964.627655099,,1.8,2665641.2312092176,,3213766.7545565874,7465925.849269452,8.1%,-17.7%
-1761,Marseille,79304676.76851721,0.2536895863167885,1.1,125302984.83882347,0.2536895863167885,179149708.18378964,129920441.19723321,-39.5%,-30.6%,47979838.72922086,0.3581372667613391,1.8,66133711.978456005,0.3581372667613391,94778604.66693728,66619572.30772985,-40.0%,-29.8%,31324838.039296355,0.17535701551428262,0.4,56774095.334157705,0.17535701551428262,79089285.17380854,59010263.421738334,-41.6%,-33.6%,73677209.60001858,,0.9,106485207.11091359,,154344974.80394235,106163091.54130344,-38.2%,-27.0%,88277865.529417,,1.5,109041197.67681886,,176693019.65956077,105621362.95374578,-35.9%,-21.0%,44138932.7647085,,1.6,56723925.8539644,,81727211.51222399,52758207.68074373,-38.0%,-24.8%,29538276.835310083,,0.1,47889339.25429823,,66440288.73407114,48115795.41865598,-40.0%,-29.9%,44138932.7647085,,1.5,54330116.89576573,,80427445.51149154,47310963.48418465,-35.4%,-19.2%,44138932.7647085,,1.5,54520598.838409334,,88346509.82978022,52810681.47687279,-35.9%,-21.0%
-1761,Rouen,,0.0,2.5,52998212.88194155,0.0,37930808.485848546,37930808.485848546,30.0%,25.3%,,0.0,3.3,30070356.62638827,0.0,16140991.81188045,16140991.81188045,53.9%,47.8%,,0.0,1.3,22607940.656955536,0.0,23105982.942496013,23105982.942496013,6.6%,3.6%,,,2.0,37705246.74531254,,19795738.078837086,19795738.078837086,97.5%,93.3%,,,3.1,34142484.4496789,,11826977.654215973,11826977.654215973,157.2%,145.3%,,,3.0,21836733.957371686,,8529849.035960712,8529849.035960712,126.8%,119.7%,,,0.1,15534649.667002313,,11937026.15782948,11937026.15782948,71.2%,70.8%,,,3.1,17071242.224839415,,5913488.827107975,5913488.827107975,157.2%,145.3%,,,3.1,17071242.224839415,,5913488.827107975,5913488.827107975,157.2%,145.3%
-1761,Bordeaux,32110333.543749347,0.102718497384277,3.7,73678316.66562364,0.102718497384277,140131723.33306727,173534423.87859166,-49.2%,-57.2%,11761993.868604999,0.08779538338048574,4.2,27623788.192136653,0.08779538338048574,40912794.64854265,32977615.942917414,-38.5%,-53.8%,20348339.67514435,0.11391037717826083,3.2,44606870.18028828,0.11391037717826083,97942324.18814848,153039901.71326128,-56.9%,-60.6%,28476337.69468049,,2.2,39514010.20880573,,72024560.88428736,84237498.11731091,-53.2%,-55.5%,14499778.648908837,,3.0,16361730.63450998,,23781743.763514515,11434573.258517921,-46.2%,-38.5%,9022853.974535158,,2.9,12341102.222884286,,15276224.035293063,8091016.303511165,-47.7%,-40.4%,19453483.720145334,,1.9,26720347.92028882,,54924959.62911325,88716309.46169995,-53.5%,-55.1%,7249889.324454418,,3.0,8414966.965187255,,12002691.676730987,5717286.629258949,-47.0%,-41.8%,7249889.324454418,,3.0,8180865.317255034,,11890871.881757235,5717286.629258949,-46.2%,-38.5%
-1761,Nantes,12148698.207461763,0.03886275498650027,1.2,31726593.633598287,0.03886275498650027,27222815.151407555,22410880.575839274,-41.9%,-38.6%,2497940.9186654636,0.01864545102352171,1.1,13682184.66983008,0.01864545102352171,14632540.015232634,10923814.718035417,-48.6%,-46.3%,9650757.2887963,0.05402511558058302,0.6,15813783.467416089,0.05402511558058302,16765897.460800594,19364839.254651994,-24.4%,13.7%,11460645.018835468,,0.6,18999296.90301836,,12452908.538105687,7748323.378908675,-23.1%,6.9%,4079634.2382257106,,-0.2,9396831.736796737,,6999068.701047673,1420480.5566499569,-30.2%,53.9%,2039817.1191128553,,0.0,6848080.088148963,,5431221.644581958,1586459.2572821279,-34.6%,31.5%,9420827.899722613,,0.6,10570197.137912655,,8926148.797640057,13638164.446490765,-6.7%,42.0%,2039817.1191128553,,-0.1,4726419.149773066,,3499534.35052383,710240.2783249771,-31.5%,56.8%,2039817.1191128553,,-0.2,4698415.868398384,,3499534.35052383,710240.2783249771,-30.2%,53.9%
-1761,Bayonne,23598481.575110856,0.07548973493667722,0.1,17990721.99833564,0.07548973493667722,17964686.37102178,17964686.37102178,22.6%,40.3%,6892727.48136392,0.051449580617348806,0.3,6458825.631017765,0.051449580617348806,6626192.449656495,6626192.449656495,13.4%,23.8%,16705754.093746938,0.09351911655919855,-0.4,11744705.014178168,0.09351911655919855,11443959.559485465,11443959.559485465,29.2%,49.7%,22004797.632015135,,0.3,15836841.029089218,,14976823.636349471,14976823.636349471,31.5%,49.0%,12331056.959006818,,0.5,10591648.365112577,,8472813.799564736,8472813.799564736,29.0%,37.4%,6168488.479503409,,0.4,5407616.215026847,,4612657.388672475,4612657.388672475,28.9%,36.9%,15836309.152511727,,0.2,10389196.702569174,,10752687.25277356,10752687.25277356,31.3%,52.7%,6165528.479503409,,0.5,5279928.816046784,,4236406.8997823605,4236406.8997823605,30.1%,37.3%,6165528.479503409,,0.5,5295824.182556288,,4236406.8997823605,4236406.8997823605,29.0%,37.4%
-1761,La Rochelle,6125383.682661703,0.01959463320204777,-0.7,14564815.922698343,0.01959463320204777,21146805.455415756,14114613.85569708,47.4%,42.5%,1736264.4450184542,0.012960047786386134,-0.5,6390613.502402433,0.012960047786386134,10823235.025898889,7714511.001187689,149.9%,144.1%,4389119.237643248,0.024570369662691233,-0.8,8080367.691723795,0.024570369662691233,10330330.608791053,6529126.479826897,-0.4%,-1.6%,5986341.283390173,,-1.3,11099815.192897126,,16071592.884861438,13096417.614494823,44.1%,34.1%,2195025.891434608,,1.8,4043381.3916491386,,4748735.994577544,8960653.883137055,8.1%,-17.7%,1640371.1957462041,,-1.0,4217394.278150701,,7762492.513491546,7463445.751207096,99.7%,86.6%,4345970.087643969,,-1.4,6696736.197304344,,8317125.657014132,5844503.81703407,7.4%,2.2%,1097512.945717304,,1.8,1997375.0220938195,,2374367.9972887714,4480326.941568519,9.3%,-17.2%,1097512.945717304,,1.8,2021690.6958245728,,2374367.9972887714,4480326.941568519,8.1%,-17.7%
-1741,Marseille,115366928.14755529,0.2830808785115065,1.1,99923353.65805836,0.2830808785115065,,,-39.5%,-30.6%,51981444.31035002,0.27461636470553585,1.8,46143431.50092662,0.27461636470553585,,,-40.0%,-29.8%,63385483.837205276,0.290422021451805,0.4,52184873.35385978,0.290422021451805,,,-41.6%,-33.6%,96362034.68260647,,0.9,89049690.66010538,,,,-38.2%,-27.0%,80442894.04194802,,1.5,81238712.65471984,,,,-35.9%,-21.0%,43933405.025973506,,1.6,41197641.46897743,,,,-38.0%,-24.8%,52428629.65663297,,0.1,46826193.97874223,,,,-40.0%,-29.9%,40221447.02097401,,1.5,39936096.96326532,,,,-35.4%,-19.2%,40221447.02097401,,1.5,40619356.32735999,,,,-35.9%,-21.0%
-1741,Rouen,,0.0,2.5,31878976.55483264,0.0,,,30.0%,25.3%,,0.0,3.3,15472455.433774333,0.0,,,53.9%,47.8%,,0.0,1.3,17565741.028554123,0.0,,,6.6%,3.6%,,,2.0,25323515.236945573,,,,97.5%,93.3%,,,3.1,18310795.62091911,,,,157.2%,145.3%,,,3.0,11914350.45135005,,,,126.8%,119.7%,,,0.1,15200501.895913703,,,,71.2%,70.8%,,,3.1,9155397.810459537,,,,157.2%,145.3%,,,3.1,9155397.810459537,,,,157.2%,145.3%
-1741,Bordeaux,,0.0,3.7,35107802.40841068,0.0,,,-49.2%,-57.2%,16893245.116355717,0.08924649215661463,4.2,12030818.682559317,0.08924649215661463,,,-38.5%,-53.8%,,0.0,3.2,23666955.391677875,0.0,,,-56.9%,-60.6%,,,2.2,25259482.264533408,,,,-53.2%,-55.5%,,,3.0,9025103.44619066,,,,-46.2%,-38.5%,9129363.116353719,,2.9,6876217.836280496,,,,-47.7%,-40.4%,,,1.9,18312583.784630638,,,,-53.5%,-55.1%,5567610.617730667,,3.0,4577044.001004762,,,,-47.0%,-41.8%,,,3.0,4512551.723095386,,,,-46.2%,-38.5%
-1741,Nantes,57237294.94207373,0.1404456545388895,1.2,25056915.2814544,0.1404456545388895,,,-41.9%,-38.6%,35906236.66444655,0.18969153923804352,1.1,11035429.083520306,0.18969153923804352,,,-48.6%,-46.3%,21331058.27762719,0.09773545439213753,0.6,14010837.141009696,0.09773545439213753,,,-24.4%,13.7%,41832532.556854516,,0.6,17006795.761408933,,,,-23.1%,6.9%,46874659.36724149,,-0.2,9778163.754947368,,,,-30.2%,53.9%,26872116.049812768,,0.0,6817000.902370033,,,,-34.6%,31.5%,14960416.507041749,,0.6,9350493.295346787,,,,-6.7%,42.0%,23437329.683620743,,-0.1,4868580.716469921,,,,-31.5%,56.8%,23437329.683620743,,-0.2,4889081.877473692,,,,-30.2%,53.9%
-1741,Bayonne,,0.0,0.1,17644275.934292138,0.0,,,22.6%,40.3%,,0.0,0.3,6116283.847708822,0.0,,,13.4%,23.8%,,0.0,-0.4,12728079.118132912,0.0,,,29.2%,49.7%,,,0.3,14832332.974444583,,,,31.5%,49.0%,,,0.5,9568801.526067596,,,,29.0%,37.4%,,,0.4,4999059.440659438,,,,28.9%,36.9%,,,0.2,10078712.528684836,,,,31.3%,52.7%,,,0.5,4809232.932112455,,,,30.1%,37.3%,,,0.5,4784400.76303379,,,,29.0%,37.4%
-1741,La Rochelle,16755715.98272359,0.04111423331313859,-0.7,16867117.688993208,0.04111423331313859,,,47.4%,42.5%,7074108.810876449,0.037372298345074786,-0.5,7106012.463137486,0.037372298345074786,,,149.9%,144.1%,9681607.171847142,0.04435955609286887,-0.8,9532609.78367284,0.04435955609286887,,,-0.4%,-1.6%,14140793.81729184,,-1.3,14315978.647624984,,,,44.1%,34.1%,4324248.129338498,,1.8,2796589.535210442,,,,8.1%,-17.7%,5488566.314542199,,-1.0,5112704.024841708,,,,99.7%,86.6%,8652227.502749642,,-1.4,8789780.346896054,,,,7.4%,2.2%,2162124.064669249,,1.8,1386586.669962817,,,,9.3%,-17.2%,2162124.064669249,,1.8,1398294.7676052232,,,,8.1%,-17.7%
-1742,Marseille,,0.0,1.1,101060565.08314164,0.0,,,-39.5%,-30.6%,52176220.79880458,0.2966922991564212,1.8,46981355.05222049,0.2966922991564212,,,-40.0%,-29.8%,,0.0,0.4,52405264.01391359,0.0,,,-41.6%,-33.6%,,,0.9,89849415.94829157,,,,-38.2%,-27.0%,,,1.5,82443118.63253199,,,,-35.9%,-21.0%,44357692.08332365,,1.6,41861718.224279135,,,,-38.0%,-24.8%,,,0.1,46878786.29247541,,,,-40.0%,-29.9%,40873649.5817131,,1.5,40555463.49601087,,,,-35.4%,-19.2%,,,1.5,41221559.31626592,,,,-35.9%,-21.0%
-1742,Rouen,,0.0,2.5,32699582.901943095,0.0,,,30.0%,25.3%,,0.0,3.3,15995145.9550637,0.0,,,53.9%,47.8%,,0.0,1.3,17788781.55773273,0.0,,,6.6%,3.6%,,,2.0,25832585.83481475,,,,97.5%,93.3%,,,3.1,18890202.36711358,,,,157.2%,145.3%,,,3.0,12280788.04798911,,,,126.8%,119.7%,,,0.1,15217037.282723915,,,,71.2%,70.8%,,,3.1,9445101.183556773,,,,157.2%,145.3%,,,3.1,9445101.183556773,,,,157.2%,145.3%
-1742,Bordeaux,52762324.43943313,0.13614507921673594,3.7,36433462.58148543,0.13614507921673594,,,-49.2%,-57.2%,19306091.253180537,0.10978120902464905,4.2,12541358.549987776,0.10978120902464905,,,-38.5%,-53.8%,33456233.186252587,0.15804714754216567,3.2,24428981.47673444,0.15804714754216567,,,-56.9%,-60.6%,34951524.60524518,,2.2,25830973.737462133,,,,-53.2%,-55.5%,13994372.040238822,,3.0,9297603.915999865,,,,-46.2%,-38.5%,10343686.270788386,,2.9,7080270.378888162,,,,-47.7%,-40.4%,24607838.334456794,,1.9,18661830.85960899,,,,-53.5%,-55.1%,6997186.020119411,,3.0,4718548.831959281,,,,-47.0%,-41.8%,6997186.020119411,,3.0,4648801.957999957,,,,-46.2%,-38.5%
-1742,Nantes,58012489.230124384,0.1496923235605687,1.2,25354345.06729807,0.1496923235605687,,,-41.9%,-38.6%,36260581.93065922,0.20619039204164727,1.1,11154690.772905042,0.20619039204164727,,,-48.6%,-46.3%,21751907.29946517,0.10275594634768119,0.6,14095895.456653412,0.10275594634768119,,,-24.4%,13.7%,38714571.65784699,,0.6,17101265.434271403,,,,-23.1%,6.9%,46371799.01820723,,-0.2,9758734.741645494,,,,-30.2%,53.9%,25612612.794653185,,0.0,6818551.506408441,,,,-34.6%,31.5%,13101958.863193799,,0.6,9407992.258115225,,,,-6.7%,42.0%,23185899.509103615,,-0.1,4861372.137332873,,,,-31.5%,56.8%,23185899.509103615,,-0.2,4879367.370822747,,,,-30.2%,53.9%
-1742,Bayonne,,0.0,0.1,17661438.71107684,0.0,,,22.6%,40.3%,,0.0,0.3,6132971.246485496,0.0,,,13.4%,23.8%,,0.0,-0.4,12677009.873756537,0.0,,,29.2%,49.7%,,,0.3,14881010.428124215,,,,31.5%,49.0%,,,0.5,9617514.439291934,,,,29.0%,37.4%,,,0.4,5018734.00786677,,,,28.9%,36.9%,,,0.2,10094014.02222151,,,,31.3%,52.7%,,,0.5,4831738.538345051,,,,30.1%,37.3%,,,0.5,4808757.219645966,,,,29.0%,37.4%
-1742,La Rochelle,,0.0,-0.7,16743802.066865262,0.0,,,47.4%,42.5%,,0.0,-0.5,7068411.002947493,0.0,,,149.9%,144.1%,,0.0,-0.8,9454156.365827926,0.0,,,-0.4%,-1.6%,,,-1.3,14134998.842732115,,,,44.1%,34.1%,,,1.8,2848620.0529321805,,,,8.1%,-17.7%,,,-1.0,5063727.537765816,,,,99.7%,86.6%,,,-1.4,8671061.785792515,,,,7.4%,2.2%,,,1.8,1412123.4024946003,,,,9.3%,-17.2%,,,1.8,1424310.0264660926,,,,8.1%,-17.7%
-1750,Marseille,151081185.75407392,0.32593167485033,1.1,110636770.00542016,0.32593167485033,,,-39.5%,-30.6%,75982636.59665269,0.3578414456779374,1.8,54256371.14871281,0.3578414456779374,,,-40.0%,-29.8%,75098549.15742122,0.29895880214543835,0.4,54202229.25990692,0.29895880214543835,,,-41.6%,-33.6%,132061740.59148782,,0.9,96511264.16046709,,,,-38.2%,-27.0%,130044152.91970532,,1.5,92743919.06843624,,,,-35.9%,-21.0%,66170875.756852664,,1.6,47574542.5293451,,,,-38.0%,-24.8%,65890864.83463517,,0.1,47301656.8492634,,,,-40.0%,-29.9%,65022076.45985266,,1.5,45869011.15660435,,,,-35.4%,-19.2%,65022076.45985266,,1.5,46371959.5342182,,,,-35.9%,-21.0%
-1750,Rouen,58474351.935568735,0.1261483576993546,2.5,40072363.207872786,0.1261483576993546,,,30.0%,25.3%,34308264.03838983,0.16157531973217487,3.3,20865074.64196076,0.16157531973217487,,,53.9%,47.8%,24166087.897178903,0.09620245359384604,1.3,19678138.533179555,0.09620245359384604,,,6.6%,3.6%,47099490.45446172,,2.0,30291375.835619796,,,,97.5%,93.3%,48778721.02002764,,3.1,24236604.306083847,,,,157.2%,145.3%,27801124.507392816,,3.0,15648516.100817258,,,,126.8%,119.7%,19298365.947068904,,0.1,15349969.573503748,,,,71.2%,70.8%,24389360.51001382,,3.1,12118302.153041901,,,,157.2%,145.3%,24389360.51001382,,3.1,12118302.153041901,,,,157.2%,145.3%
-1750,Bordeaux,58859614.518199995,0.12697949546271958,3.7,49008890.157591835,0.12697949546271958,,,-49.2%,-57.2%,25152870.00595,0.11845784470020476,4.2,17487986.355860375,0.11845784470020476,,,-38.5%,-53.8%,33706744.51225,0.13418272492164102,3.2,31478143.01833453,0.13418272492164102,,,-56.9%,-60.6%,32360989.41389,,2.2,30893807.994099647,,,,-53.2%,-55.5%,13315892.584279997,,3.0,11795649.546867425,,,,-46.2%,-38.5%,10678968.204940002,,2.9,8946467.156670624,,,,-47.7%,-40.4%,21682021.208949998,,1.9,21706571.96921062,,,,-53.5%,-55.1%,6657946.292139999,,3.0,6019984.666286526,,,,-47.0%,-41.8%,6657946.292139999,,3.0,5897824.773433785,,,,-46.2%,-38.5%
-1750,Nantes,35756157.6544666,0.07713776068386789,1.2,27864466.55694048,0.07713776068386789,,,-41.9%,-38.6%,19368854.402506195,0.09121793045048972,1.1,12156373.211797424,0.09121793045048972,,,-48.6%,-46.3%,16387303.251960404,0.06523599464392581,0.6,14795217.407584783,0.06523599464392581,,,-24.4%,13.7%,16502110.326686596,,0.6,17876161.15492603,,,,-23.1%,6.9%,9494923.185850594,,-0.2,9604685.992980381,,,,-30.2%,53.9%,7673076.002616197,,0.0,6830969.042744997,,,,-34.6%,31.5%,8829034.3240704,,0.6,9880897.108642116,,,,-6.7%,42.0%,4747461.592925297,,-0.1,4804086.416965626,,,,-31.5%,56.8%,4747461.592925297,,-0.2,4802342.996490199,,,,-30.2%,53.9%
-1750,Bayonne,16629982.379220197,0.03587632690687005,0.1,17799343.290435135,0.03587632690687005,,,22.6%,40.3%,7599680.990409998,0.035790819509667504,0.3,6268119.963809181,0.035790819509667504,,,13.4%,23.8%,9030301.388810199,0.03594860508625689,-0.4,12275763.910346668,0.03594860508625689,,,29.2%,49.7%,14152472.993200198,,0.3,15276225.385851352,,,,31.5%,49.0%,13623254.180799998,,0.5,10016252.173413295,,,,29.0%,37.4%,6811627.090399999,,0.4,5178943.858219288,,,,28.9%,36.9%,7340845.9028002,,0.2,10217265.24561748,,,,31.3%,52.7%,6811627.090399999,,0.5,5015616.55446026,,,,30.1%,37.3%,6811627.090399999,,0.5,5008126.086706638,,,,29.0%,37.4%
-1750,La Rochelle,21139169.508223407,0.04560412263361187,-0.7,15789185.657740965,0.04560412263361187,,,47.4%,42.5%,11434237.193970403,0.0538497234497791,-0.5,6774674.432811335,0.0538497234497791,,,149.9%,144.1%,9704932.314253004,0.038634234244522975,-0.8,8849332.312491441,0.038634234244522975,,,-0.4%,-1.6%,16262212.0072824,,-1.3,12767141.145479564,,,,44.1%,34.1%,3494207.387940801,,1.8,3301269.040980371,,,,8.1%,-17.7%,7578549.693970401,,-1.0,4688433.3946400415,,,,99.7%,86.6%,8683662.313312,,-1.4,7777255.171068647,,,,7.4%,2.2%,1747103.6939704006,,1.8,1634096.4555143467,,,,9.3%,-17.2%,1747103.6939704006,,1.8,1650634.5204901884,,,,8.1%,-17.7%
 1772,Marseille,175456907.62145907,0.28304270042249224,1.1,141913380.2328939,0.28304270042249224,,,-39.5%,-30.6%,92094448.76964861,0.3067260197073342,1.8,80611138.70040196,0.3067260197073342,,,-40.0%,-29.8%,83362458.85181047,0.2607964622045289,0.4,59467995.04418713,0.2607964622045289,,,-41.6%,-33.6%,143339379.73074254,,0.9,117489905.78551431,,,,-38.2%,-27.0%,135495932.28156555,,1.5,128202289.81289227,,,,-35.9%,-21.0%,73461647.39080803,,1.6,67632889.21383418,,,,-38.0%,-24.8%,69877732.33993451,,0.1,48484323.10778524,,,,-40.0%,-29.9%,67747966.14078277,,1.5,64351978.110663414,,,,-35.4%,-19.2%,67747966.14078277,,1.5,64101144.90644602,,,,-35.9%,-21.0%
 1772,Rouen,50188548.491578735,0.08096291270554831,2.5,70093459.52743222,0.08096291270554831,,,30.0%,25.3%,30417758.14715292,0.10130814625138833,3.3,43336837.42591203,0.10130814625138833,,,53.9%,47.8%,19770790.344425816,0.06185220839010474,1.3,25973949.715143073,0.06185220839010474,,,6.6%,3.6%,27239233.79541032,,2.0,46933676.43120171,,,,97.5%,93.3%,24581475.43329114,,3.1,48097053.10508164,,,,157.2%,145.3%,16497983.816645572,,3.0,30472087.375756104,,,,126.8%,119.7%,10741249.97876475,,0.1,15721551.702164758,,,,71.2%,70.8%,12290737.71664557,,3.1,24048526.552540775,,,,157.2%,145.3%,12290737.71664557,,3.1,24048526.552540775,,,,157.2%,145.3%
 1772,Bordeaux,151582962.59931034,0.24452984868920066,3.7,110765502.52870804,0.24452984868920066,,,-49.2%,-57.2%,71456679.29986116,0.23799070536782693,4.2,43634164.537663646,0.23799070536782693,,,-38.5%,-53.8%,80126283.29944919,0.2506722030745419,3.2,63211253.15817211,0.2506722030745419,,,-56.9%,-60.6%,67076361.160788044,,2.2,50539480.37353685,,,,-53.2%,-55.5%,22994287.54647125,,3.0,22695335.9620079,,,,-46.2%,-38.5%,30532458.267706465,,2.9,17023792.901550107,,,,-47.7%,-40.4%,36543902.89308158,,1.9,32892203.982923403,,,,-53.5%,-55.1%,11497143.773235625,,3.0,11762765.67974608,,,,-47.0%,-41.8%,11497143.773235625,,3.0,11347667.981004009,,,,-46.2%,-38.5%
 1772,Nantes,56438762.86667327,0.09104560240371026,1.2,36124027.04837587,0.09104560240371026,,,-41.9%,-38.6%,26390577.55367836,0.08789538260948067,1.1,15399508.889514739,0.08789538260948067,,,-48.6%,-46.3%,30048185.31299491,0.09400466988654528,0.6,16902471.97220096,0.09400466988654528,,,-24.4%,13.7%,26277473.019711316,,0.6,20192997.79637373,,,,-23.1%,6.9%,10624760.982380114,,-0.2,9193475.63826713,,,,-30.2%,53.9%,9126672.648473248,,0.0,6865233.995388926,,,,-34.6%,31.5%,17150800.371238068,,0.6,11307583.340445416,,,,-6.7%,42.0%,5312380.491190057,,-0.1,4650007.522856213,,,,-31.5%,56.8%,5312380.491190057,,-0.2,4596737.819133565,,,,-30.2%,53.9%
 1772,Bayonne,14351581.186162991,0.023151612263838824,0.1,18184158.411918815,0.023151612263838824,,,22.6%,40.3%,6318478.428589949,0.02104406687807619,0.3,6655333.460870896,0.02104406687807619,,,13.4%,23.8%,8033102.757573042,0.02513127381984601,-0.4,11236620.13032034,0.02513127381984601,,,29.2%,49.7%,12683450.411331143,,0.3,16418030.465361984,,,,31.5%,49.0%,10577045.4742607,,0.5,11200098.91403953,,,,29.0%,37.4%,5294044.7371346,,0.4,5646385.427139147,,,,28.9%,36.9%,7389405.674196543,,0.2,10564021.343281819,,,,31.3%,52.7%,5288522.73713035,,0.5,5558169.768326938,,,,30.1%,37.3%,5288522.73713035,,0.5,5600049.457019744,,,,29.0%,37.4%
 1772,La Rochelle,16166496.63837478,0.02607938853435658,-0.7,13435389.731964111,0.02607938853435658,,,47.4%,42.5%,6812748.5150308255,0.022690262694434388,-0.5,6028325.249002505,0.022690262694434388,,,149.9%,144.1%,9353748.123343954,0.02926286547349575,-0.8,7378222.415863986,0.02926286547349575,,,-0.4%,-1.6%,12455924.571555257,,-1.3,9650233.823888846,,,,44.1%,34.1%,5483374.960987239,,1.8,4952317.692192555,,,,8.1%,-17.7%,4407392.690569205,,-1.0,3793679.679381241,,,,99.7%,86.6%,8048531.880986053,,-1.4,5766337.185786854,,,,7.4%,2.2%,2741687.4804936196,,1.8,2441414.6211635494,,,,9.3%,-17.2%,2741687.4804936196,,1.8,2476158.846096282,,,,8.1%,-17.7%
-1765,Marseille,160257892.32954246,0.2974463645600525,1.1,131105315.33200535,0.2974463645600525,,,-39.5%,-30.6%,79928781.17570402,0.36311088574609685,1.8,71069866.87477654,0.36311088574609685,,,-40.0%,-29.8%,80329111.15383846,0.2520865370590232,0.4,57739276.871546924,0.2520865370590232,,,-41.6%,-33.6%,131240655.19075802,,0.9,110362277.15006208,,,,-38.2%,-27.0%,119873828.65299034,,1.5,115652793.97985311,,,,-35.9%,-21.0%,65394596.743587896,,1.6,60470709.758986235,,,,-38.0%,-24.8%,65846058.44717012,,0.1,48104847.47675919,,,,-40.0%,-29.9%,59936914.32649517,,1.5,57779748.04499745,,,,-35.4%,-19.2%,59936914.32649517,,1.5,57826396.98992644,,,,-35.9%,-21.0%
-1765,Rouen,,0.0,2.5,58669528.26696038,0.0,,,30.0%,25.3%,,0.0,3.3,34344282.39080083,0.0,,,53.9%,47.8%,,0.0,1.3,23778251.17602463,0.0,,,6.6%,3.6%,,,2.0,40829808.81546535,,,,97.5%,93.3%,,,3.1,38673430.83126054,,,,157.2%,145.3%,,,3.0,24649672.04576488,,,,126.8%,119.7%,,,0.1,15602355.560206963,,,,71.2%,70.8%,,,3.1,19336715.41563037,,,,157.2%,145.3%,,,3.1,19336715.41563037,,,,157.2%,145.3%
-1765,Bordeaux,73105566.7796037,0.1356874519663624,3.7,85452919.47227961,0.1356874519663624,,,-49.2%,-57.2%,12208544.567678874,0.05546256763124636,4.2,32619766.364119317,0.05546256763124636,,,-38.5%,-53.8%,60897022.211924836,0.1911053069815649,3.2,50635327.61569561,0.1911053069815649,,,-56.9%,-60.6%,46128394.73256859,,2.2,43213201.26167411,,,,-53.2%,-55.5%,10730445.433618477,,3.0,18429122.147549026,,,,-46.2%,-38.5%,9094070.143309936,,2.9,13872502.580287373,,,,-47.7%,-40.4%,37034324.589258656,,1.9,28817785.570237987,,,,-53.5%,-55.1%,5365222.716809238,,3.0,9504863.426955558,,,,-47.0%,-41.8%,5365222.716809238,,3.0,9214561.073774561,,,,-46.2%,-38.5%
-1765,Nantes,39633276.01560694,0.07356126862198989,1.2,33260028.29137273,0.07356126862198989,,,-41.9%,-38.6%,16108269.93565357,0.0731787483574232,1.1,14283304.42527741,0.0731787483574232,,,-48.6%,-46.3%,23525006.07995337,0.07382550649204506,0.6,16201309.867342824,0.07382550649204506,,,-24.4%,13.7%,23363762.806199078,,0.6,19424978.027026422,,,,-23.1%,6.9%,6207370.260550843,,-0.2,9322368.781992689,,,,-30.2%,53.9%,6479597.705893092,,0.0,6854312.907738374,,,,-34.6%,31.5%,16884165.100305986,,0.6,10832602.321089052,,,,-6.7%,42.0%,3103685.1302754213,,-0.1,4698488.897659611,,,,-31.5%,56.8%,3103685.1302754213,,-0.2,4661184.390996343,,,,-30.2%,53.9%
-1765,Bayonne,25243299.21927449,0.04685277881250821,0.1,18060823.272234865,0.04685277881250821,,,22.6%,40.3%,8586017.940574985,0.03900568147762201,0.3,6529602.528798742,0.03900568147762201,,,13.4%,23.8%,16657281.278699506,0.05227340741171398,-0.4,11557341.940947304,0.05227340741171398,,,29.2%,49.7%,22569059.33706682,,0.3,16045763.079774328,,,,31.5%,49.0%,13747589.50330339,,0.5,10808981.052936867,,,,29.0%,37.4%,7078135.752759695,,0.4,5493250.119258537,,,,28.9%,36.9%,15490923.584307127,,0.2,10452432.007676749,,,,31.3%,52.7%,6873794.751651695,,0.5,5379457.966711034,,,,30.1%,37.3%,6873794.751651695,,0.5,5404490.526468414,,,,29.0%,37.4%
-1765,La Rochelle,11571510.03004371,0.02147727978244597,-0.7,14143530.299138762,0.02147727978244597,,,47.4%,42.5%,4171057.278243181,0.018948822695934783,-0.5,6256419.633492755,0.018948822695934783,,,149.9%,144.1%,7400452.75180053,0.02322389081708606,-0.8,7817627.717394021,0.02322389081708606,,,-0.4%,-1.6%,8161223.778470071,,-1.3,10549082.511330657,,,,44.1%,34.1%,1837711.7587005994,,1.8,4352791.89300646,,,,8.1%,-17.7%,2208715.262079641,,-1.0,4058101.5905135614,,,,99.7%,86.6%,5952508.51639043,,-1.4,6342204.2599263415,,,,7.4%,2.2%,918855.8793502997,,1.8,2148632.464289739,,,,9.3%,-17.2%,918855.8793502997,,1.8,2176395.9465032336,,,,8.1%,-17.7%
-1749,Marseille,160025524.75081217,0.3416045824316386,1.1,109391799.73654263,0.3416045824316386,,,-39.5%,-30.6%,88233454.24000002,0.4103729640038772,1.8,53288695.96900149,0.4103729640038772,,,-40.0%,-29.8%,71792070.51081216,0.28326539366321657,0.4,53974281.451461434,0.28326539366321657,,,-41.6%,-33.6%,137854870.17080778,,0.9,95652243.56774089,,,,-38.2%,-27.0%,153302183.48,,1.5,91389029.38953409,,,,-35.9%,-21.0%,77816510.64,,1.6,46819839.92328914,,,,-38.0%,-24.8%,60038359.53080777,,0.1,47248590.12604264,,,,-40.0%,-29.9%,76651091.74,,1.5,45168495.66617413,,,,-35.4%,-19.2%,76651091.74,,1.5,45694514.69476695,,,,-35.9%,-21.0%
-1749,Rouen,,0.0,2.5,39066734.6134435,0.0,,,30.0%,25.3%,,0.0,3.3,20183244.243414413,0.0,,,53.9%,47.8%,,0.0,1.3,19431408.73791802,0.0,,,6.6%,3.6%,,,2.0,29694437.963990577,,,,97.5%,93.3%,,,3.1,23493210.891504105,,,,157.2%,145.3%,,,3.0,15181591.290410751,,,,126.8%,119.7%,,,0.1,15333289.737625958,,,,71.2%,70.8%,,,3.1,11746605.44575203,,,,157.2%,145.3%,,,3.1,11746605.44575203,,,,157.2%,145.3%
-1749,Bordeaux,67491695.93469042,0.14407371975985991,3.7,47225663.16775502,0.14407371975985991,,,-49.2%,-57.2%,29675317.522572573,0.1380196220854007,4.2,16776076.701086937,0.1380196220854007,,,-38.5%,-53.8%,37816378.41211784,0.14920967234414062,3.2,30496228.72477477,0.14920967234414062,,,-56.9%,-60.6%,39217018.244778186,,2.2,30210305.002134845,,,,-53.2%,-55.5%,18266356.929382782,,3.0,11449934.664596094,,,,-46.2%,-38.5%,14754875.312067341,,2.9,8688631.046891822,,,,-47.7%,-40.4%,24462142.93271085,,1.9,21300344.047358546,,,,-53.5%,-55.1%,9133178.464691391,,3.0,5839451.001617858,,,,-47.0%,-41.8%,9133178.464691391,,3.0,5724967.332298077,,,,-46.2%,-38.5%
-1749,Nantes,44409819.76721923,0.09480111351653768,1.2,27537590.737483077,0.09480111351653768,,,-41.9%,-38.6%,23862874.46869859,0.11098600422846013,1.1,12026401.91671214,0.11098600422846013,,,-48.6%,-46.3%,20546945.29852064,0.08107077156502228,0.6,14705939.200595971,0.08107077156502228,,,-24.4%,13.7%,33804773.50883924,,0.6,17777410.85467297,,,,-23.1%,6.9%,38162654.44913618,,-0.2,9623808.305130327,,,,-30.2%,53.9%,22541751.22611316,,0.0,6829415.614839677,,,,-34.6%,31.5%,11263022.282726085,,0.6,9820507.886438143,,,,-6.7%,42.0%,19081327.22456809,,-0.1,4811210.051227651,,,,-31.5%,56.8%,19081327.22456809,,-0.2,4811904.152565164,,,,-30.2%,53.9%
-1749,Bayonne,16263866.812155545,0.03471828284732422,0.1,17782046.502738193,0.03471828284732422,,,22.6%,40.3%,6552822.230642415,0.03047711442946252,0.3,6251064.834539488,0.03047711442946252,,,13.4%,23.8%,9711044.58151313,0.03831624922767872,-0.4,12325216.73820496,0.03831624922767872,,,29.2%,49.7%,13953927.831096992,,0.3,15226255.139730562,,,,31.5%,49.0%,11030525.061095228,,0.5,9965519.645166337,,,,29.0%,37.4%,5515262.530547614,,0.4,5158641.2323296,,,,28.9%,36.9%,8438665.300549379,,0.2,10201776.91582379,,,,31.3%,52.7%,5515262.530547614,,0.5,4992254.468475567,,,,30.1%,37.3%,5515262.530547614,,0.5,4982759.822583169,,,,29.0%,37.4%
-1749,La Rochelle,23321457.508742854,0.04978403768009436,-0.7,15905470.67141364,0.04978403768009436,,,47.4%,42.5%,10665813.021295529,0.04960659582877273,-0.5,6810713.317771388,0.04960659582877273,,,149.9%,144.1%,12655644.487447327,0.0499345692677659,-0.8,8922766.719401607,0.0499345692677659,,,-0.4%,-1.6%,17928852.572391655,,-1.3,12930607.357203852,,,,44.1%,34.1%,3997752.767720057,,1.8,3240970.814418303,,,,8.1%,-17.7%,7697792.48644573,,-1.0,4733780.0282900985,,,,99.7%,86.6%,10231060.085945927,,-1.4,7883736.310985925,,,,7.4%,2.2%,1998876.3838600286,,1.8,1604545.5791235955,,,,9.3%,-17.2%,1998876.3838600286,,1.8,1620485.4072091542,,,,8.1%,-17.7%
-1757,Marseille,,0.0,1.1,119757448.19924584,0.0,165068537.12571332,137523816.31666926,-39.5%,-30.6%,53358505.38187696,0.3626710159482725,1.8,61540397.53241262,0.3626710159482725,84872476.49264306,70147837.01797822,-40.0%,-29.8%,,0.0,0.4,55825047.96835137,0.0,75712100.35260348,64161728.00815517,-41.6%,-33.6%,,,0.9,102744340.06137924,,141827162.22616228,114631636.11099684,-38.2%,-27.0%,,,1.5,102807570.67456913,,154466716.47692856,115348103.42296164,-35.9%,-21.0%,49250171.02619471,,1.6,53209293.84011222,,73201070.91774376,57797163.83497492,-38.0%,-24.8%,,,0.1,47674796.501979776,,63561821.66443849,52927563.94560822,-40.0%,-29.9%,49247496.02619471,,1.5,51086439.4841047,,71376716.21958092,53654290.816327535,-35.4%,-19.2%,,,1.5,51403785.33728447,,77233358.23846413,57674051.711480714,-35.9%,-21.0%
-1757,Rouen,,0.0,2.5,47875117.65730987,0.0,44396223.93874587,44396223.93874587,30.0%,25.3%,,0.0,3.3,26328293.52347641,0.0,21232917.944641374,21232917.944641374,53.9%,47.8%,,0.0,1.3,21495230.11447457,0.0,23485984.857401334,23485984.857401334,6.6%,3.6%,,,2.0,34819796.451909944,,27130675.78929834,27130675.78929834,97.5%,93.3%,,,3.1,30142379.90631796,,19798843.578453537,19798843.578453537,157.2%,145.3%,,,3.0,19344798.95066017,,13107830.17299884,13107830.17299884,126.8%,119.7%,,,0.1,15467237.581226738,,14215415.58727552,14215415.58727552,71.2%,70.8%,,,3.1,15071189.953158952,,9899421.78922675,9899421.78922675,157.2%,145.3%,,,3.1,15071189.953158952,,9899421.78922675,9899421.78922675,157.2%,145.3%
-1757,Bordeaux,39823112.57058905,0.11848076947732528,3.7,63526142.58475932,0.11848076947732528,111225840.64176345,124201884.94352253,-49.2%,-57.2%,11011190.5447474,0.07484167019078293,4.2,23392984.04428134,0.07484167019078293,34689843.83439013,30823049.893489968,-38.5%,-53.8%,28811922.02584165,0.15245363081507063,3.2,39296138.90094225,0.15245363081507063,75054851.14819013,94810427.6065879,-56.9%,-60.6%,29760802.33692637,,2.2,36131481.982252166,,59853365.201187834,64769443.8704954,-53.2%,-55.5%,9770474.583932959,,3.0,14526260.513817577,,20622786.148718953,13823961.575908313,-46.2%,-38.5%,6699487.901823809,,2.9,10978754.784454009,,13946276.50294165,9885608.666920975,-47.7%,-40.4%,23061314.435102563,,1.9,24775567.548071906,,44308885.58733169,56952988.282906964,-53.5%,-55.1%,4885237.291966479,,3.0,7450045.923266258,,10364411.154019706,6911980.787954241,-47.0%,-41.8%,4885237.291966479,,3.0,7263130.256908879,,10311393.07435953,6911980.787954241,-46.2%,-38.5%
-1757,Nantes,,0.0,1.2,30263857.107198473,0.0,30649048.508631703,27449863.28545698,-41.9%,-38.6%,,0.0,1.1,13106363.32920537,0.0,16454366.364679879,13857126.446971772,-48.6%,-46.3%,4984994.270048742,0.026377291850908827,0.6,15435526.485324636,0.026377291850908827,17609770.086215705,19066009.25927136,-24.4%,13.7%,,,0.6,18582944.202398196,,15067163.987115646,11529620.102061639,-23.1%,6.9%,,,-0.2,9471889.468718931,,8907328.17482843,3568215.35096687,-30.2%,53.9%,,,0.0,6841852.9362377785,,6763652.540534975,3357661.9016005564,-34.6%,31.5%,4489054.24027548,,0.6,10314148.366438346,,9765646.595460422,12285431.39758419,-6.7%,42.0%,,,-0.1,4754515.43377466,,4453664.08741427,1784107.6754834317,-31.5%,56.8%,,,-0.2,4735944.734359474,,4453664.08741427,1784107.6754834317,-30.2%,53.9%
-1757,Bayonne,18611987.65773474,0.05537393932435841,0.1,17920892.81549939,0.05537393932435841,17552835.4867688,17552835.4867688,22.6%,40.3%,5846503.622570667,0.039737946056921075,0.3,6388815.911520225,0.039737946056921075,6819286.967828287,6819286.967828287,13.4%,23.8%,12765484.035164073,0.06754649649985409,-0.4,11935105.543719435,0.06754649649985409,10761541.067738337,10761541.067738337,29.2%,49.7%,16603588.978483865,,0.3,15630639.224430766,,14688400.80210848,14688400.80210848,31.5%,49.0%,9782492.759856459,,0.5,10378685.515385514,,9711123.57535645,9711123.57535645,29.0%,37.4%,5012054.379928229,,0.4,5323317.251931034,,5120089.923046211,5120089.923046211,28.9%,36.9%,11591534.598555636,,0.2,10326343.959511226,,9659048.314344099,9659048.314344099,31.3%,52.7%,4891246.379928229,,0.5,5182241.124483654,,4855561.78767825,4855561.78767825,30.1%,37.3%,4891246.379928229,,0.5,5189342.757692748,,4855561.78767825,4855561.78767825,29.0%,37.4%
-1757,La Rochelle,15827263.197905347,0.04708889389507204,-0.7,14998650.151370348,0.04708889389507204,20673840.69697679,16448473.375819903,47.4%,42.5%,7261098.010339802,0.049352765289492874,-0.5,6527685.693980327,0.049352765289492874,10355266.71681836,8556226.917632082,149.9%,144.1%,8566165.187565545,0.04532647922046703,-0.8,8351938.003926681,0.04532647922046703,10293999.665976055,7936947.700808612,-0.4%,-1.6%,13720239.882770658,,-1.3,11679299.804901112,,15997783.883447764,14252804.421544338,44.1%,34.1%,6399163.0339124035,,1.8,3755964.787703757,,4736414.276617298,6794162.580488943,8.1%,-17.7%,6629970.019595803,,-1.0,4382939.6826725155,,7520729.2128031645,7363633.921358325,99.7%,86.6%,7090269.863174854,,-1.4,7071086.621988936,,8458876.415481482,6926203.961567047,7.4%,2.2%,3199581.5169562018,,1.8,1856765.6615032325,,2368207.1383086485,3397081.290244513,9.3%,-17.2%,3199581.5169562018,,1.8,1877982.3938518818,,2368207.1383086485,3397081.290244513,8.1%,-17.7%
-1767,Marseille,155819227.45312315,0.29682941739939794,1.1,134106473.0574304,0.29682941739939794,,,-39.5%,-30.6%,86346788.65913217,0.3628936753606946,1.8,73674433.15216587,0.3628936753606946,,,-40.0%,-29.8%,69472438.79399098,0.24205941222801428,0.4,58228003.48809261,0.24205941222801428,,,-41.6%,-33.6%,128966281.18182853,,0.9,112353431.02572499,,,,-38.2%,-27.0%,135628413.29271185,,1.5,119107439.10255398,,,,-35.9%,-21.0%,73431204.5040921,,1.6,62435911.84405481,,,,-38.0%,-24.8%,55535076.677736424,,0.1,48212964.996261716,,,,-40.0%,-29.9%,67814206.64635593,,1.5,59585850.94170867,,,,-35.4%,-19.2%,67814206.64635593,,1.5,59553719.551277086,,,,-35.9%,-21.0%
-1767,Rouen,72615731.36479175,0.13833007381278928,2.5,61728863.58548295,0.13833007381278928,,,30.0%,25.3%,46901043.470863774,0.19711320256023665,3.3,36703914.135292016,0.19711320256023665,,,53.9%,47.8%,25714687.893927973,0.08959642622722243,1.3,24385932.267161176,0.08959642622722243,,,6.6%,3.6%,54385603.323712915,,2.0,42487886.27316337,,,,97.5%,93.3%,62104164.38109187,,3.1,41159632.81825231,,,,157.2%,145.3%,37322380.098282464,,3.0,26189238.86745259,,,,126.8%,119.7%,17063223.22543045,,0.1,15636319.084541326,,,,71.2%,70.8%,31052082.190545935,,3.1,20579816.409126114,,,,157.2%,145.3%,31052082.190545935,,3.1,20579816.409126114,,,,157.2%,145.3%
-1767,Bordeaux,83484634.5525411,0.15903490115484933,3.7,92028111.45646977,0.15903490115484933,,,-49.2%,-57.2%,28239948.84003925,0.11868534992095474,4.2,35447013.56903809,0.11868534992095474,,,-38.5%,-53.8%,55244685.71250185,0.1924863497586935,3.2,53948523.14519771,0.1924863497586935,,,-56.9%,-60.6%,41453650.0629854,,2.2,45190703.95930138,,,,-53.2%,-55.5%,6769393.804244387,,3.0,19558806.653492995,,,,-46.2%,-38.5%,7100075.402736494,,2.9,14708055.045870142,,,,-47.7%,-40.4%,34353574.660248905,,1.9,29927459.647699237,,,,-53.5%,-55.1%,3384696.9021221935,,3.0,10101656.900729105,,,,-47.0%,-41.8%,3384696.9021221935,,3.0,9779403.326746617,,,,-46.2%,-38.5%
-1767,Nantes,34526296.0226709,0.06577121771734944,1.2,34054318.8841293,0.06577121771734944,,,-41.9%,-38.6%,15138961.52786769,0.06362521959768364,1.1,14593696.66102005,0.06362521959768364,,,-48.6%,-46.3%,19387334.494803213,0.06755033901135889,0.6,16398619.86836373,0.06755033901135889,,,-24.4%,13.7%,17197466.436339036,,0.6,19641381.87992608,,,,-23.1%,6.9%,5215632.42922733,,-0.2,9285358.871682039,,,,-30.2%,53.9%,5241694.204087175,,0.0,6857431.444524254,,,,-34.6%,31.5%,11955772.232251858,,0.6,10966237.727030123,,,,-6.7%,42.0%,2607816.214613665,,-0.1,4684585.726725589,,,,-31.5%,56.8%,2607816.214613665,,-0.2,4642679.435841028,,,,-30.2%,53.9%
-1767,Bayonne,17957913.890987836,0.03420911016629248,0.1,18095976.2744873,0.03420911016629248,,,22.6%,40.3%,6924296.990026709,0.02910106586499012,0.3,6565281.293105168,0.02910106586499012,,,13.4%,23.8%,11033616.900961125,0.038443890385301174,-0.4,11464784.277454263,0.038443890385301174,,,29.2%,49.7%,15797545.245239848,,0.3,16151255.393302448,,,,31.5%,49.0%,11510302.465596821,,0.5,10919314.035267485,,,,29.0%,37.4%,5768971.23279611,,0.4,5536574.26748987,,,,28.9%,36.9%,10028574.012443738,,0.2,10484193.848108243,,,,31.3%,52.7%,5755151.232798411,,0.5,5429923.911405836,,,,30.1%,37.3%,5755151.232798411,,0.5,5459657.017633752,,,,29.0%,37.4%
-1767,La Rochelle,12283463.360102393,0.023399508086528922,-0.7,13937479.373390945,0.023399508086528922,,,47.4%,42.5%,6113870.114851836,0.02569504704355723,-0.5,6190383.132422773,0.02569504704355723,,,149.9%,144.1%,6169593.245250556,0.021496411246764074,-0.8,7689479.011792183,0.021496411246764074,,,-0.4%,-1.6%,8123421.203556097,,-1.3,10284049.535425298,,,,44.1%,34.1%,4133765.6479212395,,1.8,4516265.883989482,,,,8.1%,-17.7%,3621021.481952576,,-1.0,3980725.8606826193,,,,99.7%,86.6%,4502399.721603521,,-1.4,6172040.140642409,,,,7.4%,2.2%,2066882.8239606197,,1.8,2228503.8704464235,,,,9.3%,-17.2%,2066882.8239606197,,1.8,2258132.941994761,,,,8.1%,-17.7%
+1747,Marseille,74418213.11469391,0.2349028236830506,1.1,106943729.65168639,0.2349028236830506,157918215.64789405,157918215.64789405,-39.5%,-30.6%,35600040.11585111,0.2652305599040694,1.8,51404813.941700846,0.2652305599040694,83515657.30117384,83515657.30117384,-40.0%,-29.8%,38818172.998842806,0.21260765671829318,0.4,53521257.71075132,0.21260765671829318,69240024.84175745,69240024.84175745,-41.6%,-33.6%,69839685.9997605,,0.9,93957072.05622636,,143568815.19998568,143568815.19998568,-38.2%,-27.0%,68075928.23187415,,1.5,88738341.3466393,,135728515.724472,135728515.724472,-35.9%,-21.0%,34037964.11593708,,1.6,45346161.64547945,,72979970.39535964,72979970.39535964,-38.0%,-24.8%,35801721.88382342,,0.1,47142635.216096245,,64320138.92377951,64320138.92377951,-40.0%,-29.9%,34037964.11593708,,1.5,43799396.29822887,,61266851.09179798,61266851.09179798,-35.4%,-19.2%,34037964.11593708,,1.5,44369170.67331973,,67864257.86223587,67864257.86223587,-35.9%,-21.0%
+1747,Rouen,,0.0,2.5,37130553.80530753,0.0,,,30.0%,25.3%,,0.0,3.3,18885698.05670441,0.0,,,53.9%,47.8%,,0.0,1.3,18947191.05311458,0.0,,,6.6%,3.6%,,,2.0,28535621.121689726,,,,97.5%,93.3%,,,3.1,22074129.534360103,,,,157.2%,145.3%,,,3.0,14289122.655891182,,,,126.8%,119.7%,,,0.1,15299984.420926163,,,,71.2%,70.8%,,,3.1,11037064.76718011,,,,157.2%,145.3%,,,3.1,11037064.76718011,,,,157.2%,145.3%
+1747,Bordeaux,41561901.25071488,0.13119110971372314,3.7,43851500.67550866,0.13119110971372314,136777273.831927,136777273.831927,-49.2%,-57.2%,20593033.58523307,0.15342403576401398,4.2,15438019.945747757,0.15342403576401398,36109939.61307012,36109939.61307012,-38.5%,-53.8%,20968867.665481817,0.11484677082888409,3.2,28623332.808687188,0.11484677082888409,108366457.06960236,108366457.06960236,-56.9%,-60.6%,17008904.476898536,,2.2,28888330.471893486,,94939465.31813589,94939465.31813589,-53.2%,-55.5%,8616353.575038956,,3.0,10788605.268901268,,55848997.020615384,55848997.020615384,-46.2%,-38.5%,7251971.785057778,,2.9,8195037.089626348,,19856833.858060952,19856833.858060952,-47.7%,-40.4%,9756932.691840757,,1.9,20510553.00232486,,78216630.69632474,78216630.69632474,-53.5%,-55.1%,4308176.787519478,,3.0,5494463.413697069,,26590273.181962773,26590273.181962773,-47.0%,-41.8%,4308176.787519478,,3.0,5394302.634450663,,27924498.51030764,27924498.51030764,-46.2%,-38.5%
+1747,Nantes,,0.0,1.2,26895297.777685836,0.0,49129073.4282306,49129073.4282306,-41.9%,-38.6%,,0.0,1.1,11770613.27963306,0.0,45343789.02018678,45343789.02018678,-48.6%,-46.3%,,0.0,0.6,14528995.719865622,0.0,13551994.805240542,13551994.805240542,-24.4%,13.7%,,,0.6,17581543.770215776,,33741712.93515794,33741712.93515794,-23.1%,6.9%,,,-0.2,9662167.219108943,,155148135.74107653,155148135.74107653,-30.2%,53.9%,,,0.0,6826309.818741934,,43860489.33209423,43860489.33209423,-34.6%,31.5%,,,0.6,9700834.431364555,,8271739.065752125,8271739.065752125,-6.7%,42.0%,,,-0.1,4825489.024789835,,77574067.87053372,77574067.87053372,-31.5%,56.8%,,,-0.2,4831083.609554488,,77574067.87053372,77574067.87053372,-30.2%,53.9%
+1747,Bayonne,,0.0,0.1,17747503.336274996,0.0,,,22.6%,40.3%,,0.0,0.3,6217093.667282734,0.0,,,13.4%,23.8%,12752367.735913675,0.06984488997005078,-0.4,12424720.85757836,0.06984488997005078,,,29.2%,49.7%,,,0.3,15126804.487632912,,,,31.5%,49.0%,,,0.5,9864824.171130637,,,,29.0%,37.4%,,,0.4,5118274.441129128,,,,28.9%,36.9%,9514095.241400063,,0.2,10170870.656819722,,,,31.3%,52.7%,,,0.5,4945856.242272204,,,,30.1%,37.3%,,,0.5,4932412.085565317,,,,29.0%,37.4%
+1747,La Rochelle,47706829.27353594,0.1505877181980615,-0.7,16140616.271883965,0.1505877181980615,6554848.815469976,6554848.815469976,47.4%,42.5%,11180400.85292304,0.08329720889422143,-0.5,6883367.2501169825,0.08329720889422143,1015652.3014705472,1015652.3014705472,149.9%,144.1%,36526428.4206129,0.20005574077446867,-0.8,9071468.732076941,0.20005574077446867,8908489.55381297,8908489.55381297,-0.4%,-1.6%,38153804.2132972,,-1.3,13263845.478659647,,5231504.456952391,5231504.456952391,44.1%,34.1%,1930034.9251064789,,1.8,3123658.316150477,,919954.6553990665,919954.6553990665,8.1%,-17.7%,5061472.217591039,,-1.0,4825793.318671586,,689849.0760232756,689849.0760232756,99.7%,86.6%,33092331.995706163,,-1.4,8101092.163419812,,7134931.393649759,7134931.393649759,7.4%,2.2%,965017.4625532394,,1.8,1547037.3497924036,,459977.3276995324,459977.3276995324,9.3%,-17.2%,965017.4625532394,,1.8,1561829.1580752411,,459977.3276995324,459977.3276995324,8.1%,-17.7%
 1744,Marseille,60782878.49634711,0.19675748626326692,1.1,103373962.48329306,0.19675748626326692,135028534.99808362,135028534.99808362,-39.5%,-30.6%,32198747.948294297,0.22686329096060476,1.8,48703126.2953083,0.22686329096060476,65962071.54714142,65962071.54714142,-40.0%,-29.8%,28584130.54805281,0.17116999805124836,0.4,52848841.57079367,0.17116999805124836,65572729.99251215,65572729.99251215,-41.6%,-33.6%,52177668.18760845,,0.9,91470477.2149799,,118335471.45300852,118335471.45300852,-38.2%,-27.0%,54888158.909766234,,1.5,84905763.13841173,,108109571.53204407,108109571.53204407,-35.9%,-21.0%,28740089.852575596,,1.6,43222157.62158059,,57064840.84212788,57064840.84212788,-38.0%,-24.8%,23437578.33503285,,0.1,46984148.19168277,,57676659.42404339,57676659.42404339,-40.0%,-29.9%,27444079.454883117,,1.5,41823162.691247515,,50707761.04877756,50707761.04877756,-35.4%,-19.2%,27444079.454883117,,1.5,42452881.56920593,,54054785.76602194,54054785.76602194,-35.9%,-21.0%
 1744,Rouen,,0.0,2.5,34404709.76810238,0.0,,,30.0%,25.3%,,0.0,3.3,17094096.10122973,0.0,,,53.9%,47.8%,,0.0,1.3,18243394.72953286,0.0,,,6.6%,3.6%,,,2.0,26881633.809551377,,,,97.5%,93.3%,,,3.1,20104598.34001563,,,,157.2%,145.3%,,,3.0,13047820.314696755,,,,126.8%,119.7%,,,0.1,15250162.038409267,,,,71.2%,70.8%,,,3.1,10052299.17000787,,,,157.2%,145.3%,,,3.1,10052299.17000787,,,,157.2%,145.3%
 1744,Bordeaux,46519817.77354968,0.15058718232798007,3.7,39236842.64856241,0.15058718232798007,75852197.08732973,75852197.08732973,-49.2%,-57.2%,18768215.945350405,0.13223555281276225,4.2,13628353.487674983,0.13223555281276225,24841197.560156405,24841197.560156405,-38.5%,-53.8%,27751601.82819928,0.1661845765385886,3.2,26027430.544414956,0.1661845765385886,51791285.09937011,51791285.09937011,-56.9%,-60.6%,25768339.19805635,,2.2,27013038.9109922,,50322865.10691945,50322865.10691945,-53.2%,-55.5%,10617157.886147797,,3.0,9867536.602007223,,22983675.18012308,22983675.18012308,-46.2%,-38.5%,7749348.642382153,,2.9,7506721.0021865405,,13251132.971200963,13251132.971200963,-47.7%,-40.4%,18018990.5556742,,1.9,19380433.956033636,,37411380.96191818,37411380.96191818,-53.5%,-55.1%,5308578.943073899,,3.0,5014818.122963398,,11491837.590062171,11491837.590062171,-47.0%,-41.8%,5308578.943073899,,3.0,4933768.301003638,,11491837.590061517,11491837.590061517,-46.2%,-38.5%
 1744,Nantes,30708149.493465453,0.09940395143500792,1.2,25959838.171394,0.09940395143500792,48613591.86794969,48613591.86794969,-41.9%,-38.6%,14908209.789692322,0.10503903880523002,1.1,11397094.722644603,0.10503903880523002,33441998.63592493,33441998.63592493,-48.6%,-46.3%,15799939.70377313,0.09461458496203659,0.6,14267564.36303913,0.09461458496203659,17365778.52436812,17365778.52436812,-24.4%,13.7%,17217072.771855608,,0.6,17291781.98076567,,32179781.49783325,32179781.49783325,-23.1%,6.9%,11558556.855900852,,-0.2,9719992.453501804,,53276600.14150528,53276600.14150528,-30.2%,53.9%,7875552.63778672,,0.0,6821653.772672804,,24635291.612736236,24635291.612736236,-34.6%,31.5%,9341520.13406889,,0.6,9524053.092551697,,11091377.326496037,11091377.326496037,-6.7%,42.0%,5779278.427950426,,-0.1,4846986.9830265725,,26638300.070751075,26638300.070751075,-31.5%,56.8%,5779278.427950426,,-0.2,4859996.22675091,,26638300.070751075,26638300.070751075,-30.2%,53.9%
 1744,Bayonne,,0.0,0.1,17695814.36413725,0.0,,,22.6%,40.3%,,0.0,0.3,6166482.755744498,0.0,,,13.4%,23.8%,,0.0,-0.4,12575485.282722633,0.0,,,29.2%,49.7%,,,0.3,14978845.115692155,,,,31.5%,49.0%,,,0.5,9715685.492187552,,,,29.0%,37.4%,,,0.4,5058315.743882788,,,,28.9%,36.9%,,,0.2,10124686.736710537,,,,31.3%,52.7%,,,0.5,4877066.19986129,,,,30.1%,37.3%,,,0.5,4857842.746093758,,,,29.0%,37.4%
 1744,La Rochelle,11166413.175277064,0.03614628726536171,-0.7,16499868.915562442,0.03614628726536171,10480037.455167525,10480037.455167525,47.4%,42.5%,5592241.20323792,0.039401353283963755,-0.5,6993803.934032164,0.039401353283963755,2680454.232890331,2680454.232890331,149.9%,144.1%,5574171.972039144,0.03337974558950719,-0.8,9299181.232112797,0.03337974558950719,9287006.856599228,9287006.856599228,-0.4%,-1.6%,9668706.345578816,,-1.3,13779874.043614818,,8601024.699418707,8601024.699418707,44.1%,34.1%,2051098.3527088405,,1.8,2955603.180151123,,1994520.5433100706,1994520.5433100706,8.1%,-17.7%,4404401.676200421,,-1.0,4967177.561093064,,1945837.197912497,1945837.197912497,99.7%,86.6%,5264304.669378394,,-1.4,8438413.3986444,,7857038.222789073,7857038.222789073,7.4%,2.2%,1025549.1763544203,,1.8,1464616.4573555626,,997260.2716550335,997260.2716550335,9.3%,-17.2%,1025549.1763544203,,1.8,1477801.590075564,,997260.2716550335,997260.2716550335,8.1%,-17.7%
-1775,Marseille,152787784.539378,0.24442011303897138,1.1,146814012.0103885,0.24442011303897138,,,-39.5%,-30.6%,80127942.99381651,0.27341799044505166,1.8,85082845.84026769,0.27341799044505166,,,-40.0%,-29.8%,72659841.54556146,0.2188266590913049,0.4,60224629.21988743,0.2188266590913049,,,-41.6%,-33.6%,121943636.64649874,,0.9,120683830.23545636,,,,-38.2%,-27.0%,121320676.70099051,,1.5,133989238.59021832,,,,-35.9%,-21.0%,65460153.10098726,,1.6,70956474.54004087,,,,-38.0%,-24.8%,56483483.545511484,,0.1,48647870.52528242,,,,-40.0%,-29.9%,60660338.35049526,,1.5,67392746.27917486,,,,-35.4%,-19.2%,60660338.35049526,,1.5,66994619.29510904,,,,-35.9%,-21.0%
-1775,Rouen,65971194.48840465,0.10553649208792615,2.5,75646880.55576693,0.10553649208792615,,,30.0%,25.3%,33387256.816037744,0.11392625748321476,3.3,47878894.64944471,0.11392625748321476,,,53.9%,47.8%,32583937.6723669,0.09813170616966366,1.3,26975976.50837041,0.09813170616966366,,,6.6%,3.6%,38917118.56775449,,2.0,49821436.37463313,,,,97.5%,93.3%,32476506.515058845,,3.1,52808843.156512596,,,,157.2%,145.3%,23083616.707529612,,3.0,33371044.633621,,,,126.8%,119.7%,15833501.860224877,,0.1,15772914.117901227,,,,71.2%,70.8%,16238253.257529423,,3.1,26404421.57825625,,,,157.2%,145.3%,16238253.257529423,,3.1,26404421.57825625,,,,157.2%,145.3%
-1775,Bordeaux,122460882.93295462,0.19590507801106746,3.7,123792669.8757618,0.19590507801106746,,,-49.2%,-57.2%,47402819.63788839,0.16175110957011415,4.2,49428208.84838986,0.16175110957011415,,,-38.5%,-53.8%,75058063.29506624,0.2260492849881032,3.2,69515764.65886584,0.2260492849881032,,,-56.9%,-60.6%,39606589.29155147,,2.2,54048017.91161677,,,,-53.2%,-55.5%,24928661.739739727,,3.0,24813794.061771814,,,,-46.2%,-38.5%,13987543.970443632,,2.9,18584760.802177746,,,,-47.7%,-40.4%,25619045.32110784,,1.9,34810226.36982797,,,,-53.5%,-55.1%,12464330.869869864,,3.0,12887822.466642952,,,,-47.0%,-41.8%,12464330.869869864,,3.0,12406897.030885972,,,,-46.2%,-38.5%
-1775,Nantes,,0.0,1.2,37425751.962731704,0.0,,,-41.9%,-38.6%,9274319.78045202,0.031646461675818506,1.1,15904199.117921278,0.031646461675818506,,,-48.6%,-46.3%,,0.0,0.6,17212183.99234516,0.0,,,-24.4%,13.7%,,,0.6,20531375.829496503,,,,-23.1%,6.9%,,,-0.2,9138782.706537915,,,,-30.2%,53.9%,5523338.952474541,,0.0,6869919.786668153,,,,-34.6%,31.5%,,,0.6,11517469.793433085,,,,-6.7%,42.0%,5488098.802153831,,-0.1,4629383.232368753,,,,-31.5%,56.8%,,,-0.2,4569391.3532689735,,,,-30.2%,53.9%
-1775,Bayonne,,0.0,0.1,18237273.823177196,0.0,,,22.6%,40.3%,5270909.792168358,0.0179857551479018,0.3,6709956.575276249,0.0179857551479018,,,13.4%,23.8%,,0.0,-0.4,11101907.032859178,0.0,,,29.2%,49.7%,,,0.3,16580205.950681228,,,,31.5%,49.0%,,,0.5,11372023.78309945,,,,29.0%,37.4%,4471157.12116435,,0.4,5713314.802746327,,,,28.9%,36.9%,,,0.2,10612209.29520938,,,,31.3%,52.7%,4460449.32115738,,0.5,5636566.640221181,,,,30.1%,37.3%,,,0.5,5686011.891549725,,,,29.0%,37.4%
-1775,La Rochelle,21914111.126649827,0.035056791581030256,-0.7,13142860.178865233,0.035056791581030256,,,47.4%,42.5%,10256685.78201927,0.0349985574366043,-0.5,5933134.097471586,0.0349985574366043,,,149.9%,144.1%,11657425.344630556,0.03510818889100147,-0.8,7197549.146873909,0.03510818889100147,,,-0.4%,-1.6%,18095687.265619174,,-1.3,9288851.978462568,,,,44.1%,34.1%,11078295.128981061,,1.8,5233905.704028015,,,,8.1%,-17.7%,7562050.016051711,,-1.0,3685697.5263653453,,,,99.7%,86.6%,10533637.249567464,,-1.4,5535830.822760907,,,,7.4%,2.2%,5539147.564490531,,1.8,2578804.5643627294,,,,9.3%,-17.2%,5539147.564490531,,1.8,2616952.852014031,,,,8.1%,-17.7%
 1789,Marseille,213669273.7414955,0.19826930062346937,1.1,172017882.49746597,0.19826930062346937,,,-39.5%,-30.6%,131546378.56101577,0.20666365849679788,1.8,109461429.57523678,0.20666365849679788,,,-40.0%,-29.8%,82122895.1804797,0.1861572424231317,0.4,63884874.665554464,0.1861572424231317,,,-41.6%,-33.6%,158724007.9136053,,0.9,136775682.51456955,,,,-38.2%,-27.0%,194887727.8724723,,1.5,164645257.39341834,,,,-35.9%,-21.0%,99920806.93623611,,1.6,88760099.08259206,,,,-38.0%,-24.8%,58803200.97736919,,0.1,49418416.36355904,,,,-40.0%,-29.9%,97443863.93623614,,1.5,83596033.11295666,,,,-35.4%,-19.2%,97443863.93623614,,1.5,82322628.696709,,,,-35.9%,-21.0%
 1789,Rouen,150323252.0,0.13948887230994217,2.5,107974405.67601399,0.13948887230994217,,,30.0%,25.3%,108058409.0,0.1697632909363983,3.3,76234165.80436963,0.1697632909363983,,,53.9%,47.8%,42264843.0,0.09580649351238134,1.3,32187951.99536518,0.09580649351238134,,,6.6%,3.6%,97033228.0,,2.0,65831037.76506064,,,,97.5%,93.3%,128977050.0,,3.1,81680462.34712058,,,,157.2%,145.3%,75253362.0,,3.0,50997856.2780074,,,,126.8%,119.7%,21779866.0,,0.1,16014832.97683502,,,,71.2%,70.8%,64488525.0,,3.1,40840231.17356022,,,,157.2%,145.3%,64488525.0,,3.1,40840231.17356022,,,,157.2%,145.3%
 1789,Bordeaux,250634332.2362001,0.23257014401060813,3.7,207993692.153928,0.23257014401060813,,,-49.2%,-57.2%,119052135.35924602,0.1870347942249562,4.2,88443620.14966173,0.1870347942249562,,,-38.5%,-53.8%,131582196.8769541,0.29827222808888193,3.2,108334019.32427597,0.29827222808888193,,,-56.9%,-60.6%,109222850.736045,,2.2,73927911.2582569,,,,-53.2%,-55.5%,68508988.71849193,,3.0,37631983.406531766,,,,-46.2%,-38.5%,44592478.35924597,,2.9,27987235.48644562,,,,-47.7%,-40.4%,64630372.37679904,,1.9,45349404.26425288,,,,-53.5%,-55.1%,34254494.35924596,,3.0,19738160.425209932,,,,-47.0%,-41.8%,34254494.35924596,,3.0,18815991.703265984,,,,-46.2%,-38.5%
 1789,Nantes,99155476.17309555,0.09200895650355169,1.2,44148669.91874606,0.09200895650355169,,,-41.9%,-38.6%,55708633.02290355,0.08752008254661811,1.1,18487073.204050627,0.08752008254661811,,,-48.6%,-46.3%,43446843.15019201,0.09848586676170357,0.6,18734243.983849782,0.09848586676170357,,,-24.4%,13.7%,36653963.92305924,,0.6,22186999.634974115,,,,-23.1%,6.9%,22074354.145734515,,-0.2,8887820.033030251,,,,-30.2%,53.9%,16568169.07286724,,0.0,6891829.1357208155,,,,-34.6%,31.5%,20085794.850192,,0.6,12549634.47813604,,,,-6.7%,42.0%,11037177.072867258,,-0.1,4534339.514337402,,,,-31.5%,56.8%,11037177.072867258,,-0.2,4443910.016515141,,,,-30.2%,53.9%
 1789,Bayonne,27236435.207829148,0.025273399705874465,0.1,18487204.489753794,0.025273399705874465,,,22.6%,40.3%,10583312.229999999,0.01662672928279216,0.3,6970851.949597883,0.01662672928279216,,,13.4%,23.8%,16653122.977829149,0.03774951485177117,-0.4,10494289.947466467,0.03774951485177117,,,29.2%,49.7%,24135246.207829148,,0.3,17358463.652066853,,,,31.5%,49.0%,16850744.46,,0.5,12209895.992143333,,,,29.0%,37.4%,8485059.23,,0.4,6036294.8732518805,,,,28.9%,36.9%,15650186.977829149,,0.2,10840009.03529703,,,,31.3%,52.7%,8425372.23,,0.5,6017293.906140569,,,,30.1%,37.3%,8425372.23,,0.5,6104947.9960716665,,,,29.0%,37.4%
 1789,La Rochelle,23933450.373430233,0.02220847379669346,-0.7,11859729.267982388,0.02220847379669346,,,47.4%,42.5%,10599154.435469542,0.016651617905168607,-0.5,5508403.880996161,0.016651617905168607,,,149.9%,144.1%,13334295.937960692,0.030226354733469702,-0.8,6411182.720648419,0.030226354733469702,,,-0.4%,-1.6%,13188711.37343025,,-1.3,7773352.040401663,,,,44.1%,34.1%,6158930.870939104,,1.8,6774965.373099353,,,,8.1%,-17.7%,4679014.435469553,,-1.0,3221033.0265379595,,,,99.7%,86.6%,8509696.937960697,,-1.4,4576172.928921031,,,,7.4%,2.2%,3079465.435469552,,1.8,3329486.404714676,,,,9.3%,-17.2%,3079465.435469552,,1.8,3387482.686549682,,,,8.1%,-17.7%
-1777,Marseille,151112290.19980615,0.2089809290509686,1.1,150174760.6209985,0.2089809290509686,173358839.78867877,164496623.03903565,-39.5%,-30.6%,89843072.74581158,0.2525672942899529,1.8,88200959.33624989,0.2525672942899529,98690896.93124546,92430946.13595872,-40.0%,-29.8%,61269217.45399458,0.16677707145122483,0.4,60734392.77887384,0.16677707145122483,76821683.75453392,73675367.65258697,-41.6%,-33.6%,123496709.83509737,,0.9,122861205.35409795,,140567811.3070282,131101881.52944699,-38.2%,-27.0%,139048842.87283474,,1.5,137991608.56037912,,145690855.8546969,135670688.15902448,-35.9%,-21.0%,75605403.43685709,,1.6,73262447.33696975,,80619240.14901212,74532991.76882146,-38.0%,-24.8%,47891306.398240276,,0.1,48757208.51024984,,62007330.2745304,58318833.45540923,-40.0%,-29.9%,69524421.43641737,,1.5,69499336.18983637,,75101053.86178377,69893322.65312018,-35.4%,-19.2%,69524421.43641737,,1.5,68995804.28018944,,72845427.92734857,67835344.07951212,-35.9%,-21.0%
-1777,Rouen,,0.0,2.5,79591503.60382162,0.0,68021879.07273585,74244769.94752476,30.0%,25.3%,,0.0,3.3,51168425.0120365,0.0,43034499.13043162,47918063.190999724,53.9%,47.8%,,0.0,1.3,27665379.220021844,0.0,24484975.554656886,26034635.70321741,6.6%,3.6%,,,2.0,51844659.18560084,,41865805.74869321,44624097.74577151,97.5%,93.3%,,,3.1,56203769.543036625,,43488133.78557815,51410360.87674253,157.2%,145.3%,,,3.0,35455330.09703795,,28683119.308540292,31998389.366859127,126.8%,119.7%,,,0.1,15807248.917566514,,13035221.04387457,13089956.556532284,71.2%,70.8%,,,3.1,28101884.77151826,,21744066.892789032,25705180.438371398,157.2%,145.3%,,,3.1,28101884.77151826,,21744066.892789032,25705180.438371398,157.2%,145.3%
-1777,Bordeaux,217388523.5054081,0.3006377280571239,3.7,133317921.62485684,0.3006377280571239,141087381.89084882,183692938.4664771,-49.2%,-57.2%,120227951.69289368,0.3379854175625682,4.2,53712291.19744271,0.3379854175625682,61596987.98495649,128213823.77880245,-38.5%,-53.8%,97160571.81251444,0.2644746628204424,3.2,74064354.18208799,0.2644746628204424,80425704.69681863,78093241.51310693,-56.9%,-60.6%,59057810.17789017,,2.2,56521338.519697286,,58907320.55170934,58084423.392243005,-53.2%,-55.5%,36852013.61007379,,3.0,26334851.79099195,,25508355.077534895,56148294.6041229,-46.2%,-38.5%,21552870.305040076,,2.9,19704136.53273926,,23427099.3140133,42857059.46725968,-47.7%,-40.4%,37504939.87285009,,1.9,36150648.7884419,,35718473.99888389,27150171.6412217,-53.5%,-55.1%,18426006.805036895,,3.0,13697025.923205303,,14423028.399563003,32602414.631756365,-47.0%,-41.8%,18426006.805036895,,3.0,13167425.895496044,,12754177.53876747,28074147.302061398,-46.2%,-38.5%
-1777,Nantes,,0.0,1.2,38319525.18656729,0.0,50227925.31550208,53308462.97874995,-41.9%,-38.6%,,0.0,1.1,16249815.214513786,0.0,18931237.889594946,21209962.128082592,-48.6%,-46.3%,,0.0,0.6,17421805.070449855,0.0,18881947.84682757,8424322.887595592,-24.4%,13.7%,,,0.6,20760105.50057534,,23500346.455626417,18908740.956105825,-23.1%,6.9%,,,-0.2,9102501.635039167,,8365386.186339876,18229862.06122427,-30.2%,53.9%,,,0.0,6873045.424184143,,7016021.199092125,8952140.03673124,-34.6%,31.5%,,,0.6,11659554.004192255,,11663818.140210373,4584281.522699413,-6.7%,42.0%,,,-0.1,4615684.55013268,,4337451.419707727,7753999.945308745,-31.5%,56.8%,,,-0.2,4551250.817519584,,4182693.0931699304,9114931.030612119,-30.2%,53.9%
-1777,Bayonne,,0.0,0.1,18272770.26307482,0.0,14876808.70995809,11181565.434552787,22.6%,40.3%,6885074.526691326,0.019355355855993635,0.3,6746620.822158007,0.019355355855993635,5371253.993493127,4639972.804640209,13.4%,23.8%,,0.0,-0.4,11012996.747040102,0.0,9400096.291887583,6661294.4805581905,29.2%,49.7%,,,0.3,16689211.940350538,,13498701.591307161,10240740.135900317,31.5%,49.0%,,,0.5,11488104.040154172,,9006064.098314527,7937041.768015481,29.0%,37.4%,6314869.7217075545,,0.4,5758374.556449987,,4501319.935665669,4038974.8065355998,28.9%,36.9%,,,0.2,10644456.651423944,,8939468.439962208,6283605.0883489465,31.3%,52.7%,6261668.171903195,,0.5,5689444.581101883,,4480554.318110707,4058658.68718726,30.1%,37.3%,,,0.5,5744052.020077085,,4503032.049157255,3968520.884007705,29.0%,37.4%
-1777,La Rochelle,,0.0,-0.7,12951387.579764977,0.0,14564157.69580894,24358813.89616819,47.4%,42.5%,,0.0,-0.5,5870509.87481258,0.0,6471725.863323258,9720696.471529692,149.9%,144.1%,,0.0,-0.8,7079564.9398969915,0.0,8113834.130846441,13001990.460270384,-0.4%,-1.6%,,,-1.3,9055480.774857698,,10550179.326237082,21267245.12459574,44.1%,34.1%,,,1.8,5430470.91433387,,6520621.780958988,17605242.798880335,8.1%,-17.7%,,,-1.0,3615422.4162731594,,4100174.239223311,8183731.338833762,99.7%,86.6%,,,-1.4,5387302.056128157,,6308418.776524988,12063358.494078534,7.4%,2.2%,,,1.8,2674666.816368223,,3112975.626424253,8303597.756660247,9.3%,-17.2%,,,1.8,2715235.4571669395,,3260310.890479505,8802621.39944015,8.1%,-17.7%
-1746,Marseille,73432842.2245298,0.24564045206185903,1.1,105740316.32126555,0.24564045206185903,149886782.61053583,149886782.61053583,-39.5%,-30.6%,32880300.461018704,0.26918058675083567,1.8,50487996.95752178,0.26918058675083567,77198707.8360006,77198707.8360006,-40.0%,-29.8%,40552541.76351109,0.22937629922717642,0.4,53296173.732342966,0.22937629922717642,67995352.83097889,67995352.83097889,-41.6%,-33.6%,67484302.60745627,,0.9,93120785.63483693,,134610331.17076057,134610331.17076057,-38.2%,-27.0%,58479464.72048733,,1.5,87441968.88339737,,125815876.82497229,125815876.82497229,-35.9%,-21.0%,29651222.161240414,,1.6,44626809.13993772,,67234470.97064297,67234470.97064297,-38.0%,-24.8%,37833080.44621586,,0.1,47089746.89586505,,62024701.37928923,62024701.37928923,-40.0%,-29.9%,29239732.360243663,,1.5,43130488.144232534,,57523042.87762122,57523042.87762122,-35.4%,-19.2%,29239732.360243663,,1.5,43720984.4416986,,62907938.412486024,62907938.412486024,-35.9%,-21.0%
-1746,Rouen,,0.0,2.5,36198750.84574895,0.0,,,30.0%,25.3%,,0.0,3.3,18268549.867503464,0.0,,,53.9%,47.8%,,0.0,1.3,18709626.074016966,0.0,,,6.6%,3.6%,,,2.0,27973283.08097356,,,,97.5%,93.3%,,,3.1,21397064.285400935,,,,157.2%,145.3%,,,3.0,13862759.80819415,,,,126.8%,119.7%,,,0.1,15283358.900735278,,,,71.2%,70.8%,,,3.1,10698532.142700449,,,,157.2%,145.3%,,,3.1,10698532.142700449,,,,157.2%,145.3%
-1746,Bordeaux,35852053.14820024,0.11992882579353403,3.7,42255929.35573394,0.11992882579353403,112373873.33652481,112373873.33652481,-49.2%,-57.2%,11962451.279120866,0.0979327928620843,4.2,14809561.344149902,0.0979327928620843,31876846.491373897,31876846.491373897,-38.5%,-53.8%,23889601.869079374,0.13512614076562443,3.2,27730470.113521285,0.13512614076562443,84725761.12460215,84725761.12460215,-56.9%,-60.6%,23487910.349078428,,2.2,28249197.20887268,,76833917.0087485,76833917.0087485,-53.2%,-55.5%,10446944.025855407,,3.0,10472405.522071678,,41541618.25833723,41541618.25833723,-46.2%,-38.5%,6600125.512250955,,2.9,7958857.1041997215,,17352324.954885703,17352324.954885703,-47.7%,-40.4%,16887784.83682747,,1.9,20126707.99289686,,61169366.47667411,61169366.47667411,-53.5%,-55.1%,5223472.012927704,,3.0,5329689.635946812,,20103809.455090284,20103809.455090284,-47.0%,-41.8%,5223472.012927704,,3.0,5236202.761035866,,20770809.129166212,20770809.129166212,-46.2%,-38.5%
-1746,Nantes,29253335.959653705,0.09785543432290571,1.2,26579791.199346468,0.09785543432290571,48956641.75424564,48956641.75424564,-41.9%,-38.6%,8183454.363562834,0.06699534421359975,1.1,11644766.382269194,0.06699534421359975,40967797.25016963,40967797.25016963,-48.6%,-46.3%,21069881.59609087,0.11917702949053509,0.6,14441323.96408914,0.11917702949053509,14719743.321885489,14719743.321885489,-24.4%,13.7%,20173608.97870717,,0.6,17484420.97572012,,33212822.243591122,33212822.243591122,-23.1%,6.9%,5517820.611745157,,-0.2,9681403.972683586,,108645032.73977771,108645032.73977771,-30.2%,53.9%,4332129.955432768,,0.0,6824757.450388859,,36188302.96708259,36188302.96708259,-34.6%,31.5%,15841479.0232744,,0.6,9641545.700837487,,9121362.39486122,9121362.39486122,-6.7%,42.0%,2758910.3058725786,,-0.1,4832644.395439835,,54322516.36988566,54322516.36988566,-31.5%,56.8%,2758910.3058725786,,-0.2,4840701.986341801,,54322516.36988566,54322516.36988566,-30.2%,53.9%
-1746,Bayonne,,0.0,0.1,17730256.924856924,0.0,,,22.6%,40.3%,,0.0,0.3,6200177.377104896,0.0,,,13.4%,23.8%,19382859.430333726,0.10963476939369013,-0.4,12474773.75744219,0.10963476939369013,,,29.2%,49.7%,,,0.3,15077323.014024427,,,,31.5%,49.0%,,,0.5,9814858.628905015,,,,29.0%,37.4%,,,0.4,5098209.653013298,,,,28.9%,36.9%,12685509.671766309,,0.2,10155452.656480605,,,,31.3%,52.7%,,,0.5,4922819.090698647,,,,30.1%,37.3%,,,0.5,4907429.314452516,,,,29.0%,37.4%
-1746,La Rochelle,21321328.080479153,0.07132204759600864,-0.7,16259489.519975789,0.07132204759600864,7664715.944905764,7664715.944905764,47.4%,42.5%,9353645.776156569,0.07657532999950249,-0.5,6919984.342631898,0.07657532999950249,1403565.9917032623,1403565.9917032623,149.9%,144.1%,11967682.304322582,0.06769249368635398,-0.8,9146746.493451513,0.06769249368635398,9032916.010519791,9032916.010519791,-0.4%,-1.6%,13829966.502062157,,-1.3,13433671.32679489,,6174490.565571938,6174490.565571938,44.1%,34.1%,2027781.73072188,,1.8,3066604.17893487,,1190667.370638581,1190667.370638581,8.1%,-17.7%,4265938.24099594,,-1.0,4872468.500608254,,974701.3294551437,974701.3294551437,99.7%,86.6%,9564028.261066217,,-1.4,8212007.069663957,,7367941.284550942,7367941.284550942,7.4%,2.2%,1013890.86536094,,1.8,1519060.8436679833,,595333.6853192893,595333.6853192893,9.3%,-17.2%,1013890.86536094,,1.8,1533302.0894674375,,595333.6853192893,595333.6853192893,8.1%,-17.7%
-1752,Marseille,152649217.7040942,0.2778400692675755,1.1,113169378.20804681,0.2778400692675755,,,-39.5%,-30.6%,72536829.71123928,0.2851612616381191,1.8,56244756.95611082,0.2851612616381191,,,-40.0%,-29.8%,80112387.99285492,0.27152809873580075,0.4,54661016.99592844,0.27152809873580075,,,-41.6%,-33.6%,128178268.88924642,,0.9,98252518.35203207,,,,-38.2%,-27.0%,122358614.1987883,,1.5,95514257.0485614,,,,-35.9%,-21.0%,62664310.407607,,1.6,49120639.64888437,,,,-38.0%,-24.8%,65513958.48163942,,0.1,47407969.16652792,,,,-40.0%,-29.9%,61179307.09939415,,1.5,47302803.38869776,,,,-35.4%,-19.2%,61179307.09939415,,1.5,47757128.52428061,,,,-35.9%,-21.0%
-1752,Rouen,,0.0,2.5,42161945.30747096,0.0,,,30.0%,25.3%,,0.0,3.3,22298614.34781673,0.0,,,53.9%,47.8%,,0.0,1.3,20181036.43794371,0.0,,,6.6%,3.6%,,,2.0,31521492.97044888,,,,97.5%,93.3%,,,3.1,25794704.854406856,,,,157.2%,145.3%,,,3.0,16625889.599042216,,,,126.8%,119.7%,,,0.1,15383383.698898392,,,,71.2%,70.8%,,,3.1,12897352.427203404,,,,157.2%,145.3%,,,3.1,12897352.427203404,,,,157.2%,145.3%
-1752,Bordeaux,92987045.605435,0.16924768813478386,3.7,52779889.01530614,0.16924768813478386,,,-49.2%,-57.2%,26313651.377653956,0.10344585026707855,4.2,19003719.485042114,0.10344585026707855,,,-38.5%,-53.8%,66673394.22778104,0.22597878336302415,3.2,33537836.27275435,0.22597878336302415,,,-56.9%,-60.6%,57185673.23863688,,2.2,32307556.266956586,,,,-53.2%,-55.5%,26708037.430537343,,3.0,12518709.62666699,,,,-46.2%,-38.5%,16084385.291098023,,2.9,9485320.377114981,,,,-47.7%,-40.4%,41101287.94753886,,1.9,22542417.60232049,,,,-53.5%,-55.1%,13354018.715268672,,3.0,6397968.79921665,,,,-47.0%,-41.8%,13354018.715268672,,3.0,6259354.813333572,,,,-46.2%,-38.5%
-1752,Nantes,,0.0,1.2,28529904.465305164,0.0,,,-41.9%,-38.6%,,0.0,1.1,12420544.845152345,0.0,,,-48.6%,-46.3%,19488858.359375678,0.06605436174645747,0.6,14975403.107734887,0.06605436174645747,,,-24.4%,13.7%,,,0.6,18075310.422616266,,,,-23.1%,6.9%,,,-0.2,9566555.28012457,,,,-30.2%,53.9%,,,0.0,6834076.958670305,,,,-34.6%,31.5%,11292195.219725497,,0.6,10002791.890434805,,,,-6.7%,42.0%,,,-0.1,4789870.775279177,,,,-31.5%,56.8%,,,-0.2,4783277.640062293,,,,-30.2%,53.9%
-1752,Bayonne,16041652.941921158,0.029197751757821418,0.1,17833987.356508385,0.029197751757821418,,,22.6%,40.3%,6549367.101444947,0.025747276149426908,0.3,6302369.946690495,0.025747276149426908,,,13.4%,23.8%,9492285.840476211,0.03217258143835562,-0.4,12177452.721585495,0.03217258143835562,,,29.2%,49.7%,13639866.063100826,,0.3,15376658.400468208,,,,31.5%,49.0%,11470318.401993232,,0.5,10118493.353100473,,,,29.0%,37.4%,5735159.200996616,,0.4,5219789.136792827,,,,28.9%,36.9%,7904706.86210421,,0.2,10248312.484015128,,,,31.3%,52.7%,5735159.200996616,,0.5,5062669.218355788,,,,30.1%,37.3%,5735159.200996616,,0.5,5059246.676550236,,,,29.0%,37.4%
-1752,La Rochelle,19547146.653775062,0.03557817499462138,-0.7,15559159.89664935,0.03557817499462138,,,47.4%,42.5%,9562134.84912517,0.0375912546548455,-0.5,6703167.753010611,0.0375912546548455,,,149.9%,144.1%,9985011.804649893,0.03384259712009734,-0.8,8704271.621156255,0.03384259712009734,,,-0.4%,-1.6%,15876864.524760611,,-1.3,12446382.12136957,,,,44.1%,34.1%,6605259.492172438,,1.8,3425251.909608857,,,,8.1%,-17.7%,7352134.248290169,,-1.0,4599039.142775541,,,,99.7%,86.6%,8524730.276470441,,-1.4,7568588.007036547,,,,7.4%,2.2%,3302629.746086219,,1.8,1694840.9447961512,,,,9.3%,-17.2%,3302629.746086219,,1.8,1712625.9548044312,,,,8.1%,-17.7%
+1766,Marseille,149053946.65444914,0.2943413152268615,1.1,132597403.58791907,0.2943413152268615,,,-39.5%,-30.6%,80910757.86589214,0.3814922040994452,1.8,72360432.25547408,0.3814922040994452,,,-40.0%,-29.8%,68143188.788557,0.23153689909462127,0.4,57983125.261375755,0.23153689909462127,,,-41.6%,-33.6%,124848376.0315132,,0.9,111353403.60142358,,,,-38.2%,-27.0%,123989810.9937569,,1.5,117367406.5317777,,,,-35.9%,-21.0%,66919275.50400648,,1.6,61445454.703008555,,,,-38.0%,-24.8%,57929100.52750672,,0.1,48158875.895804584,,,,-40.0%,-29.9%,61994905.49687845,,1.5,58675850.692245625,,,,-35.4%,-19.2%,61994905.49687845,,1.5,58683703.26588874,,,,-35.9%,-21.0%
+1766,Rouen,50794330.35516087,0.10030509314500914,2.5,60179758.283129,0.10030509314500914,,,30.0%,25.3%,25353315.665176697,0.11954025063476152,3.3,35504501.00917031,0.11954025063476152,,,53.9%,47.8%,25441014.689984173,0.08644346934537375,1.3,24080174.887447976,0.08644346934537375,,,6.6%,3.6%,32461012.994699825,,2.0,41650597.51680049,,,,97.5%,93.3%,19910871.337098226,,3.1,39897170.48659934,,,,157.2%,145.3%,15854264.768555736,,3.0,25407797.016091533,,,,126.8%,119.7%,16606748.226144088,,0.1,15619328.09085793,,,,71.2%,70.8%,9955435.668549113,,3.1,19948585.243299633,,,,157.2%,145.3%,9955435.668549113,,3.1,19948585.243299633,,,,157.2%,145.3%
+1766,Bordeaux,73181925.17871957,0.14451455054642207,3.7,88679596.28615703,0.14451455054642207,,,-49.2%,-57.2%,25701500.307875685,0.12118193253566495,4.2,34004018.89376862,0.12118193253566495,,,-38.5%,-53.8%,47480424.87084388,0.16132896827593743,3.2,52265678.45001176,0.16132896827593743,,,-56.9%,-60.6%,47958470.483713806,,2.2,44190892.561137795,,,,-53.2%,-55.5%,16176883.27914538,,3.0,18985563.907282736,,,,-46.2%,-38.5%,13881372.391643638,,2.9,14284170.664579805,,,,-47.7%,-40.4%,34077098.09207017,,1.9,29367381.817066137,,,,-53.5%,-55.1%,8088441.63957269,,3.0,9798717.73383606,,,,-47.0%,-41.8%,8088441.63957269,,3.0,9492781.953641418,,,,-46.2%,-38.5%
+1766,Nantes,100683009.86086693,0.19882177029602358,1.2,33654830.40411241,0.19882177029602358,,,-41.9%,-38.6%,17623090.132152636,0.08309243016486681,1.1,14437666.435387094,0.08309243016486681,,,-48.6%,-46.3%,83059919.7287143,0.28222096140390956,0.6,16299666.312048368,0.28222096140390956,,,-24.4%,13.7%,83084941.07071419,,0.6,19532880.264774106,,,,-23.1%,6.9%,9033962.493100537,,-0.2,9303845.424068866,,,,-30.2%,53.9%,8006979.924876008,,0.0,6855871.998814855,,,,-34.6%,31.5%,75077961.14583819,,0.6,10899215.212823391,,,,-6.7%,42.0%,4516981.2465502685,,-0.1,4691532.162007936,,,,-31.5%,56.8%,4516981.2465502685,,-0.2,4651922.712034441,,,,-30.2%,53.9%
+1766,Bayonne,17116868.576660886,0.03380119562415703,0.1,18078391.229090884,0.03380119562415703,,,22.6%,40.3%,6562373.214066982,0.030941425931358367,0.3,6547417.608014215,0.030941425931358367,,,13.4%,23.8%,10554495.362593904,0.035862060041632844,-0.4,11510970.079612572,0.035862060041632844,,,29.2%,49.7%,14749631.745971393,,0.3,16098422.825912433,,,,31.5%,49.0%,10278198.891821126,,0.5,10864007.479667613,,,,29.0%,37.4%,5217394.446202063,,0.4,5514869.649880446,,,,28.9%,36.9%,9532237.29976933,,0.2,10468300.881836263,,,,31.3%,52.7%,5139099.445910563,,0.5,5404632.035934256,,,,30.1%,37.3%,5139099.445910563,,0.5,5432003.739833796,,,,29.0%,37.4%
+1766,La Rochelle,12916548.066509645,0.0255066962762233,-0.7,14040126.844554398,0.0255066962762233,,,47.4%,42.5%,4934124.974354845,0.02326427611626961,-0.5,6223313.793191868,0.02326427611626961,,,149.9%,144.1%,7982423.092154801,0.02712267392935955,-0.8,7753288.609029472,0.02712267392935955,,,-0.4%,-1.6%,8919377.001444036,,-1.3,10415723.071386525,,,,44.1%,34.1%,3128933.9135037195,,1.8,4433775.53857784,,,,8.1%,-17.7%,3064539.3321407954,,-1.0,4019227.5310853706,,,,99.7%,86.6%,5854837.669303241,,-1.4,6256543.716175793,,,,7.4%,2.2%,1564466.9567518597,,1.8,2188203.7754369495,,,,9.3%,-17.2%,1564466.9567518597,,1.8,2216887.7692889236,,,,8.1%,-17.7%
+1771,Marseille,,0.0,1.1,140316461.42247352,0.0,,,-39.5%,-30.6%,97527353.57682055,0.28966096717579226,1.8,79173420.02373561,0.28966096717579226,,,-40.0%,-29.8%,,0.0,0.4,59217902.02535612,0.0,,,-41.6%,-33.6%,,,0.9,116444159.99215975,,,,-38.2%,-27.0%,,,1.5,126329391.17949577,,,,-35.9%,-21.0%,83992829.23529848,,1.6,66559989.40164362,,,,-38.0%,-24.8%,,,0.1,48429929.57643149,,,,-40.0%,-29.9%,80349822.38526821,,1.5,63369189.15642921,,,,-35.4%,-19.2%,,,1.5,63164695.589747764,,,,-35.9%,-21.0%
+1771,Rouen,73327506.14141776,0.10838863509631849,2.5,68334442.05153278,0.10838863509631849,,,30.0%,25.3%,47961553.222477585,0.14244813771895437,3.3,41920673.15902633,0.14244813771895437,,,53.9%,47.8%,25365952.91894017,0.07464326419413904,1.3,25648281.345416684,0.07464326419413904,,,6.6%,3.6%,51453789.00759831,,2.0,46008776.58285473,,,,97.5%,93.3%,62977417.3674629,,3.1,46621803.846255615,,,,157.2%,145.3%,35994140.73476239,,3.0,29562852.68992697,,,,126.8%,119.7%,15459648.272835914,,0.1,15704468.091615528,,,,71.2%,70.8%,31488708.68373145,,3.1,23310901.923127763,,,,157.2%,145.3%,31488708.68373145,,3.1,23310901.923127763,,,,157.2%,145.3%
+1771,Bordeaux,,0.0,3.7,106735212.65646468,0.0,,,-49.2%,-57.2%,93415459.66051455,0.2774484429450052,4.2,41857883.24488141,0.2774484429450052,,,-38.5%,-53.8%,,0.0,3.2,61239471.24734967,0.0,,,-56.9%,-60.6%,,,2.2,49421331.19444386,,,,-53.2%,-55.5%,,,3.0,22030165.69147376,,,,-46.2%,-38.5%,53203407.53370418,,2.9,16533169.2331736,,,,-47.7%,-40.4%,,,1.9,32276642.406085275,,,,-53.5%,-55.1%,31251537.82019224,,3.0,11410011.426617254,,,,-47.0%,-41.8%,,,3.0,11015082.845737016,,,,-46.2%,-38.5%
+1771,Nantes,46403343.88607542,0.06859083817765257,1.2,35700258.9880969,0.06859083817765257,,,-41.9%,-38.6%,24093575.25181427,0.07155908628922289,1.1,15234863.227591015,0.07155908628922289,,,-48.6%,-46.3%,22309768.634261154,0.06564996629926921,0.6,16800478.040663056,0.06564996629926921,,,-24.4%,13.7%,20780052.006272167,,0.6,20081448.981271904,,,,-23.1%,6.9%,11113484.961163802,,-0.2,9211779.257045092,,,,-30.2%,53.9%,8921777.875814755,,0.0,6863672.775304593,,,,-34.6%,31.5%,11858274.13045741,,0.6,11238474.619301133,,,,-6.7%,42.0%,5556742.480581901,,-0.1,4656902.684606733,,,,-31.5%,56.8%,5556742.480581901,,-0.2,4605889.628522554,,,,-30.2%,53.9%
+1771,Bayonne,15032020.643571433,0.022219495603111872,0.1,18166487.674163703,0.022219495603111872,,,22.6%,40.3%,5366804.854854901,0.015939670542546955,0.3,6637224.749939479,0.015939670542546955,,,13.4%,23.8%,9665215.78871653,0.028441401666083155,-0.4,11281886.774829965,0.028441401666083155,,,29.2%,49.7%,13682754.93062103,,0.3,16364325.246798461,,,,31.5%,49.0%,9367509.497662019,,0.5,11143370.17711401,,,,29.0%,37.4%,4686539.7488310095,,0.4,5624250.32506148,,,,28.9%,36.9%,8996215.18179002,,0.2,10548007.366686417,,,,31.3%,52.7%,4683754.7488310095,,0.5,5532280.540425385,,,,30.1%,37.3%,4683754.7488310095,,0.5,5571685.088556995,,,,29.0%,37.4%
+1771,La Rochelle,10840840.44986194,0.016024326497499734,-0.7,13534339.387288002,0.016024326497499734,,,47.4%,42.5%,5076204.03314896,0.015076572016951065,-0.5,6060393.818836411,0.015076572016951065,,,149.9%,144.1%,5764636.416712981,0.01696333981265783,-0.8,7439449.112752218,0.01696333981265783,,,-0.4%,-1.6%,7820871.77738863,,-1.3,9773792.195138093,,,,44.1%,34.1%,5398855.7463514,,1.8,4861862.78818313,,,,8.1%,-17.7%,3614279.8251026403,,-1.0,3830372.2348952508,,,,99.7%,86.6%,4206591.95228599,,-1.4,5845286.139265206,,,,7.4%,2.2%,2699427.8731757,,1.8,2397264.264282786,,,,9.3%,-17.2%,2699427.8731757,,1.8,2430931.3940915694,,,,8.1%,-17.7%
 1763,Marseille,169785284.90606418,0.382614739482333,1.1,128171320.26836383,0.382614739482333,186634533.85805428,126277877.11869399,-39.5%,-30.6%,89767126.8384973,0.4856942705568228,1.8,68557378.20427269,0.4856942705568228,100157166.30190037,64922557.27857506,-40.0%,-29.8%,80018158.06756689,0.3090366897929949,0.4,57254652.296826884,0.3090366897929949,80833955.01831111,56591773.47161654,-41.6%,-33.6%,142388924.57498908,,0.9,108406410.97073717,,161012292.90030143,102166399.8569994,-38.2%,-27.0%,132687047.80941623,,1.5,112298348.92033619,,188978166.84701416,101070036.37546903,-35.9%,-21.0%,69700948.87807575,,1.6,58567363.40920032,,86355758.78289549,50405947.85982723,-38.0%,-24.8%,72687975.69691333,,0.1,47996972.41067175,,67928042.39955418,45876528.97906135,-40.0%,-29.9%,66343523.90470812,,1.5,56028389.81706152,,85374491.6563587,44426332.157499544,-35.4%,-19.2%,66343523.90470812,,1.5,56149174.46016798,,94489083.42350759,50535018.18773406,-35.9%,-21.0%
 1763,Rouen,45496805.8926687,0.1025280167449892,2.5,55761816.22558067,0.1025280167449892,35060260.035069674,35060260.035069674,30.0%,25.3%,23824953.36938641,0.1289073601365602,3.3,32136347.327734295,0.1289073601365602,14073123.053521525,14073123.053521525,53.9%,47.8%,21671852.523282293,0.08369847203708286,1.3,23185713.09047341,0.08369847203708286,22918293.894243,22918293.894243,6.6%,3.6%,39888433.2691375,,2.0,39236437.35038987,,16909362.8134576,16909362.8134576,97.5%,93.3%,30615416.253933746,,3.1,36337405.11885865,,9140937.76567844,9140937.76567844,157.2%,145.3%,20300729.95827831,,3.0,23200610.565238003,,6880921.676754013,6880921.676754013,126.8%,119.7%,19587703.310859192,,0.1,15568465.807773763,,10938667.916278984,10938667.916278984,71.2%,70.8%,15307708.126966873,,3.1,18168702.55942929,,4570468.88283921,4570468.88283921,157.2%,145.3%,15307708.126966873,,3.1,18168702.55942929,,4570468.88283921,4570468.88283921,157.2%,145.3%
 1763,Bordeaux,42108656.50012191,0.09489275025017051,3.7,79347509.48127322,0.09489275025017051,157290265.69675007,205123002.0719624,-49.2%,-57.2%,15484627.192607678,0.08378116771731833,4.2,30018019.870061643,0.08378116771731833,44431149.24220834,34110735.138909064,-38.5%,-53.8%,26624029.30751423,0.10282418497059592,3.2,47525608.733499505,0.10282418497059592,111883546.57615617,194437023.66083226,-56.9%,-60.6%,29538789.618085355,,2.2,41322232.22200102,,79009014.0234356,96066751.54331602,-53.2%,-55.5%,10519481.571252503,,3.0,17364686.360792104,,25538293.516160283,10399529.300618645,-46.2%,-38.5%,9599851.23902209,,2.9,13084417.160521613,,15988027.725508874,7319862.231757759,-47.7%,-40.4%,19938938.379063264,,1.9,27749256.86805032,,61151794.502412416,110725319.64015524,-53.5%,-55.1%,5259740.785626251,,3.0,8943327.778095106,,12916524.103285553,5199764.650309387,-47.0%,-41.8%,5259740.785626251,,3.0,8682343.180396097,,12769146.75808012,5199764.650309387,-46.2%,-38.5%
 1763,Nantes,26764634.611834906,0.060314671586602774,1.2,32484263.911044143,0.060314671586602774,25656124.421796415,20249685.805524908,-41.9%,-38.6%,12612316.607264312,0.0682402359342293,1.1,13979513.898632051,0.0682402359342293,13798726.261958664,9698953.965608016,-48.6%,-46.3%,14152318.004570594,0.05465741295041143,0.6,16006373.921993395,0.05465741295041143,16359249.109431682,19516006.076503597,-24.4%,13.7%,19515145.026653104,,0.6,19210958.457871974,,11321147.273713471,6351906.665315053,-23.1%,6.9%,5011015.006621557,,-0.2,9359526.207706902,,6204212.408413563,896246.3740673491,-30.2%,53.9%,8042691.182263212,,0.0,6851195.7891615955,,4866936.109354549,1090498.0752910515,-34.6%,31.5%,11472453.844389893,,0.6,10700595.406355737,,8533863.29210467,14369401.46336373,-6.7%,42.0%,2505507.5033107786,,-0.1,4712433.331188307,,3102106.204206776,448123.18703367375,-31.5%,56.8%,2505507.5033107786,,-0.2,4679763.10385345,,3102106.204206776,448123.18703367375,-30.2%,53.9%
 1763,Bayonne,21338824.637405492,0.04808749376612484,0.1,18025738.557735935,0.04808749376612484,18174221.563314687,18174221.563314687,22.6%,40.3%,6681517.054268036,0.036151035085752216,0.3,6494117.659340931,0.036151035085752216,6531705.34092628,6531705.34092628,13.4%,23.8%,14657307.583137456,0.056607724123638965,-0.4,11650646.842318045,0.056607724123638965,11801229.003855824,11801229.003855824,29.2%,49.7%,19294620.88845586,,0.3,15940959.791832302,,15123151.965412226,15123151.965412226,31.5%,49.0%,10687733.208918752,,0.5,10699762.91783473,,7914195.11793455,7914195.11793455,29.0%,37.4%,5519893.104585826,,0.4,5450264.986044314,,4378123.445527572,4378123.445527572,28.9%,36.9%,13774727.783870034,,0.2,10420766.38966558,,11345100.626962999,11345100.626962999,31.3%,52.7%,5343866.604459376,,0.5,5329461.054661154,,3957097.558967296,3957097.558967296,30.1%,37.3%,5343866.604459376,,0.5,5349881.4589173645,,3957097.558967296,3957097.558967296,29.0%,37.4%
 1763,La Rochelle,,0.0,-0.7,14352627.470399374,0.0,21387330.080032382,13074970.084667971,47.4%,42.5%,,0.0,-0.5,6323160.585221167,0.0,11065090.98038157,7325233.234216371,149.9%,144.1%,,0.0,-0.8,7947912.0801349515,0.0,10348544.135937022,5921829.010380642,-0.4%,-1.6%,,,-1.3,10820945.722550936,,16108624.987309044,12553898.41435381,44.1%,34.1%,,,1.8,4195235.123554287,,4754908.8688946245,10290621.060908312,8.1%,-17.7%,,,-1.0,4136981.318302781,,7886273.154012304,7513857.870450475,99.7%,86.6%,,,-1.4,6517059.830793844,,8247143.559205203,5368758.041757407,7.4%,2.2%,,,1.8,2071623.7148266681,,2377454.434447312,5145310.530454219,9.3%,-17.2%,,,1.8,2097617.5617771465,,2377454.434447312,5145310.530454219,8.1%,-17.7%
-1770,Marseille,151567891.1033504,0.23796213791096818,1.1,138737512.37419125,0.23796213791096818,,,-39.5%,-30.6%,88861607.23503114,0.26233363587958486,1.8,77761343.39885685,0.26233363587958486,,,-40.0%,-29.8%,62706283.86831925,0.21027832791921208,0.4,58968860.77425385,0.21027832791921208,,,-41.6%,-33.6%,124001305.58759302,,0.9,115407722.09855165,,,,-38.2%,-27.0%,138117320.9658601,,1.5,124483853.59632729,,,,-35.9%,-21.0%,73671184.88459273,,1.6,65504109.622463554,,,,-38.0%,-24.8%,50330120.70300029,,0.1,48375597.068024196,,,,-40.0%,-29.9%,69058660.48293005,,1.5,62401409.439780794,,,,-35.4%,-19.2%,69058660.48293005,,1.5,62241926.79816376,,,,-35.9%,-21.0%
-1770,Rouen,49023498.41898596,0.0769670700485124,2.5,66619567.674024835,0.0769670700485124,,,30.0%,25.3%,32609788.676224675,0.0962692966611852,3.3,40550786.40914294,0.0962692966611852,,,53.9%,47.8%,16413709.742761288,0.05504149228340543,1.3,25326696.29332992,0.05504149228340543,,,6.6%,3.6%,30513479.967916988,,2.0,45102103.30004735,,,,97.5%,93.3%,32102338.629373036,,3.1,45191803.93713323,,,,157.2%,145.3%,20786020.31468678,,3.0,28680748.003553424,,,,126.8%,119.7%,9727459.653230209,,0.1,15687403.044739531,,,,71.2%,70.8%,16051169.314686518,,3.1,22595901.968566574,,,,157.2%,145.3%,16051169.314686518,,3.1,22595901.968566574,,,,157.2%,145.3%
-1770,Bordeaux,213694561.32338905,0.33550123513815977,3.7,102851568.04906753,0.33550123513815977,,,-49.2%,-57.2%,120965561.67024802,0.3571096291927337,4.2,40153911.695268184,0.3571096291927337,,,-38.5%,-53.8%,92728999.65314104,0.3109560604425327,3.2,59329196.16813666,0.3109560604425327,,,-56.9%,-60.6%,92374263.95316303,,2.2,48327920.251229994,,,,-53.2%,-55.5%,66916100.588454366,,3.0,21384490.68153178,,,,-46.2%,-38.5%,46825406.99482773,,2.9,16056685.280039357,,,,-47.7%,-40.4%,45548856.9583353,,1.9,31672600.764338035,,,,-53.5%,-55.1%,33458050.294227183,,3.0,11067835.94097283,,,,-47.0%,-41.8%,33458050.294227183,,3.0,10692245.340765946,,,,-46.2%,-38.5%
-1770,Nantes,49078708.3759675,0.07705374988090738,1.2,35281462.11690149,0.07705374988090738,,,-41.9%,-38.6%,31402321.577535108,0.09270466122344877,1.1,15071977.894141765,0.09270466122344877,,,-48.6%,-46.3%,17676386.798432395,0.059275734907733836,0.6,16699099.56715334,0.059275734907733836,,,-24.4%,13.7%,25811000.358326323,,0.6,19970516.376713756,,,,-23.1%,6.9%,27769979.1473788,,-0.2,9230119.317150965,,,,-30.2%,53.9%,16681840.624508172,,0.0,6862111.9102567,,,,-34.6%,31.5%,9129159.733818153,,0.6,11169788.270930488,,,,-6.7%,42.0%,13884989.5736894,,-0.1,4663808.070696755,,,,-31.5%,56.8%,13884989.5736894,,-0.2,4615059.6585754985,,,,-30.2%,53.9%
-1770,Bayonne,14311781.78460992,0.022469549229650436,0.1,18148834.108221862,0.022469549229650436,,,22.6%,40.3%,5648601.76058723,0.01667557321545393,0.3,6619165.311582235,0.01667557321545393,,,13.4%,23.8%,8663180.02402269,0.02905098018150885,-0.4,11327335.775695983,0.02905098018150885,,,29.2%,49.7%,12634141.669589087,,0.3,16310795.704026746,,,,31.5%,49.0%,9074784.10517896,,0.5,11086928.772435987,,,,29.0%,37.4%,4564002.05259678,,0.4,5602201.99756737,,,,28.9%,36.9%,8070139.616992308,,0.2,10532017.665642763,,,,31.3%,52.7%,4537392.05258948,,0.5,5506511.9011617,,,,30.1%,37.3%,4537392.05258948,,0.5,5543464.386217993,,,,29.0%,37.4%
-1770,La Rochelle,10849680.535732154,0.017034037731470233,-0.7,13634017.792166917,0.017034037731470233,,,47.4%,42.5%,4675885.09933538,0.013803958506168631,-0.5,6092632.982181558,0.013803958506168631,,,149.9%,144.1%,6173795.436396774,0.02070311460342599,-0.8,7501183.887087909,0.02070311460342599,,,-0.4%,-1.6%,7075367.338507866,,-1.3,9898932.56651135,,,,44.1%,34.1%,4327096.426158779,,1.8,4773060.057997743,,,,8.1%,-17.7%,2830310.11217157,,-1.0,3867419.681634663,,,,99.7%,86.6%,4245057.226336296,,-1.4,5925316.010673673,,,,7.4%,2.2%,2163548.2130793897,,1.8,2353912.3191079902,,,,9.3%,-17.2%,2163548.2130793897,,1.8,2386530.028998875,,,,8.1%,-17.7%
-1778,Marseille,112736817.52331236,0.17881688163542112,1.1,151883875.13012278,0.17881688163542112,174845795.9777706,164928744.66959053,-39.5%,-30.6%,64536603.70214123,0.1823710037737475,1.8,89802610.07332301,0.1823710037737475,100097670.45521864,93088365.95813684,-40.0%,-29.8%,48200213.821171135,0.17426956445912495,0.4,60990890.343249224,0.17426956445912495,77139194.18281154,73606200.7747888,-41.6%,-33.6%,85929853.85705909,,0.9,123964580.471186,,141530920.68533987,130940890.46499817,-38.2%,-27.0%,95421751.18880251,,1.5,140037405.60475582,,147090038.77759284,136014241.18102998,-35.9%,-21.0%,50264762.644664966,,1.6,74443386.01642384,,81617218.10167657,74808234.59118511,-38.0%,-24.8%,35665091.212394126,,0.1,48811969.62126154,,62182994.59165667,58038653.355836794,-40.0%,-29.9%,47710875.594401255,,1.5,70577197.22677274,,75976831.23063539,70206035.80665484,-35.4%,-19.2%,47710875.594401255,,1.5,70018702.80237779,,73545019.38879654,68007120.59051462,-35.9%,-21.0%
-1778,Rouen,,0.0,2.5,81640292.49517828,0.0,68794498.14971642,76073631.89733402,30.0%,25.3%,,0.0,3.3,52896996.85104248,0.0,43782111.050780356,49525595.71136038,53.9%,47.8%,,0.0,1.3,28016659.636323668,0.0,24538824.212988015,26339286.86890366,6.6%,3.6%,,,2.0,52886875.9316169,,42004700.098776944,45179072.72669235,97.5%,93.3%,,,3.1,57982220.02159426,,43920752.317074895,53209905.798259325,157.2%,145.3%,,,3.0,36545793.73597942,,29049800.864100367,32920886.456597112,126.8%,119.7%,,,0.1,15824444.33499727,,12880034.384078337,12938366.834010359,71.2%,70.8%,,,3.1,28991110.010797076,,21960376.158537485,26604952.899129804,157.2%,145.3%,,,3.1,28991110.010797076,,21960376.158537485,26604952.899129804,157.2%,145.3%
-1778,Bordeaux,200484755.88645342,0.31799779034600617,3.7,138351966.67841172,0.31799779034600617,144989596.8430843,197612452.66071984,-49.2%,-57.2%,132324431.2604504,0.3739294906830977,4.2,55991626.19124359,0.3739294906830977,63768621.08132797,148670196.62011647,-38.5%,-53.8%,68160324.62600303,0.24643604549216305,3.2,76449070.29472654,0.24643604549216305,82348426.51801594,80183409.20516035,-56.9%,-60.6%,44156878.57935423,,2.2,57800124.15212804,,59752045.09488977,59142715.53682224,-53.2%,-55.5%,26129085.039341416,,3.0,27129996.08248795,,26043135.121919703,64805601.01264167,-46.2%,-38.5%,17200016.706055395,,2.9,20288859.014650613,,24050566.94006823,48219583.21676385,-47.7%,-40.4%,26956861.87329883,,1.9,36840093.188883595,,36042319.95912893,26537613.42870425,-53.5%,-55.1%,13064542.519670708,,3.0,14120485.985511314,,14791576.834998624,37961723.96166044,-47.0%,-41.8%,13064542.519670708,,3.0,13564998.041244142,,13021567.560959874,32402800.506319854,-46.2%,-38.5%
-1778,Nantes,70481106.37826885,0.11179321834386767,1.2,38774384.37581105,0.11179321834386767,50423566.07679903,53709521.25223945,-41.9%,-38.6%,28386346.565855905,0.08021566397540146,1.1,16425429.62877951,0.08021566397540146,18806467.887118552,21352363.436324812,-48.6%,-46.3%,42094759.81241295,0.1521950812446093,0.6,17527571.01290223,0.1521950812446093,18814741.879559807,7528087.321385088,-24.4%,13.7%,42578390.168815106,,0.6,20875424.129830446,,23378690.61556277,18208473.88163562,-23.1%,6.9%,14593367.671155874,,-0.2,9084415.148682429,,8171709.6649671355,19571222.083967958,-30.2%,53.9%,11089341.658675758,,0.0,6874608.776183582,,6882651.103821548,9049478.8445156,-34.6%,31.5%,31489048.51013935,,0.6,11731252.067642799,,11620390.655451072,4020075.596186619,-6.7%,42.0%,7296683.835577937,,-0.1,4608850.417294187,,4242657.416387997,8190311.876012514,-31.5%,56.8%,7296683.835577937,,-0.2,4542207.574341222,,4085854.83248356,9785611.04198396,-30.2%,53.9%
-1778,Bayonne,14547533.153390469,0.02307448951571892,0.1,18290544.383046146,0.02307448951571892,14776672.367445555,10689280.526706357,22.6%,40.3%,5328097.792025309,0.01505642514163019,0.3,6765028.0045023225,0.01505642514163019,5307511.634711625,4487971.703967477,13.4%,23.8%,9219435.36136516,0.03333319206726133,-0.4,10968808.977858964,0.03333319206726133,9363891.54997481,6336812.347585454,29.2%,49.7%,13431676.293333624,,0.3,16743983.387470536,,13448884.788104735,9831404.081788337,31.5%,49.0%,8560296.171448318,,0.5,11546587.750334142,,8910181.941764489,7716155.250856027,29.0%,37.4%,4488681.835764159,,0.4,5781037.525066523,,4450911.725909257,3929630.9857443995,28.9%,36.9%,8942994.457569463,,0.2,10660617.057248559,,8946373.878563719,5999512.9306731,31.3%,52.7%,4280148.085724159,,0.5,5716069.284299241,,4431779.237787478,3954884.8428896423,30.1%,37.3%,4280148.085724159,,0.5,5773293.87516708,,4455090.970882221,3858077.625428006,29.0%,37.4%
-1778,La Rochelle,16436976.728661306,0.026071420026784184,-0.7,12856699.889415823,0.026071420026784184,14443456.78880625,26184560.56013426,47.4%,42.5%,8974251.512137672,0.02535992231540869,-0.5,5839446.075741326,0.02535992231540869,6403344.387959242,10225471.937832491,149.9%,144.1%,7462725.216523634,0.026981744894054152,-0.8,7021300.091236005,0.026981744894054152,8063701.081621433,13902190.956794696,-0.4%,-1.6%,9318384.633708397,,-1.3,8941003.156234205,,10430766.173895163,23448054.648448296,44.1%,34.1%,4425934.879527943,,1.8,5531504.76631257,,6615058.225683728,20757276.476155713,8.1%,-17.7%,4030261.589664162,,-1.0,3580788.9447512003,,4038878.47598728,8931048.325343065,99.7%,86.6%,5288123.044044235,,-1.4,5314538.833033563,,6251117.147162967,13210018.823269624,7.4%,2.2%,2212967.4397639716,,1.8,2723926.089214877,,3155578.242619608,9683722.403721113,9.3%,-17.2%,2212967.4397639716,,1.8,2765752.38315629,,3307529.1128418637,10378638.238077836,8.1%,-17.7%
+1764,Marseille,170896325.58873504,0.30554280417795493,1.1,129630017.20397691,0.30554280417795493,,,-39.5%,-30.6%,85098107.90470757,0.36534786537439623,1.8,69802319.03211632,0.36534786537439623,,,-40.0%,-29.8%,85798217.6840275,0.26286468712892475,0.4,57496453.98762116,0.26286468712892475,,,-41.6%,-33.6%,142139358.7521294,,0.9,109379972.44649549,,,,-38.2%,-27.0%,131199525.23608553,,1.5,113963230.08743326,,,,-35.9%,-21.0%,70510017.87171552,,1.6,59511427.760278195,,,,-38.0%,-24.8%,71629340.88041389,,0.1,48050879.67104851,,,,-40.0%,-29.9%,65599762.61804277,,1.5,56897330.75458553,,,,-35.4%,-19.2%,65599762.61804277,,1.5,56981615.04371673,,,,-35.9%,-21.0%
+1764,Rouen,50161964.588806435,0.08968377330957358,2.5,57197197.94940773,0.08968377330957358,,,30.0%,25.3%,26470996.890193116,0.11364673605897337,3.3,33221977.479261473,0.11364673605897337,,,53.9%,47.8%,23690967.698613316,0.07258331210109495,1.3,23480113.06532652,0.07258331210109495,,,6.6%,3.6%,34558337.86020608,,2.0,40025195.0103482,,,,97.5%,93.3%,28335153.801840406,,3.1,37487226.13706798,,,,157.2%,145.3%,18982903.0009202,,3.0,23914168.22083972,,,,126.8%,119.7%,15575434.859285884,,0.1,15585401.47252588,,,,71.2%,70.8%,14167576.900920203,,3.1,18743613.068533953,,,,157.2%,145.3%,14167576.900920203,,3.1,18743613.068533953,,,,157.2%,145.3%
+1764,Bordeaux,,0.0,3.7,82343647.83047377,0.0,,,-49.2%,-57.2%,,0.0,4.2,31291864.675581228,0.0,,,-38.5%,-53.8%,68010327.70630482,0.20836695675767633,3.2,49055833.17360021,0.20836695675767633,,,-56.9%,-60.6%,,,2.2,42257140.66984378,,,,-53.2%,-55.5%,,,3.0,17888988.95960624,,,,-46.2%,-38.5%,,,2.9,13472698.720779458,,,,-47.7%,-40.4%,33894679.10345651,,1.9,28278474.749479115,,,,-53.5%,-55.1%,,,3.0,9219821.533700708,,,,-47.0%,-41.8%,,,3.0,8944494.47980323,,,,-46.2%,-38.5%
+1764,Nantes,42213765.42899639,0.07547331529599705,1.2,32869857.570511963,0.07547331529599705,,,-41.9%,-38.6%,18930458.92857633,0.08127328480508371,1.1,14130592.794768315,0.08127328480508371,,,-48.6%,-46.3%,23283306.50042006,0.07133433821550313,0.6,16103546.931119539,0.07133433821550313,,,-24.4%,13.7%,21095358.110057916,,0.6,19317671.85564252,,,,-23.1%,6.9%,6621347.041361558,,-0.2,9340929.018730896,,,,-30.2%,53.9%,7202041.48135166,,0.0,6852754.171214163,,,,-34.6%,31.5%,13893316.628706258,,0.6,10766396.54833146,,,,-6.7%,42.0%,3310673.520680779,,-0.1,4705455.948954298,,,,-31.5%,56.8%,3310673.520680779,,-0.2,4670464.509365455,,,,-30.2%,53.9%
+1764,Bayonne,20355339.127839807,0.036392984902908806,0.1,18043272.387313187,0.036392984902908806,,,22.6%,40.3%,7915937.524806063,0.03398513725315142,0.3,6511835.92320546,0.03398513725315142,,,13.4%,23.8%,12439401.603033744,0.038111274321508924,-0.4,11603900.610996615,0.038111274321508924,,,29.2%,49.7%,17378046.251813967,,0.3,15993275.589570442,,,,31.5%,49.0%,13107959.202115284,,0.5,10754233.336216584,,,,29.0%,37.4%,6643853.751051952,,0.4,5471715.342063995,,,,28.9%,36.9%,10734192.500762014,,0.2,10436587.189108448,,,,31.3%,52.7%,6553979.601057642,,0.5,5354401.155010062,,,,30.1%,37.3%,6553979.601057642,,0.5,5377116.668108282,,,,29.0%,37.4%
+1764,La Rochelle,,0.0,-0.7,14247695.304850005,0.0,,,47.4%,42.5%,8847346.48137101,0.03798391328296222,-0.5,6289701.585218914,0.03798391328296222,,,149.9%,144.1%,,0.0,-0.8,7882500.730927576,0.0,,,-0.4%,-1.6%,,,-1.3,10684149.441009328,,,,44.1%,34.1%,,,1.8,4273287.4271529,,,,8.1%,-17.7%,4220042.2111123195,,-1.0,4097351.640722254,,,,99.7%,86.6%,,,-1.4,6429037.612353454,,,,7.4%,2.2%,1375003.63684811,,1.8,2109776.7577326884,,,,9.3%,-17.2%,,,1.8,2136643.7135764537,,,,8.1%,-17.7%
 1768,Marseille,164926838.7412307,0.31482249688755964,1.1,135632717.00096756,0.31482249688755964,,,-39.5%,-30.6%,93173015.27424042,0.4032096076457822,1.8,75012295.13291575,0.4032096076457822,,,-40.0%,-29.8%,71753823.46699028,0.24506580394367183,0.4,58473915.90097418,0.24506580394367183,,,-41.6%,-33.6%,140109314.25881693,,0.9,113362439.35960846,,,,-38.2%,-27.0%,152201071.90395483,,1.5,120873268.55712348,,,,-35.9%,-21.0%,80911944.16220726,,1.6,63442334.45159452,,,,-38.0%,-24.8%,59197370.096609674,,0.1,48267114.84628458,,,,-40.0%,-29.9%,76100535.95197742,,1.5,60509964.33046587,,,,-35.4%,-19.2%,76100535.95197742,,1.5,60436634.27856163,,,,-35.9%,-21.0%
 1768,Rouen,56837509.56298819,0.10849493517283534,2.5,63317844.87448495,0.10849493517283534,,,30.0%,25.3%,34296141.229324356,0.1484177968067047,3.3,37943845.83810747,0.1484177968067047,,,53.9%,47.8%,22541368.333663836,0.07698709679521228,1.3,24695571.993065216,0.07698709679521228,,,6.6%,3.6%,37242187.90085967,,2.0,43342006.77992908,,,,97.5%,93.3%,33711399.49313058,,3.1,42462043.12414516,,,,157.2%,145.3%,23562545.846565913,,3.0,26994714.733516965,,,,126.8%,119.7%,13679642.054293754,,0.1,15653328.561341526,,,,71.2%,70.8%,16855699.74656529,,3.1,21231021.562072538,,,,157.2%,145.3%,16855699.74656529,,3.1,21231021.562072538,,,,157.2%,145.3%
 1768,Bordeaux,66384779.23459549,0.12671935091629236,3.7,95503065.56330805,0.12671935091629236,,,-49.2%,-57.2%,18740052.71038781,0.08109825874343904,4.2,36951243.17184196,0.08109825874343904,,,-38.5%,-53.8%,47644726.52420768,0.1627243350272871,3.2,55685551.892941676,0.1627243350272871,,,-56.9%,-60.6%,35251726.49073143,,2.2,46213135.91962074,,,,-53.2%,-55.5%,8492462.995171834,,3.0,20149357.66864328,,,,-46.2%,-38.5%,7466132.997967317,,2.9,15144518.244154556,,,,-47.7%,-40.4%,27785593.49276412,,1.9,30498218.96088058,,,,-53.5%,-55.1%,4246231.497585917,,3.0,10413961.797029953,,,,-47.0%,-41.8%,4246231.497585917,,3.0,10074678.834321693,,,,-46.2%,-38.5%
 1768,Nantes,,0.0,1.2,34458549.35938877,0.0,,,-41.9%,-38.6%,,0.0,1.1,14751413.130854536,0.0,,,-48.6%,-46.3%,20807669.969185553,0.07106587667121209,0.6,16498174.161290448,0.07106587667121209,,,-24.4%,13.7%,,,0.6,19750486.201915644,,,,-23.1%,6.9%,,,-0.2,9266909.051700285,,,,-30.2%,53.9%,,,0.0,6858991.244947235,,,,-34.6%,31.5%,12601053.588831801,,0.6,11033672.382599633,,,,-6.7%,42.0%,,,-0.1,4677649.576561498,,,,-31.5%,56.8%,,,-0.2,4633454.525850158,,,,-30.2%,53.9%
 1768,Bayonne,11292988.057834482,0.02155675040414174,0.1,18113578.42504632,0.02155675040414174,,,22.6%,40.3%,3063423.6555563197,0.013257077133052367,0.3,6583193.716685726,0.013257077133052367,,,13.4%,23.8%,8229564.402278162,0.028107001395937112,-0.4,11418783.787941737,0.028107001395937112,,,29.2%,49.7%,9726944.87556688,,0.3,16204261.349117355,,,,31.5%,49.0%,4506196.908521241,,0.5,10974902.145818278,,,,29.0%,37.4%,2253261.4542606203,,0.4,5558364.306959732,,,,28.9%,36.9%,7473683.421306259,,0.2,10500110.94306928,,,,31.3%,52.7%,2253098.4542606203,,0.5,5455334.144419736,,,,30.1%,37.3%,2253098.4542606203,,0.5,5487451.072909138,,,,29.0%,37.4%
 1768,La Rochelle,14133178.045252874,0.026978279794376586,-0.7,13835582.358648118,0.026978279794376586,,,47.4%,42.5%,7401081.66164242,0.03202844969824942,-0.5,6157626.7242230745,0.03202844969824942,,,149.9%,144.1%,6732096.383610455,0.022992595136547132,-0.8,7626194.567803408,0.022992595136547132,,,-0.4%,-1.6%,8756271.034269072,,-1.3,10154040.590578299,,,,44.1%,34.1%,6018883.26924892,,1.8,4600290.961375505,,,,8.1%,-17.7%,4497735.00851315,,-1.0,3942593.0120527786,,,,99.7%,86.6%,4258536.025755923,,-1.4,6088677.906814925,,,,7.4%,2.2%,3009441.63462446,,1.8,2269546.171312593,,,,9.3%,-17.2%,3009441.63462446,,1.8,2300145.480687756,,,,8.1%,-17.7%
+1779,Marseille,90291903.57251516,0.20376013258214512,1.1,153612440.7933101,0.20376013258214512,176345506.28260857,165362001.45477745,-39.5%,-30.6%,55490251.31357412,0.2665725853064757,1.8,91433345.35894154,0.2665725853064757,101524496.60622519,93750461.71235538,-40.0%,-29.8%,34801652.25894105,0.14811323426907122,0.4,61248471.16535608,0.14811323426907122,77458016.90817949,73537098.83127132,-41.6%,-33.6%,79140647.77318889,,0.9,125077864.62868634,,142500628.86935225,130780097.09506348,-38.2%,-27.0%,102940014.17608234,,1.5,142113532.64956164,,148502659.14541447,136358664.16750994,-35.9%,-21.0%,52189930.038640864,,1.6,75643360.58964512,,82627549.92907538,75084493.85753475,-38.0%,-24.8%,26950717.734548032,,0.1,48866792.23659989,,62359156.558853894,57759819.32036635,-40.0%,-29.9%,51470007.08804117,,1.5,71671774.74588919,,76862821.31902066,70520148.08549453,-35.4%,-19.2%,51470007.08804117,,1.5,71056766.32478069,,74251329.57270736,68179332.08375461,-35.9%,-21.0%
+1779,Rouen,,0.0,2.5,83741819.8791037,0.0,69575892.93601632,77947543.97032076,30.0%,25.3%,,0.0,3.3,54683963.307469286,0.0,44542710.77381611,51187056.97240697,53.9%,47.8%,,0.0,1.3,28372400.426361874,0.0,24592791.298147686,26647502.990666572,6.6%,3.6%,,,2.0,53950044.03043804,,42144055.2459274,45740949.74586173,97.5%,93.3%,,,3.1,59816945.83773864,,44357674.52356317,55072441.17285506,157.2%,145.3%,,,3.0,37669795.65942139,,29421170.032668803,33869978.66244605,126.8%,119.7%,,,0.1,15841658.457920758,,12726695.249483071,12788532.613416573,71.2%,70.8%,,,3.1,29908472.918869264,,22178837.26178162,27536220.586427476,157.2%,145.3%,,,3.1,29908472.918869264,,22178837.26178162,27536220.586427476,157.2%,145.3%
+1779,Bordeaux,,0.0,3.7,143576095.77537474,0.0,148999739.81361258,212586731.8177381,-49.2%,-57.2%,,0.0,4.2,58367687.053520694,0.0,66016816.20547878,172390360.97385,-38.5%,-53.8%,,0.0,3.2,78910569.24035726,0.0,84317114.47921404,82329520.29124191,-56.9%,-60.6%,,,2.2,59107842.09112683,,60608882.895763054,60220289.65405169,-53.2%,-55.5%,,,3.0,27949148.65203775,,26589126.775010683,74797746.79213855,-46.2%,-38.5%,,,2.9,20890933.20239731,,24690626.969456084,54253097.02768285,-47.7%,-40.4%,,,1.9,37542686.276755005,,36369102.10880846,25938875.665231332,-53.5%,-55.1%,,,3.0,14557037.825942894,,15169542.706599465,44202017.01065696,-47.0%,-41.8%,,,3.0,13974574.326018948,,13294563.387505364,37398873.39606814,-46.2%,-38.5%
+1779,Nantes,22056667.15688417,0.04977488840511077,1.2,39234642.81990041,0.04977488840511077,50619968.870515995,54113596.82785597,-41.9%,-38.6%,10201460.893932555,0.04900734345265581,1.1,16602941.93678063,0.04900734345265581,18682520.205591597,21495720.810988396,-48.6%,-46.3%,11855206.262951616,0.05045487293154576,0.6,17633979.049244344,0.05045487293154576,18747775.116534866,6727199.262725819,-24.4%,13.7%,15897082.733057199,,0.6,20991383.333202865,,23257664.55955144,17534140.526217647,-23.1%,6.9%,8994715.249724098,,-0.2,9066364.59980773,,7982517.167893568,21011279.875491913,-30.2%,53.9%,5834082.586980555,,0.0,6876172.483785134,,6751816.289133522,9147876.040960325,-34.6%,31.5%,10063000.146076644,,0.6,11803391.023798259,,11577124.8627218,3525308.757551912,-6.7%,42.0%,4497357.624862049,,-0.1,4602026.403295303,,4149935.1142116045,8651174.761348244,-31.5%,56.8%,4497357.624862049,,-0.2,4533182.299903864,,3991258.5839467766,10505639.937745938,-30.2%,53.9%
+1779,Bayonne,24440115.70968818,0.05515357435486517,0.1,18308335.79209495,0.05515357435486517,14677210.04630995,10218669.187906394,22.6%,40.3%,11005466.09027656,0.052869747004914244,0.3,6783485.40819015,0.052869747004914244,5244525.726529546,4340950.01493755,13.4%,23.8%,13434649.619411621,0.05717686596019535,-0.4,10924798.504557459,0.05717686596019535,9327826.251669448,6028136.249749942,29.2%,49.7%,23649179.7612923,,0.3,16798934.586122863,,13399251.833242377,9438429.736202536,31.5%,49.0%,20570532.67535212,,0.5,11605369.189743007,,8815320.584960494,7501415.967752952,29.0%,37.4%,10447293.337411059,,0.4,5803789.687281276,,4401068.014488259,3823247.3396802074,28.9%,36.9%,13201886.423881244,,0.2,10676801.99778875,,8953284.651384214,5728265.048364282,31.3%,52.7%,10285266.33767606,,0.5,5742818.582228176,,4383535.120441496,3853764.3408881365,30.1%,37.3%,10285266.33767606,,0.5,5802684.594871482,,4407660.292480239,3750707.9838764425,29.0%,37.4%
+1779,La Rochelle,8152645.954763791,0.018397931098039486,-0.7,12762704.461470867,0.018397931098039486,14323756.194300553,28147150.95118706,47.4%,42.5%,4113823.0753538106,0.019762614634658213,-0.5,5808546.650742046,0.019762614634658213,6335685.444153532,10756459.339887628,149.9%,144.1%,4038822.8794099805,0.01718892869966104,-0.8,6963514.76251986,0.01718892869966104,8013877.790099649,14864717.366910376,-0.4%,-1.6%,5463128.081237061,,-1.3,8827972.741297798,,10312704.610043915,25852491.17013149,44.1%,34.1%,3686881.1497998,,1.8,5634418.352002524,,6710862.368519427,24473648.652830258,8.1%,-17.7%,2622218.27422905,,-1.0,3546487.240091202,,3978499.0568799446,9746608.348580029,99.7%,86.6%,2840909.8070080103,,-1.4,5242758.381385613,,6194336.009043501,14465672.83868715,7.4%,2.2%,1843440.5748999,,1.8,2774092.568875678,,3198763.896758236,11293234.853183305,9.3%,-17.2%,1843440.5748999,,1.8,2817209.1760012666,,3355431.1842597253,12236824.326415801,8.1%,-17.7%
+1750,Marseille,151081185.75407392,0.32593167485033,1.1,110636770.00542016,0.32593167485033,,,-39.5%,-30.6%,75982636.59665269,0.3578414456779374,1.8,54256371.14871281,0.3578414456779374,,,-40.0%,-29.8%,75098549.15742122,0.29895880214543835,0.4,54202229.25990692,0.29895880214543835,,,-41.6%,-33.6%,132061740.59148782,,0.9,96511264.16046709,,,,-38.2%,-27.0%,130044152.91970532,,1.5,92743919.06843624,,,,-35.9%,-21.0%,66170875.756852664,,1.6,47574542.5293451,,,,-38.0%,-24.8%,65890864.83463517,,0.1,47301656.8492634,,,,-40.0%,-29.9%,65022076.45985266,,1.5,45869011.15660435,,,,-35.4%,-19.2%,65022076.45985266,,1.5,46371959.5342182,,,,-35.9%,-21.0%
+1750,Rouen,58474351.935568735,0.1261483576993546,2.5,40072363.207872786,0.1261483576993546,,,30.0%,25.3%,34308264.03838983,0.16157531973217487,3.3,20865074.64196076,0.16157531973217487,,,53.9%,47.8%,24166087.897178903,0.09620245359384604,1.3,19678138.533179555,0.09620245359384604,,,6.6%,3.6%,47099490.45446172,,2.0,30291375.835619796,,,,97.5%,93.3%,48778721.02002764,,3.1,24236604.306083847,,,,157.2%,145.3%,27801124.507392816,,3.0,15648516.100817258,,,,126.8%,119.7%,19298365.947068904,,0.1,15349969.573503748,,,,71.2%,70.8%,24389360.51001382,,3.1,12118302.153041901,,,,157.2%,145.3%,24389360.51001382,,3.1,12118302.153041901,,,,157.2%,145.3%
+1750,Bordeaux,58859614.518199995,0.12697949546271958,3.7,49008890.157591835,0.12697949546271958,,,-49.2%,-57.2%,25152870.00595,0.11845784470020476,4.2,17487986.355860375,0.11845784470020476,,,-38.5%,-53.8%,33706744.51225,0.13418272492164102,3.2,31478143.01833453,0.13418272492164102,,,-56.9%,-60.6%,32360989.41389,,2.2,30893807.994099647,,,,-53.2%,-55.5%,13315892.584279997,,3.0,11795649.546867425,,,,-46.2%,-38.5%,10678968.204940002,,2.9,8946467.156670624,,,,-47.7%,-40.4%,21682021.208949998,,1.9,21706571.96921062,,,,-53.5%,-55.1%,6657946.292139999,,3.0,6019984.666286526,,,,-47.0%,-41.8%,6657946.292139999,,3.0,5897824.773433785,,,,-46.2%,-38.5%
+1750,Nantes,35756157.6544666,0.07713776068386789,1.2,27864466.55694048,0.07713776068386789,,,-41.9%,-38.6%,19368854.402506195,0.09121793045048972,1.1,12156373.211797424,0.09121793045048972,,,-48.6%,-46.3%,16387303.251960404,0.06523599464392581,0.6,14795217.407584783,0.06523599464392581,,,-24.4%,13.7%,16502110.326686596,,0.6,17876161.15492603,,,,-23.1%,6.9%,9494923.185850594,,-0.2,9604685.992980381,,,,-30.2%,53.9%,7673076.002616197,,0.0,6830969.042744997,,,,-34.6%,31.5%,8829034.3240704,,0.6,9880897.108642116,,,,-6.7%,42.0%,4747461.592925297,,-0.1,4804086.416965626,,,,-31.5%,56.8%,4747461.592925297,,-0.2,4802342.996490199,,,,-30.2%,53.9%
+1750,Bayonne,16629982.379220197,0.03587632690687005,0.1,17799343.290435135,0.03587632690687005,,,22.6%,40.3%,7599680.990409998,0.035790819509667504,0.3,6268119.963809181,0.035790819509667504,,,13.4%,23.8%,9030301.388810199,0.03594860508625689,-0.4,12275763.910346668,0.03594860508625689,,,29.2%,49.7%,14152472.993200198,,0.3,15276225.385851352,,,,31.5%,49.0%,13623254.180799998,,0.5,10016252.173413295,,,,29.0%,37.4%,6811627.090399999,,0.4,5178943.858219288,,,,28.9%,36.9%,7340845.9028002,,0.2,10217265.24561748,,,,31.3%,52.7%,6811627.090399999,,0.5,5015616.55446026,,,,30.1%,37.3%,6811627.090399999,,0.5,5008126.086706638,,,,29.0%,37.4%
+1750,La Rochelle,21139169.508223407,0.04560412263361187,-0.7,15789185.657740965,0.04560412263361187,,,47.4%,42.5%,11434237.193970403,0.0538497234497791,-0.5,6774674.432811335,0.0538497234497791,,,149.9%,144.1%,9704932.314253004,0.038634234244522975,-0.8,8849332.312491441,0.038634234244522975,,,-0.4%,-1.6%,16262212.0072824,,-1.3,12767141.145479564,,,,44.1%,34.1%,3494207.387940801,,1.8,3301269.040980371,,,,8.1%,-17.7%,7578549.693970401,,-1.0,4688433.3946400415,,,,99.7%,86.6%,8683662.313312,,-1.4,7777255.171068647,,,,7.4%,2.2%,1747103.6939704006,,1.8,1634096.4555143467,,,,9.3%,-17.2%,1747103.6939704006,,1.8,1650634.5204901884,,,,8.1%,-17.7%
+1743,Marseille,128194438.10974611,0.31081663332592446,1.1,102210718.92636839,0.31081663332592446,,,-39.5%,-30.6%,64238856.881133206,0.33771264574799886,1.8,47834494.547690324,0.33771264574799886,,,-40.0%,-29.8%,63955581.22861291,0.287794654481292,0.4,52626585.44259682,0.287794654481292,,,-41.6%,-33.6%,111400675.93140121,,0.9,90656323.30001871,,,,-38.2%,-27.0%,102514428.9526298,,1.5,83665380.5525663,,,,-35.9%,-21.0%,56034306.568348326,,1.6,42536499.42578717,,,,-38.0%,-24.8%,55366369.36305288,,0.1,46931437.67467495,,,,-40.0%,-29.9%,51257214.4763149,,1.5,41184435.74716796,,,,-35.4%,-19.2%,51257214.4763149,,1.5,41832690.27628307,,,,-35.9%,-21.0%
+1743,Rouen,,0.0,2.5,33541312.724449933,0.0,,,30.0%,25.3%,,0.0,3.3,16535494.008618398,0.0,,,53.9%,47.8%,,0.0,1.3,18014654.13809418,0.0,,,6.6%,3.6%,,,2.0,26351890.117509488,,,,97.5%,93.3%,,,3.1,19487943.225297816,,,,157.2%,145.3%,,,3.0,12658495.794249749,,,,126.8%,119.7%,,,0.1,15233590.657033354,,,,71.2%,70.8%,,,3.1,9743971.61264889,,,,157.2%,145.3%,,,3.1,9743971.61264889,,,,157.2%,145.3%
+1743,Bordeaux,61082613.590605564,0.14809918894240223,3.7,37809179.28826319,0.14809918894240223,,,-49.2%,-57.2%,22053274.816009477,0.11593714687830374,4.2,13073563.689174838,0.11593714687830374,,,-38.5%,-53.8%,39029338.77459609,0.17562869184344032,3.2,25215543.19574546,0.17562869184344032,,,-56.9%,-60.6%,39163301.752728835,,2.2,26415395.10737786,,,,-53.2%,-55.5%,16038198.739381852,,3.0,9578332.159206722,,,,-46.2%,-38.5%,11291055.367959525,,2.9,7290378.203794275,,,,-47.7%,-40.4%,27872246.384769306,,1.9,19017738.574113443,,,,-53.5%,-55.1%,8019099.369690926,,3.0,4864428.455286106,,,,-47.0%,-41.8%,8019099.369690926,,3.0,4789166.079603421,,,,-46.2%,-38.5%
+1743,Nantes,40443761.38795564,0.09805880769085955,1.2,25655305.39457165,0.09805880769085955,,,-41.9%,-38.6%,22062462.899250045,0.11598544991561131,1.1,11275241.342898563,0.11598544991561131,,,-48.6%,-46.3%,18381298.488705598,0.08271427365447546,0.6,14181470.15236688,0.08271427365447546,,,-24.4%,13.7%,24729044.711199727,,0.6,17196259.869071037,,,,-23.1%,6.9%,18598105.724679545,,-0.2,9739344.333399437,,,,-30.2%,53.9%,12284609.430581493,,0.0,6820102.463149281,,,,-34.6%,31.5%,12444435.280618234,,0.6,9465844.79909767,,,,-6.7%,42.0%,9299052.862339772,,-0.1,4854174.231452817,,,,-31.5%,56.8%,9299052.862339772,,-0.2,4869672.166699727,,,,-30.2%,53.9%
+1743,Bayonne,,0.0,0.1,17678618.18227893,0.0,,,22.6%,40.3%,,0.0,0.3,6149704.174424137,0.0,,,13.4%,23.8%,,0.0,-0.4,12626145.536004044,0.0,,,29.2%,49.7%,,,0.3,14929847.633779537,,,,31.5%,49.0%,,,0.5,9666475.340512328,,,,29.0%,37.4%,,,0.4,5038486.007359001,,,,28.9%,36.9%,,,0.2,10109338.746473791,,,,31.3%,52.7%,,,0.5,4854349.463309146,,,,30.1%,37.3%,,,0.5,4833237.670256156,,,,29.0%,37.4%
+1743,La Rochelle,,0.0,-0.7,16621388.006162459,0.0,,,47.4%,42.5%,,0.0,-0.5,7031008.510858903,0.0,,,149.9%,144.1%,,0.0,-0.8,9376348.619935522,0.0,,,-0.4%,-1.6%,,,-1.3,13956306.94917137,,,,44.1%,34.1%,,,1.8,2901618.5978671545,,,,8.1%,-17.7%,,,-1.0,5015220.214614657,,,,99.7%,86.6%,,,-1.4,8553946.688734096,,,,7.4%,2.2%,,,1.8,1438130.444400133,,,,9.3%,-17.2%,,,1.8,1450809.29893359,,,,8.1%,-17.7%
+1749,Marseille,160025524.75081217,0.3416045824316386,1.1,109391799.73654263,0.3416045824316386,,,-39.5%,-30.6%,88233454.24000002,0.4103729640038772,1.8,53288695.96900149,0.4103729640038772,,,-40.0%,-29.8%,71792070.51081216,0.28326539366321657,0.4,53974281.451461434,0.28326539366321657,,,-41.6%,-33.6%,137854870.17080778,,0.9,95652243.56774089,,,,-38.2%,-27.0%,153302183.48,,1.5,91389029.38953409,,,,-35.9%,-21.0%,77816510.64,,1.6,46819839.92328914,,,,-38.0%,-24.8%,60038359.53080777,,0.1,47248590.12604264,,,,-40.0%,-29.9%,76651091.74,,1.5,45168495.66617413,,,,-35.4%,-19.2%,76651091.74,,1.5,45694514.69476695,,,,-35.9%,-21.0%
+1749,Rouen,,0.0,2.5,39066734.6134435,0.0,,,30.0%,25.3%,,0.0,3.3,20183244.243414413,0.0,,,53.9%,47.8%,,0.0,1.3,19431408.73791802,0.0,,,6.6%,3.6%,,,2.0,29694437.963990577,,,,97.5%,93.3%,,,3.1,23493210.891504105,,,,157.2%,145.3%,,,3.0,15181591.290410751,,,,126.8%,119.7%,,,0.1,15333289.737625958,,,,71.2%,70.8%,,,3.1,11746605.44575203,,,,157.2%,145.3%,,,3.1,11746605.44575203,,,,157.2%,145.3%
+1749,Bordeaux,67491695.93469042,0.14407371975985991,3.7,47225663.16775502,0.14407371975985991,,,-49.2%,-57.2%,29675317.522572573,0.1380196220854007,4.2,16776076.701086937,0.1380196220854007,,,-38.5%,-53.8%,37816378.41211784,0.14920967234414062,3.2,30496228.72477477,0.14920967234414062,,,-56.9%,-60.6%,39217018.244778186,,2.2,30210305.002134845,,,,-53.2%,-55.5%,18266356.929382782,,3.0,11449934.664596094,,,,-46.2%,-38.5%,14754875.312067341,,2.9,8688631.046891822,,,,-47.7%,-40.4%,24462142.93271085,,1.9,21300344.047358546,,,,-53.5%,-55.1%,9133178.464691391,,3.0,5839451.001617858,,,,-47.0%,-41.8%,9133178.464691391,,3.0,5724967.332298077,,,,-46.2%,-38.5%
+1749,Nantes,44409819.76721923,0.09480111351653768,1.2,27537590.737483077,0.09480111351653768,,,-41.9%,-38.6%,23862874.46869859,0.11098600422846013,1.1,12026401.91671214,0.11098600422846013,,,-48.6%,-46.3%,20546945.29852064,0.08107077156502228,0.6,14705939.200595971,0.08107077156502228,,,-24.4%,13.7%,33804773.50883924,,0.6,17777410.85467297,,,,-23.1%,6.9%,38162654.44913618,,-0.2,9623808.305130327,,,,-30.2%,53.9%,22541751.22611316,,0.0,6829415.614839677,,,,-34.6%,31.5%,11263022.282726085,,0.6,9820507.886438143,,,,-6.7%,42.0%,19081327.22456809,,-0.1,4811210.051227651,,,,-31.5%,56.8%,19081327.22456809,,-0.2,4811904.152565164,,,,-30.2%,53.9%
+1749,Bayonne,16263866.812155545,0.03471828284732422,0.1,17782046.502738193,0.03471828284732422,,,22.6%,40.3%,6552822.230642415,0.03047711442946252,0.3,6251064.834539488,0.03047711442946252,,,13.4%,23.8%,9711044.58151313,0.03831624922767872,-0.4,12325216.73820496,0.03831624922767872,,,29.2%,49.7%,13953927.831096992,,0.3,15226255.139730562,,,,31.5%,49.0%,11030525.061095228,,0.5,9965519.645166337,,,,29.0%,37.4%,5515262.530547614,,0.4,5158641.2323296,,,,28.9%,36.9%,8438665.300549379,,0.2,10201776.91582379,,,,31.3%,52.7%,5515262.530547614,,0.5,4992254.468475567,,,,30.1%,37.3%,5515262.530547614,,0.5,4982759.822583169,,,,29.0%,37.4%
+1749,La Rochelle,23321457.508742854,0.04978403768009436,-0.7,15905470.67141364,0.04978403768009436,,,47.4%,42.5%,10665813.021295529,0.04960659582877273,-0.5,6810713.317771388,0.04960659582877273,,,149.9%,144.1%,12655644.487447327,0.0499345692677659,-0.8,8922766.719401607,0.0499345692677659,,,-0.4%,-1.6%,17928852.572391655,,-1.3,12930607.357203852,,,,44.1%,34.1%,3997752.767720057,,1.8,3240970.814418303,,,,8.1%,-17.7%,7697792.48644573,,-1.0,4733780.0282900985,,,,99.7%,86.6%,10231060.085945927,,-1.4,7883736.310985925,,,,7.4%,2.2%,1998876.3838600286,,1.8,1604545.5791235955,,,,9.3%,-17.2%,1998876.3838600286,,1.8,1620485.4072091542,,,,8.1%,-17.7%
+1754,Marseille,,0.0,1.1,115759960.84636731,0.0,,,-39.5%,-30.6%,74212763.01663025,0.29940464312969123,1.8,58306013.064919606,0.29940464312969123,,,-40.0%,-29.8%,,0.0,0.4,55123688.08120715,0.0,,,-41.6%,-33.6%,,,0.9,100025188.2149806,,,,-38.2%,-27.0%,,,1.5,98367347.32771826,,,,-35.9%,-21.0%,60963457.2636041,,1.6,50716982.47076674,,,,-38.0%,-24.8%,,,0.1,47514520.42486865,,,,-40.0%,-29.9%,56397374.95040833,,1.5,48781413.68233134,,,,-35.4%,-19.2%,,,1.5,49183673.66385903,,,,-35.9%,-21.0%
+1754,Rouen,,0.0,2.5,44360489.120365426,0.0,,,30.0%,25.3%,,0.0,3.3,23830645.72569081,0.0,,,53.9%,47.8%,,0.0,1.3,20696786.488361266,0.0,,,6.6%,3.6%,,,2.0,32801564.52707814,,,,97.5%,93.3%,,,3.1,27452971.139151543,,,,157.2%,145.3%,,,3.0,17664307.796258196,,,,126.8%,119.7%,,,0.1,15416870.56083955,,,,71.2%,70.8%,,,3.1,13726485.569575746,,,,157.2%,145.3%,,,3.1,13726485.569575746,,,,157.2%,145.3%
+1754,Bordeaux,121966756.17763133,0.22341063559300056,3.7,56841048.13453862,0.22341063559300056,,,-49.2%,-57.2%,31255901.0252594,0.12609909012642048,4.2,20650825.48198282,0.12609909012642048,,,-38.5%,-53.8%,90710855.15237193,0.30433443725196857,3.2,35732300.38388651,0.30433443725196857,,,-56.9%,-60.6%,66310170.35933566,,2.2,33785999.83990045,,,,-53.2%,-55.5%,14039651.849969631,,3.0,13286092.47791907,,,,-46.2%,-38.5%,11602374.678187165,,2.9,10056629.178974777,,,,-47.7%,-40.4%,54707795.6811485,,1.9,23410448.783815417,,,,-53.5%,-55.1%,7019825.9249848155,,3.0,6799685.88375158,,,,-47.0%,-41.8%,7019825.9249848155,,3.0,6643046.2389595695,,,,-46.2%,-38.5%
+1754,Nantes,,0.0,1.2,29211233.85355808,0.0,,,-41.9%,-38.6%,,0.0,1.1,12690457.224587822,0.0,,,-48.6%,-46.3%,23458883.695358895,0.07870443020291325,0.6,15157783.225556767,0.07870443020291325,,,-24.4%,13.7%,,,0.6,18276678.311546143,,,,-23.1%,6.9%,,,-0.2,9528575.946633369,,,,-30.2%,53.9%,,,0.0,6837186.288617744,,,,-34.6%,31.5%,13366967.626790376,,0.6,10126190.416033769,,,,-6.7%,42.0%,,,-0.1,4775697.198712083,,,,-31.5%,56.8%,,,-0.2,4764287.9733167,,,,-30.2%,53.9%
+1754,Bayonne,17289380.204127267,0.031669542926825174,0.1,17868698.8526713,0.031669542926825174,,,22.6%,40.3%,7119275.740170822,0.02872207051299327,0.3,6336807.076808006,0.02872207051299327,,,13.4%,23.8%,10170104.463956444,0.034120646461031474,-0.4,12079928.863853632,0.034120646461031474,,,29.2%,49.7%,14359334.10815467,,0.3,15477751.708460625,,,,31.5%,49.0%,11083195.916644104,,0.5,10221778.162544854,,,,29.0%,37.4%,5607412.158552832,,0.4,5260956.553784425,,,,28.9%,36.9%,8751921.949601838,,0.2,10279454.065760953,,,,31.3%,52.7%,5541597.958322052,,0.5,5110163.294220437,,,,30.1%,37.3%,5541597.958322052,,0.5,5110889.081272426,,,,29.0%,37.4%
+1754,La Rochelle,20361898.042909946,0.03729757784999354,-0.7,15332485.280570125,0.03729757784999354,,,47.4%,42.5%,10592659.154740712,0.04273512001310211,-0.5,6632415.826121904,0.04273512001310211,,,149.9%,144.1%,9769238.888169235,0.03277574458334592,-0.8,8561588.804606143,0.03277574458334592,,,-0.4%,-1.6%,17077246.642831936,,-1.3,12133681.780905012,,,,44.1%,34.1%,4919767.484134648,,1.8,3553891.09419421,,,,8.1%,-17.7%,8679417.712880714,,-1.0,4511349.369058378,,,,99.7%,86.6%,8397828.929951223,,-1.4,7365519.474447964,,,,7.4%,2.2%,2459883.742067324,,1.8,1757843.4972208354,,,,9.3%,-17.2%,2459883.742067324,,1.8,1776945.547097108,,,,8.1%,-17.7%
+1762,Marseille,91016133.9788189,0.26937428234471167,1.1,126729037.71574524,0.26937428234471167,182853827.62657115,128086211.235678,-39.5%,-30.6%,58356347.295732476,0.41624421375959253,1.8,67334641.18980262,0.41624421375959253,97430777.83477102,65765591.299879216,-40.0%,-29.8%,32659786.68308642,0.16521339150133738,0.4,57013867.504530095,0.16521339150133738,79956861.620314,57788367.86121784,-41.6%,-33.6%,83512926.84020147,,0.9,107441514.90168874,,157643389.61980617,104145575.32830685,-38.2%,-27.0%,104288919.31019527,,1.5,110657789.89028654,,182732380.68259,103320641.67319992,-35.9%,-21.0%,52798052.655100636,,1.6,57638275.2993673,,84009614.70777196,51568667.47874629,-38.0%,-24.8%,30714874.18510083,,0.1,47943125.62770454,,67180047.26231286,46982823.27483692,-40.0%,-29.9%,52144459.65509763,,1.5,55172719.42040281,,82864059.0109073,45845965.78151364,-35.4%,-19.2%,52144459.65509763,,1.5,55328894.94514316,,91366190.34129548,51660320.8365995,-35.9%,-21.0%
+1762,Rouen,,0.0,2.5,54362455.85886483,0.0,36467300.542462386,36467300.542462386,30.0%,25.3%,,0.0,3.3,31086193.475793235,0.0,15071634.416163156,15071634.416163156,53.9%,47.8%,,0.0,1.3,22895004.381712183,0.0,23011947.066501983,23011947.066501983,6.6%,3.6%,,,2.0,38463223.36600816,,18295718.552034076,18295718.552034076,97.5%,93.3%,,,3.1,35222851.804082,,10397579.847890459,10397579.847890459,157.2%,145.3%,,,3.0,22508344.243006617,,7661150.24855807,7661150.24855807,126.8%,119.7%,,,0.1,15551548.545931702,,11426949.070002558,11426949.070002558,71.2%,70.8%,,,3.1,17611425.902040966,,5198789.923945219,5198789.923945219,157.2%,145.3%,,,3.1,17611425.902040966,,5198789.923945219,5198789.923945219,157.2%,145.3%
+1762,Bordeaux,33747414.055872545,0.0998799338632211,3.7,76460387.98090042,0.0998799338632211,148463315.31931362,188668762.62064198,-49.2%,-57.2%,8980650.366498953,0.06405719213214907,4.2,28796031.373054177,0.06405719213214907,42635694.96261548,33539390.616728876,-38.5%,-53.8%,24766763.68937359,0.1252856016892668,3.2,46043117.39027221,0.1252856016892668,104681109.04113433,172501081.12841737,-56.9%,-60.6%,28325568.2249012,,2.2,40408007.94237175,,75435996.32097644,89957894.60779068,-53.2%,-55.5%,6058120.5331324935,,3.0,16855750.377483282,,24644373.649146445,10904777.835518971,-46.2%,-38.5%,5192312.342161528,,2.9,12707325.828232257,,15628073.886994217,7695786.162349344,-47.7%,-40.4%,23133255.88273967,,1.9,27229943.041507974,,57954808.63822073,99111763.79442379,-53.5%,-55.1%,3029060.2665662467,,3.0,8675125.80954947,,12451227.102048958,5452388.9177595535,-47.0%,-41.8%,3029060.2665662467,,3.0,8427875.188741745,,12322186.824573288,5452388.9177595535,-46.2%,-38.5%
+1762,Nantes,5938902.339939631,0.017576966695914225,1.2,32103193.619829528,0.017576966695914225,26427862.808711413,21302893.94157235,-41.9%,-38.6%,1557436.64375888,0.01110888568773051,1.1,13830050.280296886,0.01110888568773051,14209518.436152332,10293181.047618628,-48.6%,-46.3%,4381465.696180751,0.022164162137276466,0.6,15909787.280190114,0.022164162137276466,16561325.221866306,19440275.73272309,-24.4%,13.7%,5173412.64467358,,0.6,19104834.55915443,,11873550.92404873,7015456.287049794,-23.1%,6.9%,1863709.5964669008,,-0.2,9378160.42249017,,6589666.826356168,1128317.574236423,-30.2%,53.9%,931854.7982334504,,0.0,6849637.761500059,,5141343.087163501,1315306.339448622,-34.6%,31.5%,4241557.84644013,,0.6,10635196.422174022,,8727802.333007133,13999009.256193846,-6.7%,42.0%,931854.7982334504,,-0.1,4719421.059680653,,3294833.413178078,564158.7871182105,-31.5%,56.8%,931854.7982334504,,-0.2,4689080.2112450935,,3294833.413178078,564158.7871182105,-30.2%,53.9%
+1762,Bayonne,25897658.81175834,0.07664754535112511,0.1,18008221.766929317,0.07664754535112511,18069150.24073928,18069150.24073928,22.6%,40.3%,10309375.272833945,0.07353472250493583,0.3,6476447.605670589,0.07353472250493583,6578779.264683277,6578779.264683277,13.4%,23.8%,15588283.538924394,0.07885517490179726,-0.4,11697581.39050085,0.07885517490179726,11621221.42773093,11621221.42773093,29.2%,49.7%,23933280.85693584,,0.3,15888815.124934653,,15049809.959321465,15049809.959321465,31.5%,49.0%,16314871.413473248,,0.5,10645568.393269416,,8188742.370332776,8188742.370332776,29.0%,37.4%,9150501.706736624,,0.4,5428898.720249463,,4493860.640866947,4493860.640866947,28.9%,36.9%,14782779.150199216,,0.2,10404969.572937602,,11044922.765369542,11044922.765369542,31.3%,52.7%,8157435.706736624,,0.5,5304637.122038086,,4094371.1851664092,4094371.1851664092,30.1%,37.3%,8157435.706736624,,0.5,5322784.196634699,,4094371.1851664092,4094371.1851664092,29.0%,37.4%
+1762,La Rochelle,4152304.1112779393,0.012289293020430768,-0.7,14458332.445805445,0.012289293020430768,21266727.731675316,13584850.161848653,47.4%,42.5%,1657889.8236691197,0.01182539823227845,-0.5,6356797.575334087,0.01182539823227845,10943494.883428385,7517352.750245811,149.9%,144.1%,2494414.2876088195,0.012618289527245013,-0.8,8013866.232286618,0.012618289527245013,10339433.361838326,6218068.076234282,-0.4%,-1.6%,3351031.7523052897,,-1.3,10959493.497999148,,16090098.282202514,12822289.043861156,44.1%,34.1%,1413327.42926282,,1.8,4118608.4582261858,,4751821.429373782,9602639.92708887,8.1%,-17.7%,869285.51485133,,-1.0,4176994.2950196248,,7824138.05587363,7488609.390159684,99.7%,86.6%,2481746.23745396,,-1.4,6606287.192430803,,8282060.691237678,5601582.5324442,7.4%,2.2%,706663.71463141,,1.8,2034160.628655465,,2375910.714686891,4801319.9635444265,9.3%,-17.2%,706663.71463141,,1.8,2059304.2291130961,,2375910.714686891,4801319.9635444265,8.1%,-17.7%
+1767,Marseille,155819227.45312315,0.29682941739939794,1.1,134106473.0574304,0.29682941739939794,,,-39.5%,-30.6%,86346788.65913217,0.3628936753606946,1.8,73674433.15216587,0.3628936753606946,,,-40.0%,-29.8%,69472438.79399098,0.24205941222801428,0.4,58228003.48809261,0.24205941222801428,,,-41.6%,-33.6%,128966281.18182853,,0.9,112353431.02572499,,,,-38.2%,-27.0%,135628413.29271185,,1.5,119107439.10255398,,,,-35.9%,-21.0%,73431204.5040921,,1.6,62435911.84405481,,,,-38.0%,-24.8%,55535076.677736424,,0.1,48212964.996261716,,,,-40.0%,-29.9%,67814206.64635593,,1.5,59585850.94170867,,,,-35.4%,-19.2%,67814206.64635593,,1.5,59553719.551277086,,,,-35.9%,-21.0%
+1767,Rouen,72615731.36479175,0.13833007381278928,2.5,61728863.58548295,0.13833007381278928,,,30.0%,25.3%,46901043.470863774,0.19711320256023665,3.3,36703914.135292016,0.19711320256023665,,,53.9%,47.8%,25714687.893927973,0.08959642622722243,1.3,24385932.267161176,0.08959642622722243,,,6.6%,3.6%,54385603.323712915,,2.0,42487886.27316337,,,,97.5%,93.3%,62104164.38109187,,3.1,41159632.81825231,,,,157.2%,145.3%,37322380.098282464,,3.0,26189238.86745259,,,,126.8%,119.7%,17063223.22543045,,0.1,15636319.084541326,,,,71.2%,70.8%,31052082.190545935,,3.1,20579816.409126114,,,,157.2%,145.3%,31052082.190545935,,3.1,20579816.409126114,,,,157.2%,145.3%
+1767,Bordeaux,83484634.5525411,0.15903490115484933,3.7,92028111.45646977,0.15903490115484933,,,-49.2%,-57.2%,28239948.84003925,0.11868534992095474,4.2,35447013.56903809,0.11868534992095474,,,-38.5%,-53.8%,55244685.71250185,0.1924863497586935,3.2,53948523.14519771,0.1924863497586935,,,-56.9%,-60.6%,41453650.0629854,,2.2,45190703.95930138,,,,-53.2%,-55.5%,6769393.804244387,,3.0,19558806.653492995,,,,-46.2%,-38.5%,7100075.402736494,,2.9,14708055.045870142,,,,-47.7%,-40.4%,34353574.660248905,,1.9,29927459.647699237,,,,-53.5%,-55.1%,3384696.9021221935,,3.0,10101656.900729105,,,,-47.0%,-41.8%,3384696.9021221935,,3.0,9779403.326746617,,,,-46.2%,-38.5%
+1767,Nantes,34526296.0226709,0.06577121771734944,1.2,34054318.8841293,0.06577121771734944,,,-41.9%,-38.6%,15138961.52786769,0.06362521959768364,1.1,14593696.66102005,0.06362521959768364,,,-48.6%,-46.3%,19387334.494803213,0.06755033901135889,0.6,16398619.86836373,0.06755033901135889,,,-24.4%,13.7%,17197466.436339036,,0.6,19641381.87992608,,,,-23.1%,6.9%,5215632.42922733,,-0.2,9285358.871682039,,,,-30.2%,53.9%,5241694.204087175,,0.0,6857431.444524254,,,,-34.6%,31.5%,11955772.232251858,,0.6,10966237.727030123,,,,-6.7%,42.0%,2607816.214613665,,-0.1,4684585.726725589,,,,-31.5%,56.8%,2607816.214613665,,-0.2,4642679.435841028,,,,-30.2%,53.9%
+1767,Bayonne,17957913.890987836,0.03420911016629248,0.1,18095976.2744873,0.03420911016629248,,,22.6%,40.3%,6924296.990026709,0.02910106586499012,0.3,6565281.293105168,0.02910106586499012,,,13.4%,23.8%,11033616.900961125,0.038443890385301174,-0.4,11464784.277454263,0.038443890385301174,,,29.2%,49.7%,15797545.245239848,,0.3,16151255.393302448,,,,31.5%,49.0%,11510302.465596821,,0.5,10919314.035267485,,,,29.0%,37.4%,5768971.23279611,,0.4,5536574.26748987,,,,28.9%,36.9%,10028574.012443738,,0.2,10484193.848108243,,,,31.3%,52.7%,5755151.232798411,,0.5,5429923.911405836,,,,30.1%,37.3%,5755151.232798411,,0.5,5459657.017633752,,,,29.0%,37.4%
+1767,La Rochelle,12283463.360102393,0.023399508086528922,-0.7,13937479.373390945,0.023399508086528922,,,47.4%,42.5%,6113870.114851836,0.02569504704355723,-0.5,6190383.132422773,0.02569504704355723,,,149.9%,144.1%,6169593.245250556,0.021496411246764074,-0.8,7689479.011792183,0.021496411246764074,,,-0.4%,-1.6%,8123421.203556097,,-1.3,10284049.535425298,,,,44.1%,34.1%,4133765.6479212395,,1.8,4516265.883989482,,,,8.1%,-17.7%,3621021.481952576,,-1.0,3980725.8606826193,,,,99.7%,86.6%,4502399.721603521,,-1.4,6172040.140642409,,,,7.4%,2.2%,2066882.8239606197,,1.8,2228503.8704464235,,,,9.3%,-17.2%,2066882.8239606197,,1.8,2258132.941994761,,,,8.1%,-17.7%
+1740,Marseille,109641515.25605261,0.28523013361346705,1.1,98798939.01304728,0.28523013361346705,,,-39.5%,-30.6%,49485692.83599193,0.2818418790151906,1.8,45320452.513854876,0.2818418790151906,,,-40.0%,-29.8%,60155822.42006069,0.28807907961719126,0.4,51965409.54808185,0.28807907961719126,,,-41.6%,-33.6%,92192853.92166692,,0.9,88257083.50985904,,,,-38.2%,-27.0%,83528473.58130832,,1.5,80051901.7628709,,,,-35.9%,-21.0%,42770046.7452086,,1.6,40544099.34903338,,,,-38.0%,-24.8%,49422807.176458314,,0.1,46773660.66720775,,,,-40.0%,-29.9%,41764236.79065416,,1.5,39326189.44957211,,,,-35.4%,-19.2%,41764236.79065416,,1.5,40025950.88143537,,,,-35.9%,-21.0%
+1740,Rouen,,0.0,2.5,31078963.58284068,0.0,,,30.0%,25.3%,,0.0,3.3,14966845.430650495,0.0,,,53.9%,47.8%,,0.0,1.3,17345497.041538548,0.0,,,6.6%,3.6%,,,2.0,24824476.65349712,,,,97.5%,93.3%,,,3.1,17749160.636562288,,,,157.2%,145.3%,,,3.0,11558846.722448621,,,,126.8%,119.7%,,,0.1,15183984.477056904,,,,71.2%,70.8%,,,3.1,8874580.31828119,,,,157.2%,145.3%,,,3.1,8874580.31828119,,,,157.2%,145.3%
+1740,Bordeaux,34215493.87234497,0.0890108994395804,3.7,33830377.422714256,0.0890108994395804,,,-49.2%,-57.2%,15215823.9939525,0.08666053114448698,4.2,11541062.126220552,0.08666053114448698,,,-38.5%,-53.8%,18999669.878392473,0.09098715953673855,3.2,22928699.587623805,0.09098715953673855,,,-56.9%,-60.6%,21168690.995450623,,2.2,24700634.624042217,,,,-53.2%,-55.5%,6814368.990277499,,3.0,8760589.604626507,,,,-46.2%,-38.5%,7509973.244910998,,2.9,6678046.063462188,,,,-47.7%,-40.4%,13658717.750539627,,1.9,17969872.69855383,,,,-53.5%,-55.1%,3407184.4951387495,,3.0,4439782.766523802,,,,-47.0%,-41.8%,3407184.4951387495,,3.0,4380294.802313276,,,,-46.2%,-38.5%
+1740,Nantes,40152182.6768143,0.10445507254286013,1.2,24762974.620542567,0.10445507254286013,,,-41.9%,-38.6%,15781864.300198868,0.08988436927563219,1.1,10917442.494525572,0.08988436927563219,,,-48.6%,-46.3%,24370318.37661544,0.11670655649738211,0.6,13926292.08946349,0.11670655649738211,,,-24.4%,13.7%,22862459.878206708,,0.6,16912847.951628882,,,,-23.1%,6.9%,5650909.661024557,,-0.2,9797631.450165277,,,,-30.2%,53.9%,6368852.277259383,,0.0,6815450.650953862,,,,-34.6%,31.5%,16493607.600947326,,0.6,9293345.749823222,,,,-6.7%,42.0%,2825454.8305122787,,-0.1,4875799.984690576,,,,-31.5%,56.8%,2825454.8305122787,,-0.2,4898815.725082655,,,,-30.2%,53.9%
+1740,Bayonne,,0.0,0.1,17627129.835701764,0.0,,,22.6%,40.3%,,0.0,0.3,6099641.854212352,0.0,,,13.4%,23.8%,,0.0,-0.4,12779354.09459814,0.0,,,29.2%,49.7%,,,0.3,14783814.750174012,,,,31.5%,49.0%,,,0.5,9520335.344774825,,,,29.0%,37.4%,,,0.4,4979462.002185,,,,28.9%,36.9%,,,0.2,10063434.23064838,,,,31.3%,52.7%,,,0.5,4786832.1540504815,,,,30.1%,37.3%,,,0.5,4760167.672387413,,,,29.0%,37.4%
+1740,La Rochelle,19592794.140117444,0.05097024860880286,-0.7,16991341.51241254,0.05097024860880286,,,47.4%,42.5%,9775962.24040329,0.05567822554588645,-0.5,7143813.949869218,0.05567822554588645,,,149.9%,144.1%,9816831.899714151,0.04701164051384077,-0.8,9611714.231449287,0.04701164051384077,,,-0.4%,-1.6%,16689691.98688759,,-1.3,14499275.657502744,,,,44.1%,34.1%,5596733.62152273,,1.8,2745509.3635243587,,,,8.1%,-17.7%,7754903.31077304,,-1.0,5162154.213606426,,,,99.7%,86.6%,8934788.67611455,,-1.4,8910124.325635679,,,,7.4%,2.2%,2798366.810761365,,1.8,1361511.7417657361,,,,9.3%,-17.2%,2798366.810761365,,1.8,1372754.6817621817,,,,8.1%,-17.7%
 1745,Marseille,78061061.12713285,0.2386145398142812,1.1,104550444.72581647,0.2386145398142812,142263813.640281,142263813.640281,-39.5%,-30.6%,35635165.03908121,0.24916357388115837,1.8,49587531.6205529,0.24916357388115837,71359559.20284958,71359559.20284958,-40.0%,-29.8%,42425896.08805164,0.23042051933614288,0.4,53072036.34599005,0.23042051933614288,66773055.283784635,66773055.283784635,-41.6%,-33.6%,70453930.43532729,,0.9,92291942.77212058,,126210843.43881693,126210843.43881693,-38.2%,-27.0%,61039145.42657339,,1.5,86164535.0383215,,116627186.09087758,116627186.09087758,-35.9%,-21.0%,30833885.413602903,,1.6,43918868.14109158,,61941297.8960274,61941297.8960274,-38.0%,-24.8%,39620045.021724395,,0.1,47036917.9099158,,59811182.7113564,59811182.7113564,-40.0%,-29.9%,30519572.713286694,,1.5,42471795.61319676,,54008006.00871136,54008006.00871136,-35.4%,-19.2%,30519572.713286694,,1.5,43082267.519160666,,58313593.04543868,58313593.04543868,-35.9%,-21.0%
 1745,Rouen,,0.0,2.5,35290331.77537218,0.0,,,30.0%,25.3%,,0.0,3.3,17671568.890882663,0.0,,,53.9%,47.8%,,0.0,1.3,18475039.748543214,0.0,,,6.6%,3.6%,,,2.0,27422026.771076854,,,,97.5%,93.3%,,,3.1,20740766.21326904,,,,157.2%,145.3%,,,3.0,13449118.894675491,,,,126.8%,119.7%,,,0.1,15266751.446439963,,,,71.2%,70.8%,,,3.1,10370383.1066345,,,,157.2%,145.3%,,,3.1,10370383.1066345,,,,157.2%,145.3%
 1745,Bordeaux,37745629.06151001,0.11537962434105566,3.7,40718414.15256343,0.11537962434105566,92324456.06549062,92324456.06549062,-49.2%,-57.2%,17239608.62123866,0.12054055289681928,4.2,14206686.348177213,0.12054055289681928,28139990.07261765,28139990.07261765,-38.5%,-53.8%,20506020.440271348,0.11137084457941678,3.2,26865458.954643883,0.11137084457941678,66242403.712921284,66242403.712921284,-56.9%,-60.6%,21657644.99917772,,2.2,27624204.303609725,,62181209.71215899,62181209.71215899,-53.2%,-55.5%,8627111.452949341,,3.0,10165473.171481203,,30899499.35688929,30899499.35688929,-46.2%,-38.5%,7023151.476213921,,2.9,7729483.797608841,,15163705.527893873,15163705.527893873,-47.7%,-40.4%,14634493.5229638,,1.9,19750046.45586212,,47837542.50019447,47837542.50019447,-53.5%,-55.1%,4313555.726474671,,3.0,5169857.268447211,,15199661.614636486,15199661.614636486,-47.0%,-41.8%,4313555.726474671,,3.0,5082736.585740664,,15449749.67844286,15449749.67844286,-46.2%,-38.5%
 1745,Nantes,24058836.94309482,0.07354227860538251,1.2,26267985.803340096,0.07354227860538251,48784815.275516964,48784815.275516964,-41.9%,-38.6%,8151658.005209526,0.05699696463893038,1.1,11520264.991821565,0.05699696463893038,37014119.19466761,37014119.19466761,-48.6%,-46.3%,15907178.937885296,0.0863939426154572,0.6,14354181.242590673,0.0863939426154572,15988114.412381554,15988114.412381554,-24.4%,13.7%,10849648.965097541,,0.6,17387834.70050479,,32692221.746542986,32692221.746542986,-23.1%,6.9%,4835974.115174205,,-0.2,9700679.025397474,,76080470.33659746,76080470.33659746,-30.2%,53.9%,3581259.4177213027,,0.0,6823205.435059243,,29858154.607479136,29858154.607479136,-34.6%,31.5%,7268389.547376239,,0.6,9582619.326104969,,10058253.926657317,10058253.926657317,-6.7%,42.0%,2417987.0575871025,,-0.1,4839810.376274385,,38040235.1682965,38040235.1682965,-31.5%,56.8%,2417987.0575871025,,-0.2,4850339.512698745,,38040235.1682965,38040235.1682965,-30.2%,53.9%
 1745,Bayonne,,0.0,0.1,17713027.272906434,0.0,,,22.6%,40.3%,,0.0,0.3,6183307.11500524,0.0,,,13.4%,23.8%,,0.0,-0.4,12525028.295058211,0.0,,,29.2%,49.7%,,,0.3,15028003.399864292,,,,31.5%,49.0%,,,0.5,9765146.163203306,,,,29.0%,37.4%,,,0.4,5078223.523384173,,,,28.9%,36.9%,,,0.2,10140058.028254109,,,,31.3%,52.7%,,,0.5,4899889.243164407,,,,30.1%,37.3%,,,0.5,4882573.081601653,,,,29.0%,37.4%
 1745,La Rochelle,,0.0,-0.7,16379238.251932286,0.0,8962505.798370654,8962505.798370654,47.4%,42.5%,,0.0,-0.5,6956796.225198776,0.0,1939637.6990566887,1939637.6990566887,149.9%,144.1%,,0.0,-0.8,9222648.932210196,0.0,9159080.353659,9159080.353659,-0.4%,-1.6%,,,-1.3,13605671.56837739,,7287451.259583972,7287451.259583972,44.1%,34.1%,,,1.8,3010592.14499816,,1541042.0276513456,1541042.0276513456,8.1%,-17.7%,,,-1.0,4919595.125958445,,1377174.681624799,1377174.681624799,99.7%,86.6%,,,-1.4,8324440.550956841,,7608560.7243408635,7608560.7243408635,7.4%,2.2%,,,1.8,1491590.2625589059,,770521.0138256714,770521.0138256714,9.3%,-17.2%,,,1.8,1505296.0724990827,,770521.0138256714,770521.0138256714,8.1%,-17.7%
-1753,Marseille,,0.0,1.1,114457340.48269352,0.0,,,-39.5%,-30.6%,67731312.8675276,0.2791135659623957,1.8,57266111.566232726,0.2791135659623957,,,-40.0%,-29.8%,,0.0,0.4,54891865.07202258,0.0,,,-41.6%,-33.6%,,,0.9,99134891.13706559,,,,-38.2%,-27.0%,,,1.5,96930305.36341442,,,,-35.9%,-21.0%,58563002.97366647,,1.6,49912429.51435353,,,,-38.0%,-24.8%,,,0.1,47461214.89452758,,,,-40.0%,-29.9%,57727467.47049629,,1.5,48036419.72959735,,,,-35.4%,-19.2%,,,1.5,48465152.68170729,,,,-35.9%,-21.0%
-1753,Rouen,,0.0,2.5,43247248.65359076,0.0,,,30.0%,25.3%,,0.0,3.3,23051906.183581144,0.0,,,53.9%,47.8%,,0.0,1.3,20437284.61097416,0.0,,,6.6%,3.6%,,,2.0,32155159.54959657,,,,97.5%,93.3%,,,3.1,26610924.22128483,,,,157.2%,145.3%,,,3.0,17137235.228125088,,,,126.8%,119.7%,,,0.1,15400118.027912853,,,,71.2%,70.8%,,,3.1,13305462.11064239,,,,157.2%,145.3%,,,3.1,13305462.11064239,,,,157.2%,145.3%
-1753,Bordeaux,128147799.04138356,0.23969938057957085,3.7,54772841.92055931,0.23969938057957085,,,-49.2%,-57.2%,31241378.94684226,0.12874241343129542,4.2,19810161.39747899,0.12874241343129542,,,-38.5%,-53.8%,96906420.09454131,0.3319246938267478,3.2,34617683.919113696,0.3319246938267478,,,-56.9%,-60.6%,77803153.54717268,,2.2,33038509.21066158,,,,-53.2%,-55.5%,15113547.163444798,,3.0,12896694.6852329,,,,-46.2%,-38.5%,11037228.183258358,,2.9,9766798.332945067,,,,-47.7%,-40.4%,66765925.36391432,,1.9,22972333.63727993,,,,-53.5%,-55.1%,7556773.581722399,,3.0,6595769.714651695,,,,-47.0%,-41.8%,7556773.581722399,,3.0,6448347.342616484,,,,-46.2%,-38.5%
-1753,Nantes,,0.0,1.2,28868559.21509939,0.0,,,-41.9%,-38.6%,,0.0,1.1,12554775.707414314,0.0,,,-48.6%,-46.3%,21939713.34752571,0.07514809264875828,0.6,15066317.20170442,0.07514809264875828,,,-24.4%,13.7%,,,0.6,18175715.501060665,,,,-23.1%,6.9%,,,-0.2,9547546.728575554,,,,-30.2%,53.9%,,,0.0,6835631.446851056,,,,-34.6%,31.5%,13170095.837917892,,0.6,10064302.031164432,,,,-6.7%,42.0%,,,-0.1,4782778.736643961,,,,-31.5%,56.8%,,,-0.2,4773773.364287784,,,,-30.2%,53.9%
-1753,Bayonne,15127865.798115622,0.028296545773120754,0.1,17851334.66763188,0.028296545773120754,,,22.6%,40.3%,5891327.052754796,0.02427753475207583,0.3,6319565.054562729,0.02427753475207583,,,13.4%,23.8%,9236538.745360825,0.03163707102255738,-0.4,12128592.771615906,0.03163707102255738,,,29.2%,49.7%,12185144.764885966,,0.3,15427122.247141954,,,,31.5%,49.0%,8354569.901693509,,0.5,10170004.640833616,,,,29.0%,37.4%,4254871.700846754,,0.4,5240332.419664141,,,,28.9%,36.9%,7930273.064039211,,0.2,10263871.464072319,,,,31.3%,52.7%,4177284.9508467545,,0.5,5086360.821886447,,,,30.1%,37.3%,4177284.9508467545,,0.5,5085002.3204168165,,,,29.0%,37.4%
-1753,La Rochelle,17274754.971163396,0.03231228391924649,-0.7,15445406.763611412,0.03231228391924649,,,47.4%,42.5%,8358230.425187,0.03444338224584738,-0.5,6667697.945334481,0.03444338224584738,,,149.9%,144.1%,8916524.545976397,0.030540955666657738,-0.8,8632635.429806031,0.030540955666657738,,,-0.4%,-1.6%,13689581.505469998,,-1.3,12289037.3904649,,,,44.1%,34.1%,4884924.281235419,,1.8,3488978.683931822,,,,8.1%,-17.7%,6117667.016289091,,-1.0,4554983.24201476,,,,99.7%,86.6%,7571914.489180908,,-1.4,7466363.395917773,,,,7.4%,2.2%,2442462.1406177096,,1.8,1726054.7887113867,,,,9.3%,-17.2%,2442462.1406177096,,1.8,1744489.3419659138,,,,8.1%,-17.7%
+1773,Marseille,191943367.39045423,0.2887568111190186,1.1,143528473.3163917,0.2887568111190186,,,-39.5%,-30.6%,108209078.53882226,0.32690122493666757,1.8,82074965.06564157,0.32690122493666757,,,-40.0%,-29.8%,83734288.85163195,0.2509203397872683,0.4,59719144.27264253,0.2509203397872683,,,-41.6%,-33.6%,154538138.9824246,,0.9,118545043.06973015,,,,-38.2%,-27.0%,167201810.77750617,,1.5,130102955.13825357,,,,-35.9%,-21.0%,89319211.58882771,,1.6,68723083.40989304,,,,-38.0%,-24.8%,65218927.39359687,,0.1,48538777.730622515,,,,-40.0%,-29.9%,83600905.38875309,,1.5,65350009.07984855,,,,-35.4%,-19.2%,83600905.38875309,,1.5,65051477.56912689,,,,-35.9%,-21.0%
+1773,Rouen,69964917.04095003,0.10525420393325946,2.5,71897756.40252814,0.10525420393325946,,,30.0%,25.3%,44410546.42205017,0.1341649168583055,3.3,44800842.5569746,0.1341649168583055,,,53.9%,47.8%,25554370.61889986,0.0765768891893941,1.3,26303753.250326045,0.0765768891893941,,,6.6%,3.6%,39331512.477778554,,2.0,47877169.24795584,,,,97.5%,93.3%,42688616.16647629,,3.1,49618983.53443595,,,,157.2%,145.3%,26628464.283342242,,3.0,31409286.47092644,,,,126.8%,119.7%,12703048.194436308,,0.1,15738653.896581242,,,,71.2%,70.8%,21344308.083238143,,3.1,24809491.767217927,,,,157.2%,145.3%,21344308.083238143,,3.1,24809491.767217927,,,,157.2%,145.3%
+1773,Bordeaux,144954494.45848155,0.2180674338804072,3.7,114947974.94736898,0.2180674338804072,,,-49.2%,-57.2%,75613889.3156951,0.22843067673529938,4.2,45485824.11015015,0.22843067673529938,,,-38.5%,-53.8%,69340605.14278643,0.20778785420046803,3.2,65246522.29095541,0.20778785420046803,,,-56.9%,-60.6%,66530868.97102955,,2.2,51682927.48687178,,,,-53.2%,-55.5%,51819951.16812219,,3.0,23380590.125463914,,,,-46.2%,-38.5%,36732577.483376175,,2.9,17528975.88281916,,,,-47.7%,-40.4%,29798291.487653375,,1.9,33519505.196434766,,,,-53.5%,-55.1%,25909975.584061094,,3.0,12126425.755704427,,,,-47.0%,-41.8%,25909975.584061094,,3.0,11690295.062732019,,,,-46.2%,-38.5%
+1773,Nantes,,0.0,1.2,36552825.30658612,0.0,,,-41.9%,-38.6%,,0.0,1.1,15565933.904070942,0.0,,,-48.6%,-46.3%,2342934.25,0.007020897486224615,0.6,17005085.09814776,0.007020897486224615,,,-24.4%,13.7%,,,0.6,20305166.244957294,,,,-23.1%,6.9%,,,-0.2,9175208.388408864,,,,-30.2%,53.9%,,,0.0,6866795.570590443,,,,-34.6%,31.5%,2342157.25,,0.6,11377117.031658996,,,,-6.7%,42.0%,,,-0.1,4643122.570306698,,,,-31.5%,56.8%,,,-0.2,4587604.194204439,,,,-30.2%,53.9%
+1773,Bayonne,13977718.417804584,0.021027876357063185,0.1,18201846.33819041,0.021027876357063185,,,22.6%,40.3%,5139273.952221456,0.01552582253681751,0.3,6673491.578809601,0.01552582253681751,,,13.4%,23.8%,8838444.465583127,0.02648551171700548,-0.4,11191535.110493366,0.02648551171700548,,,29.2%,49.7%,12241626.234269615,,0.3,16471911.936258398,,,,31.5%,49.0%,8630619.87742167,,0.5,11257116.445965266,,,,29.0%,37.4%,4323016.038751706,,0.4,5668607.645315081,,,,28.9%,36.9%,7918610.195517911,,0.2,10580059.632284055,,,,31.3%,52.7%,4315309.938710835,,0.5,5584180.149180947,,,,30.1%,37.3%,4315309.938710835,,0.5,5628558.222982623,,,,29.0%,37.4%
+1773,La Rochelle,27086761.95964256,0.04074893086092281,-0.7,13337163.498301856,0.04074893086092281,,,47.4%,42.5%,10656918.011046315,0.032194706755688744,-0.5,5996426.369984411,0.032194706755688744,,,149.9%,144.1%,16429843.948596243,0.049234096124448255,-0.8,7317499.614943727,0.049234096124448255,,,-0.4%,-1.6%,22992573.483803757,,-1.3,9528237.453427076,,,,44.1%,34.1%,12268785.949076332,,1.8,5044455.508701947,,,,8.1%,-17.7%,7923580.668951896,,-1.0,3757338.615458018,,,,99.7%,86.6%,15068992.81485186,,-1.4,5688454.550895298,,,,7.4%,2.2%,6134392.974538166,,1.8,2486378.094079029,,,,9.3%,-17.2%,6134392.974538166,,1.8,2522227.754350978,,,,8.1%,-17.7%
+1778,Marseille,112736817.52331236,0.17881688163542112,1.1,151883875.13012278,0.17881688163542112,174845795.9777706,164928744.66959053,-39.5%,-30.6%,64536603.70214123,0.1823710037737475,1.8,89802610.07332301,0.1823710037737475,100097670.45521864,93088365.95813684,-40.0%,-29.8%,48200213.821171135,0.17426956445912495,0.4,60990890.343249224,0.17426956445912495,77139194.18281154,73606200.7747888,-41.6%,-33.6%,85929853.85705909,,0.9,123964580.471186,,141530920.68533987,130940890.46499817,-38.2%,-27.0%,95421751.18880251,,1.5,140037405.60475582,,147090038.77759284,136014241.18102998,-35.9%,-21.0%,50264762.644664966,,1.6,74443386.01642384,,81617218.10167657,74808234.59118511,-38.0%,-24.8%,35665091.212394126,,0.1,48811969.62126154,,62182994.59165667,58038653.355836794,-40.0%,-29.9%,47710875.594401255,,1.5,70577197.22677274,,75976831.23063539,70206035.80665484,-35.4%,-19.2%,47710875.594401255,,1.5,70018702.80237779,,73545019.38879654,68007120.59051462,-35.9%,-21.0%
+1778,Rouen,,0.0,2.5,81640292.49517828,0.0,68794498.14971642,76073631.89733402,30.0%,25.3%,,0.0,3.3,52896996.85104248,0.0,43782111.050780356,49525595.71136038,53.9%,47.8%,,0.0,1.3,28016659.636323668,0.0,24538824.212988015,26339286.86890366,6.6%,3.6%,,,2.0,52886875.9316169,,42004700.098776944,45179072.72669235,97.5%,93.3%,,,3.1,57982220.02159426,,43920752.317074895,53209905.798259325,157.2%,145.3%,,,3.0,36545793.73597942,,29049800.864100367,32920886.456597112,126.8%,119.7%,,,0.1,15824444.33499727,,12880034.384078337,12938366.834010359,71.2%,70.8%,,,3.1,28991110.010797076,,21960376.158537485,26604952.899129804,157.2%,145.3%,,,3.1,28991110.010797076,,21960376.158537485,26604952.899129804,157.2%,145.3%
+1778,Bordeaux,200484755.88645342,0.31799779034600617,3.7,138351966.67841172,0.31799779034600617,144989596.8430843,197612452.66071984,-49.2%,-57.2%,132324431.2604504,0.3739294906830977,4.2,55991626.19124359,0.3739294906830977,63768621.08132797,148670196.62011647,-38.5%,-53.8%,68160324.62600303,0.24643604549216305,3.2,76449070.29472654,0.24643604549216305,82348426.51801594,80183409.20516035,-56.9%,-60.6%,44156878.57935423,,2.2,57800124.15212804,,59752045.09488977,59142715.53682224,-53.2%,-55.5%,26129085.039341416,,3.0,27129996.08248795,,26043135.121919703,64805601.01264167,-46.2%,-38.5%,17200016.706055395,,2.9,20288859.014650613,,24050566.94006823,48219583.21676385,-47.7%,-40.4%,26956861.87329883,,1.9,36840093.188883595,,36042319.95912893,26537613.42870425,-53.5%,-55.1%,13064542.519670708,,3.0,14120485.985511314,,14791576.834998624,37961723.96166044,-47.0%,-41.8%,13064542.519670708,,3.0,13564998.041244142,,13021567.560959874,32402800.506319854,-46.2%,-38.5%
+1778,Nantes,70481106.37826885,0.11179321834386767,1.2,38774384.37581105,0.11179321834386767,50423566.07679903,53709521.25223945,-41.9%,-38.6%,28386346.565855905,0.08021566397540146,1.1,16425429.62877951,0.08021566397540146,18806467.887118552,21352363.436324812,-48.6%,-46.3%,42094759.81241295,0.1521950812446093,0.6,17527571.01290223,0.1521950812446093,18814741.879559807,7528087.321385088,-24.4%,13.7%,42578390.168815106,,0.6,20875424.129830446,,23378690.61556277,18208473.88163562,-23.1%,6.9%,14593367.671155874,,-0.2,9084415.148682429,,8171709.6649671355,19571222.083967958,-30.2%,53.9%,11089341.658675758,,0.0,6874608.776183582,,6882651.103821548,9049478.8445156,-34.6%,31.5%,31489048.51013935,,0.6,11731252.067642799,,11620390.655451072,4020075.596186619,-6.7%,42.0%,7296683.835577937,,-0.1,4608850.417294187,,4242657.416387997,8190311.876012514,-31.5%,56.8%,7296683.835577937,,-0.2,4542207.574341222,,4085854.83248356,9785611.04198396,-30.2%,53.9%
+1778,Bayonne,14547533.153390469,0.02307448951571892,0.1,18290544.383046146,0.02307448951571892,14776672.367445555,10689280.526706357,22.6%,40.3%,5328097.792025309,0.01505642514163019,0.3,6765028.0045023225,0.01505642514163019,5307511.634711625,4487971.703967477,13.4%,23.8%,9219435.36136516,0.03333319206726133,-0.4,10968808.977858964,0.03333319206726133,9363891.54997481,6336812.347585454,29.2%,49.7%,13431676.293333624,,0.3,16743983.387470536,,13448884.788104735,9831404.081788337,31.5%,49.0%,8560296.171448318,,0.5,11546587.750334142,,8910181.941764489,7716155.250856027,29.0%,37.4%,4488681.835764159,,0.4,5781037.525066523,,4450911.725909257,3929630.9857443995,28.9%,36.9%,8942994.457569463,,0.2,10660617.057248559,,8946373.878563719,5999512.9306731,31.3%,52.7%,4280148.085724159,,0.5,5716069.284299241,,4431779.237787478,3954884.8428896423,30.1%,37.3%,4280148.085724159,,0.5,5773293.87516708,,4455090.970882221,3858077.625428006,29.0%,37.4%
+1778,La Rochelle,16436976.728661306,0.026071420026784184,-0.7,12856699.889415823,0.026071420026784184,14443456.78880625,26184560.56013426,47.4%,42.5%,8974251.512137672,0.02535992231540869,-0.5,5839446.075741326,0.02535992231540869,6403344.387959242,10225471.937832491,149.9%,144.1%,7462725.216523634,0.026981744894054152,-0.8,7021300.091236005,0.026981744894054152,8063701.081621433,13902190.956794696,-0.4%,-1.6%,9318384.633708397,,-1.3,8941003.156234205,,10430766.173895163,23448054.648448296,44.1%,34.1%,4425934.879527943,,1.8,5531504.76631257,,6615058.225683728,20757276.476155713,8.1%,-17.7%,4030261.589664162,,-1.0,3580788.9447512003,,4038878.47598728,8931048.325343065,99.7%,86.6%,5288123.044044235,,-1.4,5314538.833033563,,6251117.147162967,13210018.823269624,7.4%,2.2%,2212967.4397639716,,1.8,2723926.089214877,,3155578.242619608,9683722.403721113,9.3%,-17.2%,2212967.4397639716,,1.8,2765752.38315629,,3307529.1128418637,10378638.238077836,8.1%,-17.7%
+1777,Marseille,151112290.19980615,0.2089809290509686,1.1,150174760.6209985,0.2089809290509686,173358839.78867877,164496623.03903565,-39.5%,-30.6%,89843072.74581158,0.2525672942899529,1.8,88200959.33624989,0.2525672942899529,98690896.93124546,92430946.13595872,-40.0%,-29.8%,61269217.45399458,0.16677707145122483,0.4,60734392.77887384,0.16677707145122483,76821683.75453392,73675367.65258697,-41.6%,-33.6%,123496709.83509737,,0.9,122861205.35409795,,140567811.3070282,131101881.52944699,-38.2%,-27.0%,139048842.87283474,,1.5,137991608.56037912,,145690855.8546969,135670688.15902448,-35.9%,-21.0%,75605403.43685709,,1.6,73262447.33696975,,80619240.14901212,74532991.76882146,-38.0%,-24.8%,47891306.398240276,,0.1,48757208.51024984,,62007330.2745304,58318833.45540923,-40.0%,-29.9%,69524421.43641737,,1.5,69499336.18983637,,75101053.86178377,69893322.65312018,-35.4%,-19.2%,69524421.43641737,,1.5,68995804.28018944,,72845427.92734857,67835344.07951212,-35.9%,-21.0%
+1777,Rouen,,0.0,2.5,79591503.60382162,0.0,68021879.07273585,74244769.94752476,30.0%,25.3%,,0.0,3.3,51168425.0120365,0.0,43034499.13043162,47918063.190999724,53.9%,47.8%,,0.0,1.3,27665379.220021844,0.0,24484975.554656886,26034635.70321741,6.6%,3.6%,,,2.0,51844659.18560084,,41865805.74869321,44624097.74577151,97.5%,93.3%,,,3.1,56203769.543036625,,43488133.78557815,51410360.87674253,157.2%,145.3%,,,3.0,35455330.09703795,,28683119.308540292,31998389.366859127,126.8%,119.7%,,,0.1,15807248.917566514,,13035221.04387457,13089956.556532284,71.2%,70.8%,,,3.1,28101884.77151826,,21744066.892789032,25705180.438371398,157.2%,145.3%,,,3.1,28101884.77151826,,21744066.892789032,25705180.438371398,157.2%,145.3%
+1777,Bordeaux,217388523.5054081,0.3006377280571239,3.7,133317921.62485684,0.3006377280571239,141087381.89084882,183692938.4664771,-49.2%,-57.2%,120227951.69289368,0.3379854175625682,4.2,53712291.19744271,0.3379854175625682,61596987.98495649,128213823.77880245,-38.5%,-53.8%,97160571.81251444,0.2644746628204424,3.2,74064354.18208799,0.2644746628204424,80425704.69681863,78093241.51310693,-56.9%,-60.6%,59057810.17789017,,2.2,56521338.519697286,,58907320.55170934,58084423.392243005,-53.2%,-55.5%,36852013.61007379,,3.0,26334851.79099195,,25508355.077534895,56148294.6041229,-46.2%,-38.5%,21552870.305040076,,2.9,19704136.53273926,,23427099.3140133,42857059.46725968,-47.7%,-40.4%,37504939.87285009,,1.9,36150648.7884419,,35718473.99888389,27150171.6412217,-53.5%,-55.1%,18426006.805036895,,3.0,13697025.923205303,,14423028.399563003,32602414.631756365,-47.0%,-41.8%,18426006.805036895,,3.0,13167425.895496044,,12754177.53876747,28074147.302061398,-46.2%,-38.5%
+1777,Nantes,,0.0,1.2,38319525.18656729,0.0,50227925.31550208,53308462.97874995,-41.9%,-38.6%,,0.0,1.1,16249815.214513786,0.0,18931237.889594946,21209962.128082592,-48.6%,-46.3%,,0.0,0.6,17421805.070449855,0.0,18881947.84682757,8424322.887595592,-24.4%,13.7%,,,0.6,20760105.50057534,,23500346.455626417,18908740.956105825,-23.1%,6.9%,,,-0.2,9102501.635039167,,8365386.186339876,18229862.06122427,-30.2%,53.9%,,,0.0,6873045.424184143,,7016021.199092125,8952140.03673124,-34.6%,31.5%,,,0.6,11659554.004192255,,11663818.140210373,4584281.522699413,-6.7%,42.0%,,,-0.1,4615684.55013268,,4337451.419707727,7753999.945308745,-31.5%,56.8%,,,-0.2,4551250.817519584,,4182693.0931699304,9114931.030612119,-30.2%,53.9%
+1777,Bayonne,,0.0,0.1,18272770.26307482,0.0,14876808.70995809,11181565.434552787,22.6%,40.3%,6885074.526691326,0.019355355855993635,0.3,6746620.822158007,0.019355355855993635,5371253.993493127,4639972.804640209,13.4%,23.8%,,0.0,-0.4,11012996.747040102,0.0,9400096.291887583,6661294.4805581905,29.2%,49.7%,,,0.3,16689211.940350538,,13498701.591307161,10240740.135900317,31.5%,49.0%,,,0.5,11488104.040154172,,9006064.098314527,7937041.768015481,29.0%,37.4%,6314869.7217075545,,0.4,5758374.556449987,,4501319.935665669,4038974.8065355998,28.9%,36.9%,,,0.2,10644456.651423944,,8939468.439962208,6283605.0883489465,31.3%,52.7%,6261668.171903195,,0.5,5689444.581101883,,4480554.318110707,4058658.68718726,30.1%,37.3%,,,0.5,5744052.020077085,,4503032.049157255,3968520.884007705,29.0%,37.4%
+1777,La Rochelle,,0.0,-0.7,12951387.579764977,0.0,14564157.69580894,24358813.89616819,47.4%,42.5%,,0.0,-0.5,5870509.87481258,0.0,6471725.863323258,9720696.471529692,149.9%,144.1%,,0.0,-0.8,7079564.9398969915,0.0,8113834.130846441,13001990.460270384,-0.4%,-1.6%,,,-1.3,9055480.774857698,,10550179.326237082,21267245.12459574,44.1%,34.1%,,,1.8,5430470.91433387,,6520621.780958988,17605242.798880335,8.1%,-17.7%,,,-1.0,3615422.4162731594,,4100174.239223311,8183731.338833762,99.7%,86.6%,,,-1.4,5387302.056128157,,6308418.776524988,12063358.494078534,7.4%,2.2%,,,1.8,2674666.816368223,,3112975.626424253,8303597.756660247,9.3%,-17.2%,,,1.8,2715235.4571669395,,3260310.890479505,8802621.39944015,8.1%,-17.7%
+1741,Marseille,115366928.14755529,0.2830808785115065,1.1,99923353.65805836,0.2830808785115065,,,-39.5%,-30.6%,51981444.31035002,0.27461636470553585,1.8,46143431.50092662,0.27461636470553585,,,-40.0%,-29.8%,63385483.837205276,0.290422021451805,0.4,52184873.35385978,0.290422021451805,,,-41.6%,-33.6%,96362034.68260647,,0.9,89049690.66010538,,,,-38.2%,-27.0%,80442894.04194802,,1.5,81238712.65471984,,,,-35.9%,-21.0%,43933405.025973506,,1.6,41197641.46897743,,,,-38.0%,-24.8%,52428629.65663297,,0.1,46826193.97874223,,,,-40.0%,-29.9%,40221447.02097401,,1.5,39936096.96326532,,,,-35.4%,-19.2%,40221447.02097401,,1.5,40619356.32735999,,,,-35.9%,-21.0%
+1741,Rouen,,0.0,2.5,31878976.55483264,0.0,,,30.0%,25.3%,,0.0,3.3,15472455.433774333,0.0,,,53.9%,47.8%,,0.0,1.3,17565741.028554123,0.0,,,6.6%,3.6%,,,2.0,25323515.236945573,,,,97.5%,93.3%,,,3.1,18310795.62091911,,,,157.2%,145.3%,,,3.0,11914350.45135005,,,,126.8%,119.7%,,,0.1,15200501.895913703,,,,71.2%,70.8%,,,3.1,9155397.810459537,,,,157.2%,145.3%,,,3.1,9155397.810459537,,,,157.2%,145.3%
+1741,Bordeaux,,0.0,3.7,35107802.40841068,0.0,,,-49.2%,-57.2%,16893245.116355717,0.08924649215661463,4.2,12030818.682559317,0.08924649215661463,,,-38.5%,-53.8%,,0.0,3.2,23666955.391677875,0.0,,,-56.9%,-60.6%,,,2.2,25259482.264533408,,,,-53.2%,-55.5%,,,3.0,9025103.44619066,,,,-46.2%,-38.5%,9129363.116353719,,2.9,6876217.836280496,,,,-47.7%,-40.4%,,,1.9,18312583.784630638,,,,-53.5%,-55.1%,5567610.617730667,,3.0,4577044.001004762,,,,-47.0%,-41.8%,,,3.0,4512551.723095386,,,,-46.2%,-38.5%
+1741,Nantes,57237294.94207373,0.1404456545388895,1.2,25056915.2814544,0.1404456545388895,,,-41.9%,-38.6%,35906236.66444655,0.18969153923804352,1.1,11035429.083520306,0.18969153923804352,,,-48.6%,-46.3%,21331058.27762719,0.09773545439213753,0.6,14010837.141009696,0.09773545439213753,,,-24.4%,13.7%,41832532.556854516,,0.6,17006795.761408933,,,,-23.1%,6.9%,46874659.36724149,,-0.2,9778163.754947368,,,,-30.2%,53.9%,26872116.049812768,,0.0,6817000.902370033,,,,-34.6%,31.5%,14960416.507041749,,0.6,9350493.295346787,,,,-6.7%,42.0%,23437329.683620743,,-0.1,4868580.716469921,,,,-31.5%,56.8%,23437329.683620743,,-0.2,4889081.877473692,,,,-30.2%,53.9%
+1741,Bayonne,,0.0,0.1,17644275.934292138,0.0,,,22.6%,40.3%,,0.0,0.3,6116283.847708822,0.0,,,13.4%,23.8%,,0.0,-0.4,12728079.118132912,0.0,,,29.2%,49.7%,,,0.3,14832332.974444583,,,,31.5%,49.0%,,,0.5,9568801.526067596,,,,29.0%,37.4%,,,0.4,4999059.440659438,,,,28.9%,36.9%,,,0.2,10078712.528684836,,,,31.3%,52.7%,,,0.5,4809232.932112455,,,,30.1%,37.3%,,,0.5,4784400.76303379,,,,29.0%,37.4%
+1741,La Rochelle,16755715.98272359,0.04111423331313859,-0.7,16867117.688993208,0.04111423331313859,,,47.4%,42.5%,7074108.810876449,0.037372298345074786,-0.5,7106012.463137486,0.037372298345074786,,,149.9%,144.1%,9681607.171847142,0.04435955609286887,-0.8,9532609.78367284,0.04435955609286887,,,-0.4%,-1.6%,14140793.81729184,,-1.3,14315978.647624984,,,,44.1%,34.1%,4324248.129338498,,1.8,2796589.535210442,,,,8.1%,-17.7%,5488566.314542199,,-1.0,5112704.024841708,,,,99.7%,86.6%,8652227.502749642,,-1.4,8789780.346896054,,,,7.4%,2.2%,2162124.064669249,,1.8,1386586.669962817,,,,9.3%,-17.2%,2162124.064669249,,1.8,1398294.7676052232,,,,8.1%,-17.7%
 1756,Marseille,113083436.7717866,0.2728394369935499,1.1,118409845.02466476,0.2728394369935499,161724699.12300253,139493195.39254272,-39.5%,-30.6%,50817634.884949565,0.29262251569916026,1.8,60442810.02368539,0.29262251569916026,82562154.1299999,71058722.4729874,-40.0%,-29.8%,62265801.88683704,0.25857241926075664,0.4,55590275.38584871,0.25857241926075664,74890581.92816487,65518383.91504577,-41.6%,-33.6%,99900998.25487915,,0.9,101829840.5501922,,138859674.56742242,116852289.11182962,-38.2%,-27.0%,90788787.0355993,,1.5,101305661.78588796,,149361544.29364324,117916649.57132277,-35.9%,-21.0%,45795601.118200876,,1.6,52365203.90056608,,71212318.09747003,59130377.45682181,-38.0%,-24.8%,54105397.13667827,,0.1,47621311.161315314,,62861905.52024093,54203891.15225125,-40.0%,-29.9%,45394393.51779965,,1.5,50306242.97872639,,69277887.45883065,55368801.81951939,-35.4%,-19.2%,45394393.51779965,,1.5,50652830.89294406,,74680772.14682148,58958324.78566127,-35.9%,-21.0%
 1756,Rouen,,0.0,2.5,46673676.47880744,0.0,46177935.92247358,46177935.92247358,30.0%,25.3%,,0.0,3.3,25467935.668342944,0.0,22739428.59967729,22739428.59967729,53.9%,47.8%,,0.0,1.3,21225717.13608479,0.0,23581957.838447478,23581957.838447478,6.6%,3.6%,,,2.0,34133619.12878777,,29355051.035537824,29355051.035537824,97.5%,93.3%,,,3.1,29217842.52314614,,22520671.541579522,22520671.541579522,157.2%,145.3%,,,3.0,18767583.416343965,,14594128.680054877,14594128.680054877,126.8%,119.7%,,,0.1,15450430.317661617,,14849964.471722882,14849964.471722882,71.2%,70.8%,,,3.1,14608921.261573045,,11260335.77078974,11260335.77078974,157.2%,145.3%,,,3.1,14608921.261573045,,11260335.77078974,11260335.77078974,157.2%,145.3%
 1756,Bordeaux,48940497.324008055,0.11808004883167941,3.7,61214693.95466095,0.11808004883167941,104983973.27835913,114238850.40072444,-49.2%,-57.2%,16705121.158854103,0.09619287850822242,4.2,22440690.80387007,0.09619287850822242,33288033.851233665,30306773.107257813,-38.5%,-53.8%,32235376.16515395,0.13386448015160696,3.2,38070353.74436327,0.13386448015160696,70223239.22992434,84114130.92247677,-56.9%,-60.6%,24717653.891584866,,2.2,35332099.26958339,,57146621.72313148,60650773.674595304,-53.2%,-55.5%,9118752.564398909,,3.0,14100515.036773391,,19900924.359486695,14495582.00514549,-46.2%,-38.5%,6322150.323772414,,2.9,10662348.389139807,,13632290.572568813,10393300.854109418,-47.7%,-40.4%,18395503.56781245,,1.9,24311904.86876746,,41992438.75149662,50979406.8820625,-53.5%,-55.1%,4559376.2821994545,,3.0,7226626.069722598,,9991049.916043788,7247791.0025728345,-47.0%,-41.8%,4559376.2821994545,,3.0,7050257.518386732,,9950462.179743329,7247791.0025728345,-46.2%,-38.5%
 1756,Nantes,16707043.02312034,0.040309530222841956,1.2,29908834.229884736,0.040309530222841956,31570974.473273356,28877560.466701824,-41.9%,-38.6%,7039868.723841467,0.04053758308166434,1.1,12966235.102959245,0.04053758308166434,16944217.732523922,14706112.826619975,-48.6%,-46.3%,9667174.299278872,0.040145064710206124,0.6,15342384.486084284,0.040145064710206124,17827293.14342243,18992025.09314296,-24.4%,13.7%,9998220.870939206,,0.6,18480289.538252465,,15802350.641387701,12734057.67656885,-23.1%,6.9%,5226042.288896973,,-0.2,9490747.391528973,,9460721.381095232,4492157.743283168,-30.2%,53.9%,3549154.285261427,,0.0,6840297.033230657,,7144999.944917521,4049850.3252484985,-34.6%,31.5%,6449066.585677779,,0.6,10251111.236236796,,9987578.921968257,11968756.547696503,-6.7%,42.0%,2613021.1444484866,,-0.1,4761565.562790598,,4730360.690547674,2246078.87164158,-31.5%,56.8%,2613021.1444484866,,-0.2,4745373.6957645025,,4730360.690547674,2246078.87164158,-30.2%,53.9%
 1756,Bayonne,16806833.632699765,0.040550297699601966,0.1,17903477.91016769,0.040550297699601966,17451356.607295573,17451356.607295573,22.6%,40.3%,5470397.1434133705,0.031500115611504204,0.3,6371432.376763334,0.031500115611504204,6868433.488996247,6868433.488996247,13.4%,23.8%,11336436.489286397,0.04707704261414764,-0.4,11983186.031763531,0.04707704261414764,10597392.153897317,10597392.153897317,29.2%,49.7%,14036341.890176062,,0.3,15579509.650904475,,14617167.187346455,14617167.187346455,31.5%,49.0%,6326934.856323342,,0.5,10326117.254626945,,10048007.144131737,10048007.144131737,29.0%,37.4%,3924407.6782068713,,0.4,5302448.649834381,,5255441.256774389,5255441.256774389,28.9%,36.9%,10111934.21196919,,0.2,10310690.277536336,,9403481.390491735,9403481.390491735,31.3%,52.7%,3163467.428161671,,0.5,5158102.92304241,,5024003.5720658945,5024003.5720658945,30.1%,37.3%,3163467.428161671,,0.5,5163058.627313471,,5024003.5720658945,5024003.5720658945,29.0%,37.4%
 1756,La Rochelle,14507895.704639208,0.035003588580378844,-0.7,15109112.98813279,0.035003588580378844,20557261.6883635,17089908.79173737,47.4%,42.5%,7069464.788738561,0.04070800571122178,-0.5,6562410.68572921,0.04070800571122178,10241470.994947983,8780631.809857871,149.9%,144.1%,7438430.915900648,0.030889718258571664,-0.8,8421244.884063045,0.030889718258571664,10284936.912385134,8333992.932694648,-0.4%,-1.6%,9895355.123279609,,-1.3,11828837.659378063,,15979384.657902434,14557516.075620621,44.1%,34.1%,3740415.0215685796,,1.8,3687361.4679146935,,4733338.845935467,6339937.743347205,8.1%,-17.7%,3900938.2652850896,,-1.0,4425331.574242878,,7461474.196068907,7338890.23187981,99.7%,86.6%,5994416.857994519,,-1.4,7167899.359568118,,8494689.991724625,7226569.501828352,7.4%,2.2%,1870207.5107842898,,1.8,1823188.0520760075,,2366669.4229677333,3169968.8716735966,9.3%,-17.2%,1870207.5107842898,,1.8,1843680.73395735,,2366669.4229677333,3169968.8716735966,8.1%,-17.7%
-1779,Marseille,90291903.57251516,0.20376013258214512,1.1,153612440.7933101,0.20376013258214512,176345506.28260857,165362001.45477745,-39.5%,-30.6%,55490251.31357412,0.2665725853064757,1.8,91433345.35894154,0.2665725853064757,101524496.60622519,93750461.71235538,-40.0%,-29.8%,34801652.25894105,0.14811323426907122,0.4,61248471.16535608,0.14811323426907122,77458016.90817949,73537098.83127132,-41.6%,-33.6%,79140647.77318889,,0.9,125077864.62868634,,142500628.86935225,130780097.09506348,-38.2%,-27.0%,102940014.17608234,,1.5,142113532.64956164,,148502659.14541447,136358664.16750994,-35.9%,-21.0%,52189930.038640864,,1.6,75643360.58964512,,82627549.92907538,75084493.85753475,-38.0%,-24.8%,26950717.734548032,,0.1,48866792.23659989,,62359156.558853894,57759819.32036635,-40.0%,-29.9%,51470007.08804117,,1.5,71671774.74588919,,76862821.31902066,70520148.08549453,-35.4%,-19.2%,51470007.08804117,,1.5,71056766.32478069,,74251329.57270736,68179332.08375461,-35.9%,-21.0%
-1779,Rouen,,0.0,2.5,83741819.8791037,0.0,69575892.93601632,77947543.97032076,30.0%,25.3%,,0.0,3.3,54683963.307469286,0.0,44542710.77381611,51187056.97240697,53.9%,47.8%,,0.0,1.3,28372400.426361874,0.0,24592791.298147686,26647502.990666572,6.6%,3.6%,,,2.0,53950044.03043804,,42144055.2459274,45740949.74586173,97.5%,93.3%,,,3.1,59816945.83773864,,44357674.52356317,55072441.17285506,157.2%,145.3%,,,3.0,37669795.65942139,,29421170.032668803,33869978.66244605,126.8%,119.7%,,,0.1,15841658.457920758,,12726695.249483071,12788532.613416573,71.2%,70.8%,,,3.1,29908472.918869264,,22178837.26178162,27536220.586427476,157.2%,145.3%,,,3.1,29908472.918869264,,22178837.26178162,27536220.586427476,157.2%,145.3%
-1779,Bordeaux,,0.0,3.7,143576095.77537474,0.0,148999739.81361258,212586731.8177381,-49.2%,-57.2%,,0.0,4.2,58367687.053520694,0.0,66016816.20547878,172390360.97385,-38.5%,-53.8%,,0.0,3.2,78910569.24035726,0.0,84317114.47921404,82329520.29124191,-56.9%,-60.6%,,,2.2,59107842.09112683,,60608882.895763054,60220289.65405169,-53.2%,-55.5%,,,3.0,27949148.65203775,,26589126.775010683,74797746.79213855,-46.2%,-38.5%,,,2.9,20890933.20239731,,24690626.969456084,54253097.02768285,-47.7%,-40.4%,,,1.9,37542686.276755005,,36369102.10880846,25938875.665231332,-53.5%,-55.1%,,,3.0,14557037.825942894,,15169542.706599465,44202017.01065696,-47.0%,-41.8%,,,3.0,13974574.326018948,,13294563.387505364,37398873.39606814,-46.2%,-38.5%
-1779,Nantes,22056667.15688417,0.04977488840511077,1.2,39234642.81990041,0.04977488840511077,50619968.870515995,54113596.82785597,-41.9%,-38.6%,10201460.893932555,0.04900734345265581,1.1,16602941.93678063,0.04900734345265581,18682520.205591597,21495720.810988396,-48.6%,-46.3%,11855206.262951616,0.05045487293154576,0.6,17633979.049244344,0.05045487293154576,18747775.116534866,6727199.262725819,-24.4%,13.7%,15897082.733057199,,0.6,20991383.333202865,,23257664.55955144,17534140.526217647,-23.1%,6.9%,8994715.249724098,,-0.2,9066364.59980773,,7982517.167893568,21011279.875491913,-30.2%,53.9%,5834082.586980555,,0.0,6876172.483785134,,6751816.289133522,9147876.040960325,-34.6%,31.5%,10063000.146076644,,0.6,11803391.023798259,,11577124.8627218,3525308.757551912,-6.7%,42.0%,4497357.624862049,,-0.1,4602026.403295303,,4149935.1142116045,8651174.761348244,-31.5%,56.8%,4497357.624862049,,-0.2,4533182.299903864,,3991258.5839467766,10505639.937745938,-30.2%,53.9%
-1779,Bayonne,24440115.70968818,0.05515357435486517,0.1,18308335.79209495,0.05515357435486517,14677210.04630995,10218669.187906394,22.6%,40.3%,11005466.09027656,0.052869747004914244,0.3,6783485.40819015,0.052869747004914244,5244525.726529546,4340950.01493755,13.4%,23.8%,13434649.619411621,0.05717686596019535,-0.4,10924798.504557459,0.05717686596019535,9327826.251669448,6028136.249749942,29.2%,49.7%,23649179.7612923,,0.3,16798934.586122863,,13399251.833242377,9438429.736202536,31.5%,49.0%,20570532.67535212,,0.5,11605369.189743007,,8815320.584960494,7501415.967752952,29.0%,37.4%,10447293.337411059,,0.4,5803789.687281276,,4401068.014488259,3823247.3396802074,28.9%,36.9%,13201886.423881244,,0.2,10676801.99778875,,8953284.651384214,5728265.048364282,31.3%,52.7%,10285266.33767606,,0.5,5742818.582228176,,4383535.120441496,3853764.3408881365,30.1%,37.3%,10285266.33767606,,0.5,5802684.594871482,,4407660.292480239,3750707.9838764425,29.0%,37.4%
-1779,La Rochelle,8152645.954763791,0.018397931098039486,-0.7,12762704.461470867,0.018397931098039486,14323756.194300553,28147150.95118706,47.4%,42.5%,4113823.0753538106,0.019762614634658213,-0.5,5808546.650742046,0.019762614634658213,6335685.444153532,10756459.339887628,149.9%,144.1%,4038822.8794099805,0.01718892869966104,-0.8,6963514.76251986,0.01718892869966104,8013877.790099649,14864717.366910376,-0.4%,-1.6%,5463128.081237061,,-1.3,8827972.741297798,,10312704.610043915,25852491.17013149,44.1%,34.1%,3686881.1497998,,1.8,5634418.352002524,,6710862.368519427,24473648.652830258,8.1%,-17.7%,2622218.27422905,,-1.0,3546487.240091202,,3978499.0568799446,9746608.348580029,99.7%,86.6%,2840909.8070080103,,-1.4,5242758.381385613,,6194336.009043501,14465672.83868715,7.4%,2.2%,1843440.5748999,,1.8,2774092.568875678,,3198763.896758236,11293234.853183305,9.3%,-17.2%,1843440.5748999,,1.8,2817209.1760012666,,3355431.1842597253,12236824.326415801,8.1%,-17.7%
-1766,Marseille,149053946.65444914,0.2943413152268615,1.1,132597403.58791907,0.2943413152268615,,,-39.5%,-30.6%,80910757.86589214,0.3814922040994452,1.8,72360432.25547408,0.3814922040994452,,,-40.0%,-29.8%,68143188.788557,0.23153689909462127,0.4,57983125.261375755,0.23153689909462127,,,-41.6%,-33.6%,124848376.0315132,,0.9,111353403.60142358,,,,-38.2%,-27.0%,123989810.9937569,,1.5,117367406.5317777,,,,-35.9%,-21.0%,66919275.50400648,,1.6,61445454.703008555,,,,-38.0%,-24.8%,57929100.52750672,,0.1,48158875.895804584,,,,-40.0%,-29.9%,61994905.49687845,,1.5,58675850.692245625,,,,-35.4%,-19.2%,61994905.49687845,,1.5,58683703.26588874,,,,-35.9%,-21.0%
-1766,Rouen,50794330.35516087,0.10030509314500914,2.5,60179758.283129,0.10030509314500914,,,30.0%,25.3%,25353315.665176697,0.11954025063476152,3.3,35504501.00917031,0.11954025063476152,,,53.9%,47.8%,25441014.689984173,0.08644346934537375,1.3,24080174.887447976,0.08644346934537375,,,6.6%,3.6%,32461012.994699825,,2.0,41650597.51680049,,,,97.5%,93.3%,19910871.337098226,,3.1,39897170.48659934,,,,157.2%,145.3%,15854264.768555736,,3.0,25407797.016091533,,,,126.8%,119.7%,16606748.226144088,,0.1,15619328.09085793,,,,71.2%,70.8%,9955435.668549113,,3.1,19948585.243299633,,,,157.2%,145.3%,9955435.668549113,,3.1,19948585.243299633,,,,157.2%,145.3%
-1766,Bordeaux,73181925.17871957,0.14451455054642207,3.7,88679596.28615703,0.14451455054642207,,,-49.2%,-57.2%,25701500.307875685,0.12118193253566495,4.2,34004018.89376862,0.12118193253566495,,,-38.5%,-53.8%,47480424.87084388,0.16132896827593743,3.2,52265678.45001176,0.16132896827593743,,,-56.9%,-60.6%,47958470.483713806,,2.2,44190892.561137795,,,,-53.2%,-55.5%,16176883.27914538,,3.0,18985563.907282736,,,,-46.2%,-38.5%,13881372.391643638,,2.9,14284170.664579805,,,,-47.7%,-40.4%,34077098.09207017,,1.9,29367381.817066137,,,,-53.5%,-55.1%,8088441.63957269,,3.0,9798717.73383606,,,,-47.0%,-41.8%,8088441.63957269,,3.0,9492781.953641418,,,,-46.2%,-38.5%
-1766,Nantes,100683009.86086693,0.19882177029602358,1.2,33654830.40411241,0.19882177029602358,,,-41.9%,-38.6%,17623090.132152636,0.08309243016486681,1.1,14437666.435387094,0.08309243016486681,,,-48.6%,-46.3%,83059919.7287143,0.28222096140390956,0.6,16299666.312048368,0.28222096140390956,,,-24.4%,13.7%,83084941.07071419,,0.6,19532880.264774106,,,,-23.1%,6.9%,9033962.493100537,,-0.2,9303845.424068866,,,,-30.2%,53.9%,8006979.924876008,,0.0,6855871.998814855,,,,-34.6%,31.5%,75077961.14583819,,0.6,10899215.212823391,,,,-6.7%,42.0%,4516981.2465502685,,-0.1,4691532.162007936,,,,-31.5%,56.8%,4516981.2465502685,,-0.2,4651922.712034441,,,,-30.2%,53.9%
-1766,Bayonne,17116868.576660886,0.03380119562415703,0.1,18078391.229090884,0.03380119562415703,,,22.6%,40.3%,6562373.214066982,0.030941425931358367,0.3,6547417.608014215,0.030941425931358367,,,13.4%,23.8%,10554495.362593904,0.035862060041632844,-0.4,11510970.079612572,0.035862060041632844,,,29.2%,49.7%,14749631.745971393,,0.3,16098422.825912433,,,,31.5%,49.0%,10278198.891821126,,0.5,10864007.479667613,,,,29.0%,37.4%,5217394.446202063,,0.4,5514869.649880446,,,,28.9%,36.9%,9532237.29976933,,0.2,10468300.881836263,,,,31.3%,52.7%,5139099.445910563,,0.5,5404632.035934256,,,,30.1%,37.3%,5139099.445910563,,0.5,5432003.739833796,,,,29.0%,37.4%
-1766,La Rochelle,12916548.066509645,0.0255066962762233,-0.7,14040126.844554398,0.0255066962762233,,,47.4%,42.5%,4934124.974354845,0.02326427611626961,-0.5,6223313.793191868,0.02326427611626961,,,149.9%,144.1%,7982423.092154801,0.02712267392935955,-0.8,7753288.609029472,0.02712267392935955,,,-0.4%,-1.6%,8919377.001444036,,-1.3,10415723.071386525,,,,44.1%,34.1%,3128933.9135037195,,1.8,4433775.53857784,,,,8.1%,-17.7%,3064539.3321407954,,-1.0,4019227.5310853706,,,,99.7%,86.6%,5854837.669303241,,-1.4,6256543.716175793,,,,7.4%,2.2%,1564466.9567518597,,1.8,2188203.7754369495,,,,9.3%,-17.2%,1564466.9567518597,,1.8,2216887.7692889236,,,,8.1%,-17.7%
+1759,Marseille,71379103.67011715,0.22306151204096866,1.1,122498839.65183604,0.22306151204096866,171965055.33507904,133668077.30714491,-39.5%,-30.6%,38241410.691821605,0.29136142641986695,1.8,63795728.11284683,0.29136142641986695,89688878.3328242,68360945.72524603,-40.0%,-29.8%,33137692.97829555,0.17556706907647257,0.4,56297571.84274555,0.17556706907647257,77382271.19886729,61532109.271137156,-41.6%,-33.6%,66455656.26762006,,0.9,104598051.2768286,,147953742.02875647,110316131.54013811,-38.2%,-27.0%,68534364.5690725,,1.5,105878518.29620236,,165206508.86452913,110377642.20014322,-35.9%,-21.0%,34296920.28453625,,1.6,54938511.43349554,,77346747.86838622,55220238.798502125,-38.0%,-24.8%,32158735.983083803,,0.1,47781947.46515621,,64985119.71096804,50464362.066855825,-40.0%,-29.9%,34267182.28453625,,1.5,52683320.215793915,,75767057.18542577,50382895.84354095,-35.4%,-19.2%,34267182.28453625,,1.5,52939259.148101084,,82603254.4322644,55188821.100071505,-35.9%,-21.0%
+1759,Rouen,,0.0,2.5,50371576.085626796,0.0,41036382.24448445,41036382.24448445,30.0%,25.3%,,0.0,3.3,28137184.92698167,0.0,18512707.924201306,18512707.924201306,53.9%,47.8%,,0.0,1.3,22044565.925316937,0.0,23295209.067592308,23295209.067592308,6.6%,3.6%,,,2.0,36233810.410179235,,23174808.560736734,23174808.560736734,97.5%,93.3%,,,3.1,32080145.5300281,,15302303.113639269,15302303.113639269,157.2%,145.3%,,,3.0,20553034.52399212,,10573921.342845844,10573921.342845844,126.8%,119.7%,,,0.1,15500906.978001308,,13026503.280225465,13026503.280225465,71.2%,70.8%,,,3.1,16040072.765014019,,7651151.55681962,7651151.55681962,157.2%,145.3%,,,3.1,16040072.765014019,,7651151.55681962,7651151.55681962,157.2%,145.3%
+1759,Bordeaux,31879684.77956994,0.09962482469918432,3.7,68414174.33474919,0.09962482469918432,124844978.78689165,146810430.65228266,-49.2%,-57.2%,8256959.730143646,0.06290980173962447,4.2,25420519.98723197,0.06290980173962447,37673046.826430656,31882137.656952836,-38.5%,-53.8%,23622725.049426295,0.1251557434382527,3.2,41867383.0868484,0.1251557434382527,85738244.4598055,120456542.04859142,-56.9%,-60.6%,30487823.266116474,,2.2,37784914.290044285,,65657538.37955273,73864848.92085092,-53.2%,-55.5%,13787801.04483759,,3.0,15416703.981519584,,22146011.28597632,12572633.032211687,-46.2%,-38.5%,7178133.522430795,,2.9,11640014.393244015,,14596110.5886835,8943412.150526652,-47.7%,-40.4%,23309689.743685678,,1.9,25729589.674285486,,49332177.65409501,71082057.7450794,-53.5%,-55.1%,6893900.522418795,,3.0,7917821.059699035,,11153512.069862496,6286316.516105832,-47.0%,-41.8%,6893900.522418795,,3.0,7708351.990759887,,11073005.642988138,6286316.516105832,-46.2%,-38.5%
+1759,Nantes,7052664.139287565,0.022039754577153813,1.2,30986595.428110115,0.022039754577153813,28885175.819388814,24802733.87982664,-41.9%,-38.6%,3829024.131588031,0.029173346709570322,1.1,13391179.31401399,0.029173346709570322,15516738.518660355,12303360.590956768,-48.6%,-46.3%,3223640.0076995343,0.017079192214139928,0.6,15623510.282407405,0.017079192214139928,17182654.03171949,19214843.33877062,-24.4%,13.7%,5643029.476544005,,0.6,18789967.382451385,,13697810.59367485,9451731.322183235,-23.1%,6.9%,5081892.675573802,,-0.2,9434285.959577907,,7895758.471382072,2251350.822947998,-30.2%,53.9%,2573879.8584496207,,0.0,6844965.804055813,,6060931.94769462,2307984.7934112814,-34.6%,31.5%,3069149.618094384,,0.6,10441387.912673922,,9336466.923641266,12944138.970836725,-6.7%,42.0%,2540946.337786901,,-0.1,4740446.476238721,,3947879.235691085,1125675.411473997,-31.5%,56.8%,2540946.337786901,,-0.2,4717142.979788962,,3947879.235691085,1125675.411473997,-30.2%,53.9%
+1759,Bayonne,28213363.30341639,0.08816747695944988,0.1,17955773.46163679,0.08816747695944988,17757566.962901812,17757566.962901812,22.6%,40.3%,5841264.294555447,0.04450461073919246,0.3,6423725.395841644,0.04450461073919246,6722046.40107941,6722046.40107941,13.4%,23.8%,22372099.008860942,0.11852979187920525,-0.4,11839522.537841922,0.11852979187920525,11097506.06113552,11097506.06113552,29.2%,49.7%,26752035.17090975,,0.3,15733402.320552142,,14831911.148371704,14831911.148371704,31.5%,49.0%,9834193.792521296,,0.5,10484626.243746152,,9070862.243390016,9070862.243390016,29.0%,37.4%,4933805.896260648,,0.4,5365301.174144319,,4859755.201057619,4859755.201057619,28.9%,36.9%,21818229.274649102,,0.2,10357722.655765094,,10191208.254351972,10191208.254351972,31.3%,52.7%,4917096.896260648,,0.5,5230856.932173153,,4535431.121695,4535431.121695,30.1%,37.3%,4917096.896260648,,0.5,5242313.121873067,,4535431.121695,4535431.121695,29.0%,37.4%
+1759,La Rochelle,5914391.078003212,0.018482622347824808,-0.7,14780141.357363967,0.018482622347824808,20908985.8012106,15236923.909221709,47.4%,42.5%,2537916.1779194237,0.019336391214532282,-0.5,6458785.979995767,0.019336391214532282,10586665.453861943,8124475.779072234,149.9%,144.1%,3376474.900083788,0.017888927946983383,-0.8,8215030.737021578,0.017888927946983383,10312149.137610322,7198703.730696986,-0.4%,-1.6%,5694046.725195842,,-1.3,11385871.482536672,,16034645.915478433,13662381.889050739,44.1%,34.1%,2261504.9502693475,,1.8,3897024.2660638737,,4742571.133952919,7802572.608410868,8.1%,-17.7%,2362073.0751120537,,-1.0,4299370.272398356,,7640654.697758683,7413371.857920398,99.7%,86.6%,3331973.650083788,,-1.4,6881366.269553439,,8387701.596069861,6362407.208827104,7.4%,2.2%,1130752.4751346738,,1.8,1925787.4633946666,,2371285.566976464,3901286.304205427,9.3%,-17.2%,1130752.4751346738,,1.8,1948512.133031954,,2371285.566976464,3901286.304205427,8.1%,-17.7%
+1746,Marseille,73432842.2245298,0.24564045206185903,1.1,105740316.32126555,0.24564045206185903,149886782.61053583,149886782.61053583,-39.5%,-30.6%,32880300.461018704,0.26918058675083567,1.8,50487996.95752178,0.26918058675083567,77198707.8360006,77198707.8360006,-40.0%,-29.8%,40552541.76351109,0.22937629922717642,0.4,53296173.732342966,0.22937629922717642,67995352.83097889,67995352.83097889,-41.6%,-33.6%,67484302.60745627,,0.9,93120785.63483693,,134610331.17076057,134610331.17076057,-38.2%,-27.0%,58479464.72048733,,1.5,87441968.88339737,,125815876.82497229,125815876.82497229,-35.9%,-21.0%,29651222.161240414,,1.6,44626809.13993772,,67234470.97064297,67234470.97064297,-38.0%,-24.8%,37833080.44621586,,0.1,47089746.89586505,,62024701.37928923,62024701.37928923,-40.0%,-29.9%,29239732.360243663,,1.5,43130488.144232534,,57523042.87762122,57523042.87762122,-35.4%,-19.2%,29239732.360243663,,1.5,43720984.4416986,,62907938.412486024,62907938.412486024,-35.9%,-21.0%
+1746,Rouen,,0.0,2.5,36198750.84574895,0.0,,,30.0%,25.3%,,0.0,3.3,18268549.867503464,0.0,,,53.9%,47.8%,,0.0,1.3,18709626.074016966,0.0,,,6.6%,3.6%,,,2.0,27973283.08097356,,,,97.5%,93.3%,,,3.1,21397064.285400935,,,,157.2%,145.3%,,,3.0,13862759.80819415,,,,126.8%,119.7%,,,0.1,15283358.900735278,,,,71.2%,70.8%,,,3.1,10698532.142700449,,,,157.2%,145.3%,,,3.1,10698532.142700449,,,,157.2%,145.3%
+1746,Bordeaux,35852053.14820024,0.11992882579353403,3.7,42255929.35573394,0.11992882579353403,112373873.33652481,112373873.33652481,-49.2%,-57.2%,11962451.279120866,0.0979327928620843,4.2,14809561.344149902,0.0979327928620843,31876846.491373897,31876846.491373897,-38.5%,-53.8%,23889601.869079374,0.13512614076562443,3.2,27730470.113521285,0.13512614076562443,84725761.12460215,84725761.12460215,-56.9%,-60.6%,23487910.349078428,,2.2,28249197.20887268,,76833917.0087485,76833917.0087485,-53.2%,-55.5%,10446944.025855407,,3.0,10472405.522071678,,41541618.25833723,41541618.25833723,-46.2%,-38.5%,6600125.512250955,,2.9,7958857.1041997215,,17352324.954885703,17352324.954885703,-47.7%,-40.4%,16887784.83682747,,1.9,20126707.99289686,,61169366.47667411,61169366.47667411,-53.5%,-55.1%,5223472.012927704,,3.0,5329689.635946812,,20103809.455090284,20103809.455090284,-47.0%,-41.8%,5223472.012927704,,3.0,5236202.761035866,,20770809.129166212,20770809.129166212,-46.2%,-38.5%
+1746,Nantes,29253335.959653705,0.09785543432290571,1.2,26579791.199346468,0.09785543432290571,48956641.75424564,48956641.75424564,-41.9%,-38.6%,8183454.363562834,0.06699534421359975,1.1,11644766.382269194,0.06699534421359975,40967797.25016963,40967797.25016963,-48.6%,-46.3%,21069881.59609087,0.11917702949053509,0.6,14441323.96408914,0.11917702949053509,14719743.321885489,14719743.321885489,-24.4%,13.7%,20173608.97870717,,0.6,17484420.97572012,,33212822.243591122,33212822.243591122,-23.1%,6.9%,5517820.611745157,,-0.2,9681403.972683586,,108645032.73977771,108645032.73977771,-30.2%,53.9%,4332129.955432768,,0.0,6824757.450388859,,36188302.96708259,36188302.96708259,-34.6%,31.5%,15841479.0232744,,0.6,9641545.700837487,,9121362.39486122,9121362.39486122,-6.7%,42.0%,2758910.3058725786,,-0.1,4832644.395439835,,54322516.36988566,54322516.36988566,-31.5%,56.8%,2758910.3058725786,,-0.2,4840701.986341801,,54322516.36988566,54322516.36988566,-30.2%,53.9%
+1746,Bayonne,,0.0,0.1,17730256.924856924,0.0,,,22.6%,40.3%,,0.0,0.3,6200177.377104896,0.0,,,13.4%,23.8%,19382859.430333726,0.10963476939369013,-0.4,12474773.75744219,0.10963476939369013,,,29.2%,49.7%,,,0.3,15077323.014024427,,,,31.5%,49.0%,,,0.5,9814858.628905015,,,,29.0%,37.4%,,,0.4,5098209.653013298,,,,28.9%,36.9%,12685509.671766309,,0.2,10155452.656480605,,,,31.3%,52.7%,,,0.5,4922819.090698647,,,,30.1%,37.3%,,,0.5,4907429.314452516,,,,29.0%,37.4%
+1746,La Rochelle,21321328.080479153,0.07132204759600864,-0.7,16259489.519975789,0.07132204759600864,7664715.944905764,7664715.944905764,47.4%,42.5%,9353645.776156569,0.07657532999950249,-0.5,6919984.342631898,0.07657532999950249,1403565.9917032623,1403565.9917032623,149.9%,144.1%,11967682.304322582,0.06769249368635398,-0.8,9146746.493451513,0.06769249368635398,9032916.010519791,9032916.010519791,-0.4%,-1.6%,13829966.502062157,,-1.3,13433671.32679489,,6174490.565571938,6174490.565571938,44.1%,34.1%,2027781.73072188,,1.8,3066604.17893487,,1190667.370638581,1190667.370638581,8.1%,-17.7%,4265938.24099594,,-1.0,4872468.500608254,,974701.3294551437,974701.3294551437,99.7%,86.6%,9564028.261066217,,-1.4,8212007.069663957,,7367941.284550942,7367941.284550942,7.4%,2.2%,1013890.86536094,,1.8,1519060.8436679833,,595333.6853192893,595333.6853192893,9.3%,-17.2%,1013890.86536094,,1.8,1533302.0894674375,,595333.6853192893,595333.6853192893,8.1%,-17.7%
+1760,Marseille,,0.0,1.1,123892979.00876981,0.0,175520624.09041402,131780937.83901428,-39.5%,-30.6%,,0.0,1.8,64954201.62291968,0.0,92198626.5761469,67484642.45121136,-40.0%,-29.8%,30709015.25629021,0.17186536089365806,0.4,56535331.52712239,0.17186536089365806,78231122.41457492,60257995.12915271,-41.6%,-33.6%,,,0.9,105537411.15647595,,151115573.60370654,108219691.23582856,-38.2%,-27.0%,,,1.5,107448222.1503217,,170853261.36391908,107973316.1887696,-35.9%,-21.0%,,,1.6,55824081.2649951,,79506817.46128605,53975187.13919997,-38.0%,-24.8%,29649339.857185278,,0.1,47835613.22268079,,65708676.116741836,49276088.73624019,-40.0%,-29.9%,,,1.5,53500382.66948323,,78062480.50982556,48822774.86461871,-35.4%,-19.2%,,,1.5,53724111.07516076,,85426630.68195939,53986658.09438469,-35.9%,-21.0%
+1760,Rouen,,0.0,2.5,51668206.01283718,0.0,39453050.01983488,39453050.01983488,30.0%,25.3%,,0.0,3.3,29087715.366060898,0.0,17286221.883924425,17286221.883924425,53.9%,47.8%,,0.0,1.3,22324476.214413438,0.0,23200403.08610315,23200403.08610315,6.6%,3.6%,,,2.0,36962207.21275573,,21418740.399368092,21418740.399368092,97.5%,93.3%,,,3.1,33095254.492183924,,13452880.620263124,13452880.620263124,157.2%,145.3%,,,3.0,21185163.367722426,,9497049.687802944,9497049.687802944,126.8%,119.7%,,,0.1,15517769.151010163,,12469872.108450146,12469872.108450146,71.2%,70.8%,,,3.1,16547627.246091932,,6726440.310131549,6726440.310131549,157.2%,145.3%,,,3.1,16547627.246091932,,6726440.310131549,6726440.310131549,157.2%,145.3%
+1760,Bordeaux,31965375.94073119,0.10772491972702726,3.7,70997473.2018887,0.10772491972702726,132267690.78987925,159614108.09390193,-49.2%,-57.2%,8626459.70177719,0.07307410999487797,4.2,26499265.270215746,0.07307410999487797,39259516.40805945,32425250.825401787,-38.5%,-53.8%,23338916.238954,0.13061803606525843,3.2,43215424.585944355,0.13061803606525843,91637344.64837465,135774288.27225086,-56.9%,-60.6%,29107079.0354503,,2.2,38639791.52370855,,68767400.49275187,78880859.98457246,-53.2%,-55.5%,11609573.402116718,,3.0,15882189.956602307,,22949308.612395998,11990108.150441632,-46.2%,-38.5%,6461837.951410677,,2.9,11985433.137891503,,14932295.717559388,8506544.158407161,-47.7%,-40.4%,22645241.08403962,,1.9,26220289.62355639,,52053509.64216892,79411194.62699646,-53.5%,-55.1%,5804786.701058359,,3.0,8162610.039296977,,11570314.018524181,5995054.075220805,-47.0%,-41.8%,5804786.701058359,,3.0,7941094.978301251,,11474654.306197977,5995054.075220805,-46.2%,-38.5%
+1760,Nantes,6693610.976483328,0.02255780462155644,1.2,31354411.511561878,0.02255780462155644,28041679.727632638,23576494.797469735,-41.9%,-38.6%,2325837.7275272883,0.019702001493909705,1.1,13535899.981942363,0.019702001493909705,15068155.072210982,11593085.504074853,-48.6%,-46.3%,4367773.2489560405,0.024444578227878336,0.6,15718358.966728695,0.024444578227878336,16972996.659406405,19289695.501967203,-24.4%,13.7%,6433357.474504799,,0.6,18894342.2509815,,13060535.30661466,8557749.16522071,-23.1%,6.9%,4243199.748488137,,-0.2,9415540.224489396,,7433905.836643499,1788295.297258121,-30.2%,53.9%,2172818.8743801382,,0.0,6846522.769027732,,5737444.098259895,1913510.86779608,-34.6%,31.5%,4260538.600124661,,0.6,10505595.110719873,,9129002.848321784,13286620.936208714,-6.7%,42.0%,2121599.8742440683,,-0.1,4733427.616830001,,3716952.9183217427,894147.6486290587,-31.5%,56.8%,2121599.8742440683,,-0.2,4707770.112244707,,3716952.9183217427,894147.6486290587,-30.2%,53.9%
+1760,Bayonne,20134008.34647001,0.0678526176863467,0.1,17973239.235413305,0.0678526176863467,17860826.442271613,17860826.442271613,22.6%,40.3%,5435098.078555205,0.0460403188046506,0.3,6441251.604562715,0.0460403188046506,6673947.3408975145,6673947.3408975145,13.4%,23.8%,14698910.267914804,0.08226357950117658,-0.4,11792018.47503929,0.08226357950117658,11269401.518039,11269401.518039,29.2%,49.7%,18944021.15999452,,0.3,15785036.946339013,,14904191.271557426,14904191.271557426,31.5%,49.0%,9336532.650077432,,0.5,10538001.443034157,,8766739.803926297,8766739.803926297,29.0%,37.4%,4820746.325038716,,0.4,5386417.142016147,,4734594.569263341,4734594.569263341,28.9%,36.9%,14123274.834955806,,0.2,10373447.742260098,,10468183.944072206,10468183.944072206,31.3%,52.7%,4668266.325038716,,0.5,5255335.598113508,,4383369.90196314,4383369.90196314,30.1%,37.3%,4668266.325038716,,0.5,5269000.721517087,,4383369.90196314,4383369.90196314,29.0%,37.4%
+1760,La Rochelle,6173162.77964594,0.020803868101919146,-0.7,14672083.634626262,0.020803868101919146,21027559.41635285,14665036.560721654,47.4%,42.5%,2857492.65888236,0.024205611581505204,-0.5,6424609.318307889,0.024205611581505204,10704296.723639173,7916840.138371825,149.9%,144.1%,3315670.12076358,0.01855640231878252,-0.8,8147421.000166069,0.01855640231878252,10321235.869733535,6855745.557451918,-0.4%,-1.6%,4803365.6951494,,-1.3,11241933.519917035,,16053108.770779466,13376406.798079938,44.1%,34.1%,2256211.15045086,,1.8,3969528.3599198293,,4745652.563204216,8361587.919887865,8.1%,-17.7%,1732702.4252254302,,-1.0,4258185.010830802,,7701332.669708904,7438366.668504211,99.7%,86.6%,3070663.26992397,,-1.4,6788423.571362341,,8352339.082439775,6097959.758600874,7.4%,2.2%,1128105.57522543,,1.8,1961254.6436518442,,2372826.2816021037,4180793.959943984,9.3%,-17.2%,1128105.57522543,,1.8,1984764.179959918,,2372826.2816021037,4180793.959943984,8.1%,-17.7%
+1755,Marseille,142798869.80244273,0.27637413106055086,1.1,117077406.12039375,0.27637413106055086,,,-39.5%,-30.6%,79420447.92118071,0.3135523337871422,1.8,59364798.24712162,0.3135523337871422,,,-40.0%,-29.8%,63378421.881262034,0.24062180912136327,0.4,55356490.140885204,0.24062180912136327,,,-41.6%,-33.6%,120718025.2021401,,0.9,100923480.75118335,,,,-38.2%,-27.0%,127785562.12080182,,1.5,99825694.18319511,,,,-35.9%,-21.0%,67530864.66140786,,1.6,51534504.25009565,,,,-38.0%,-24.8%,53187160.540732235,,0.1,47567885.824717306,,,,-40.0%,-29.9%,63892781.06040091,,1.5,49537961.70159948,,,,-35.4%,-19.2%,63892781.06040091,,1.5,49912847.09159746,,,,-35.9%,-21.0%
+1755,Rouen,48031151.68087739,0.092959894066423,2.5,45502385.845641196,0.092959894066423,,,30.0%,25.3%,24352828.677996635,0.09614509192748923,3.3,24635692.648613825,0.09614509192748923,,,53.9%,47.8%,23678323.002880752,0.08989685682908495,1.3,20959583.38392964,0.08989685682908495,,,6.6%,3.6%,31761797.162419,,2.0,33460963.978876054,,,,97.5%,93.3%,25616680.321453337,,3.1,28321662.866721146,,,,157.2%,145.3%,16248958.761210268,,3.0,18207591.000960305,,,,126.8%,119.7%,15512838.401208732,,0.1,15433641.317481143,,,,71.2%,70.8%,12808340.160726668,,3.1,14160831.433360547,,,,157.2%,145.3%,12808340.160726668,,3.1,14160831.433360547,,,,157.2%,145.3%
+1755,Bordeaux,70406283.96697909,0.13626491287708623,3.7,58987349.19979014,0.13626491287708623,,,-49.2%,-57.2%,28538401.98042751,0.1126697566903576,4.2,21527163.990778353,0.1126697566903576,,,-38.5%,-53.8%,41867881.98655157,0.15895513344522502,3.2,36882805.14974975,0.15895513344522502,,,-56.9%,-60.6%,34930179.671590865,,2.2,34550402.31698442,,,,-53.2%,-55.5%,13715763.562669301,,3.0,13687247.596389068,,,,-46.2%,-38.5%,9987974.531700868,,2.9,10355060.788166244,,,,-47.7%,-40.4%,24942205.13989,,1.9,23856919.410671473,,,,-53.5%,-55.1%,6857881.781334651,,3.0,7009906.366952718,,,,-47.0%,-41.8%,6857881.781334651,,3.0,6843623.798194619,,,,-46.2%,-38.5%
+1755,Nantes,30841541.54817666,0.05969097835114233,1.2,29557976.097433817,0.05969097835114233,,,-41.9%,-38.6%,15820236.834144201,0.06245837577413501,1.1,12827605.074138116,0.06245837577413501,,,-48.6%,-46.3%,15021304.714032458,0.05702971781824018,0.6,15249804.530000072,0.05702971781824018,,,-24.4%,13.7%,14876759.088964075,,0.6,18378201.952173512,,,,-23.1%,6.9%,6284780.831677182,,-0.2,9509642.859250639,,,,-30.2%,53.9%,5296486.928409721,,0.0,6838741.484050795,,,,-34.6%,31.5%,9580272.160554353,,0.6,10188459.370978396,,,,-6.7%,42.0%,3142390.415838591,,-0.1,4768626.145935852,,,,-31.5%,56.8%,3142390.415838591,,-0.2,4754821.429625328,,,,-30.2%,53.9%
+1755,Bayonne,18386550.5705723,0.035585484284105094,0.1,17886079.92804008,0.035585484284105094,,,22.6%,40.3%,7318646.034677398,0.028894051902257224,0.3,6354096.141425431,0.028894051902257224,,,13.4%,23.8%,11067904.535894904,0.04202028282747364,-0.4,12031460.211712789,0.04202028282747364,,,29.2%,49.7%,15999202.915834371,,0.3,15528547.327946216,,,,31.5%,49.0%,11198336.659063749,,0.5,10273815.253216485,,,,29.0%,37.4%,5949910.367980328,,0.4,5281661.857356226,,,,28.9%,36.9%,10049292.547854042,,0.2,10295060.32494334,,,,31.3%,52.7%,5599168.3295318745,,0.5,5134077.154186765,,,,30.1%,37.3%,5599168.3295318745,,0.5,5136907.626608232,,,,29.0%,37.4%
+1755,La Rochelle,,0.0,-0.7,15220389.367326215,0.0,,,47.4%,42.5%,,0.0,-0.5,6597320.402219525,0.0,,,149.9%,144.1%,,0.0,-0.8,8491126.893424744,0.0,,,-0.4%,-1.6%,,,-1.3,11980290.1466066,,,,44.1%,34.1%,,,1.8,3620011.19913971,,,,8.1%,-17.7%,,,-1.0,4468133.481145648,,,,99.7%,86.6%,,,-1.4,7266037.5944377165,,,,7.4%,2.2%,,,1.8,1790217.6575915313,,,,9.3%,-17.2%,,,1.8,1810005.599569858,,,,8.1%,-17.7%
+1752,Marseille,152649217.7040942,0.2778400692675755,1.1,113169378.20804681,0.2778400692675755,,,-39.5%,-30.6%,72536829.71123928,0.2851612616381191,1.8,56244756.95611082,0.2851612616381191,,,-40.0%,-29.8%,80112387.99285492,0.27152809873580075,0.4,54661016.99592844,0.27152809873580075,,,-41.6%,-33.6%,128178268.88924642,,0.9,98252518.35203207,,,,-38.2%,-27.0%,122358614.1987883,,1.5,95514257.0485614,,,,-35.9%,-21.0%,62664310.407607,,1.6,49120639.64888437,,,,-38.0%,-24.8%,65513958.48163942,,0.1,47407969.16652792,,,,-40.0%,-29.9%,61179307.09939415,,1.5,47302803.38869776,,,,-35.4%,-19.2%,61179307.09939415,,1.5,47757128.52428061,,,,-35.9%,-21.0%
+1752,Rouen,,0.0,2.5,42161945.30747096,0.0,,,30.0%,25.3%,,0.0,3.3,22298614.34781673,0.0,,,53.9%,47.8%,,0.0,1.3,20181036.43794371,0.0,,,6.6%,3.6%,,,2.0,31521492.97044888,,,,97.5%,93.3%,,,3.1,25794704.854406856,,,,157.2%,145.3%,,,3.0,16625889.599042216,,,,126.8%,119.7%,,,0.1,15383383.698898392,,,,71.2%,70.8%,,,3.1,12897352.427203404,,,,157.2%,145.3%,,,3.1,12897352.427203404,,,,157.2%,145.3%
+1752,Bordeaux,92987045.605435,0.16924768813478386,3.7,52779889.01530614,0.16924768813478386,,,-49.2%,-57.2%,26313651.377653956,0.10344585026707855,4.2,19003719.485042114,0.10344585026707855,,,-38.5%,-53.8%,66673394.22778104,0.22597878336302415,3.2,33537836.27275435,0.22597878336302415,,,-56.9%,-60.6%,57185673.23863688,,2.2,32307556.266956586,,,,-53.2%,-55.5%,26708037.430537343,,3.0,12518709.62666699,,,,-46.2%,-38.5%,16084385.291098023,,2.9,9485320.377114981,,,,-47.7%,-40.4%,41101287.94753886,,1.9,22542417.60232049,,,,-53.5%,-55.1%,13354018.715268672,,3.0,6397968.79921665,,,,-47.0%,-41.8%,13354018.715268672,,3.0,6259354.813333572,,,,-46.2%,-38.5%
+1752,Nantes,,0.0,1.2,28529904.465305164,0.0,,,-41.9%,-38.6%,,0.0,1.1,12420544.845152345,0.0,,,-48.6%,-46.3%,19488858.359375678,0.06605436174645747,0.6,14975403.107734887,0.06605436174645747,,,-24.4%,13.7%,,,0.6,18075310.422616266,,,,-23.1%,6.9%,,,-0.2,9566555.28012457,,,,-30.2%,53.9%,,,0.0,6834076.958670305,,,,-34.6%,31.5%,11292195.219725497,,0.6,10002791.890434805,,,,-6.7%,42.0%,,,-0.1,4789870.775279177,,,,-31.5%,56.8%,,,-0.2,4783277.640062293,,,,-30.2%,53.9%
+1752,Bayonne,16041652.941921158,0.029197751757821418,0.1,17833987.356508385,0.029197751757821418,,,22.6%,40.3%,6549367.101444947,0.025747276149426908,0.3,6302369.946690495,0.025747276149426908,,,13.4%,23.8%,9492285.840476211,0.03217258143835562,-0.4,12177452.721585495,0.03217258143835562,,,29.2%,49.7%,13639866.063100826,,0.3,15376658.400468208,,,,31.5%,49.0%,11470318.401993232,,0.5,10118493.353100473,,,,29.0%,37.4%,5735159.200996616,,0.4,5219789.136792827,,,,28.9%,36.9%,7904706.86210421,,0.2,10248312.484015128,,,,31.3%,52.7%,5735159.200996616,,0.5,5062669.218355788,,,,30.1%,37.3%,5735159.200996616,,0.5,5059246.676550236,,,,29.0%,37.4%
+1752,La Rochelle,19547146.653775062,0.03557817499462138,-0.7,15559159.89664935,0.03557817499462138,,,47.4%,42.5%,9562134.84912517,0.0375912546548455,-0.5,6703167.753010611,0.0375912546548455,,,149.9%,144.1%,9985011.804649893,0.03384259712009734,-0.8,8704271.621156255,0.03384259712009734,,,-0.4%,-1.6%,15876864.524760611,,-1.3,12446382.12136957,,,,44.1%,34.1%,6605259.492172438,,1.8,3425251.909608857,,,,8.1%,-17.7%,7352134.248290169,,-1.0,4599039.142775541,,,,99.7%,86.6%,8524730.276470441,,-1.4,7568588.007036547,,,,7.4%,2.2%,3302629.746086219,,1.8,1694840.9447961512,,,,9.3%,-17.2%,3302629.746086219,,1.8,1712625.9548044312,,,,8.1%,-17.7%
+1751,Marseille,138986808.4911104,0.29573526778480674,1.1,111895909.07830423,0.29573526778480674,,,-39.5%,-30.6%,67624214.96659152,0.31899430396494133,1.8,55241618.446420506,0.31899430396494133,,,-40.0%,-29.8%,71362593.52451889,0.27662232233148176,0.4,54431139.752838,0.27662232233148176,,,-41.6%,-33.6%,120241210.20059922,,0.9,97377999.32789785,,,,-38.2%,-27.0%,121368956.53832643,,1.5,94118895.68834531,,,,-35.9%,-21.0%,61522770.47357665,,1.6,48341410.40603268,,,,-38.0%,-24.8%,58718439.72702257,,0.1,47354783.17377838,,,,-40.0%,-29.9%,60684478.26916321,,1.5,46580390.89976433,,,,-35.4%,-19.2%,60684478.26916321,,1.5,47059447.84417257,,,,-35.9%,-21.0%
+1751,Rouen,,0.0,2.5,41103877.9911512,0.0,,,30.0%,25.3%,,0.0,3.3,21569938.636433113,0.0,,,53.9%,47.8%,,0.0,1.3,19928001.173449438,0.0,,,6.6%,3.6%,,,2.0,30900313.760020647,,,,97.5%,93.3%,,,3.1,25003520.847042214,,,,157.2%,145.3%,,,3.0,16129801.644193344,,,,126.8%,119.7%,,,0.1,15366667.55401524,,,,71.2%,70.8%,,,3.1,12501760.423521174,,,,157.2%,145.3%,,,3.1,12501760.423521174,,,,157.2%,145.3%
+1751,Bordeaux,60095279.15993086,0.12787036171207272,3.7,50859451.26798977,0.12787036171207272,,,-49.2%,-57.2%,26737232.39556796,0.12612382771743358,4.2,18230106.611455105,0.12612382771743358,,,-38.5%,-53.8%,33358046.7643629,0.129305563442419,3.2,32491672.882743992,0.129305563442419,,,-56.9%,-60.6%,36672930.18995942,,2.2,31592775.124542758,,,,-53.2%,-55.5%,26849151.44184756,,3.0,12151802.810083793,,,,-46.2%,-38.5%,16425674.82652786,,2.9,9211954.582191404,,,,-47.7%,-40.4%,20247255.363431558,,1.9,22120547.236557465,,,,-53.5%,-55.1%,13424575.72092378,,3.0,6206099.746754283,,,,-47.0%,-41.8%,13424575.72092378,,3.0,6075901.405041928,,,,-46.2%,-38.5%
+1751,Nantes,,0.0,1.2,28195222.447184302,0.0,,,-41.9%,-38.6%,,0.0,1.1,12287749.127954174,0.0,,,-48.6%,-46.3%,15755534.798751967,0.06107306938203977,0.6,14885037.613159008,0.06107306938203977,,,-24.4%,13.7%,,,0.6,17975459.99522696,,,,-23.1%,6.9%,,,-0.2,9585601.676477347,,,,-30.2%,53.9%,,,0.0,6832522.823995082,,,,-34.6%,31.5%,8942077.851577858,,0.6,9941657.68212455,,,,-6.7%,42.0%,,,-0.1,4796973.330188454,,,,-31.5%,56.8%,,,-0.2,4792800.838238681,,,,-30.2%,53.9%
+1751,Bayonne,20085182.79129176,0.04273712718332816,0.1,17816656.902903322,0.04273712718332816,,,22.6%,40.3%,8806950.52970627,0.041543802847326776,0.3,6285221.625540479,0.041543802847326776,,,13.4%,23.8%,11278232.26158549,0.043717732861288286,-0.4,12226509.503517043,0.043717732861288286,,,29.2%,49.7%,16501515.797100969,,0.3,15326359.62669531,,,,31.5%,49.0%,15033397.056981536,,0.5,10067242.971124763,,,,29.0%,37.4%,7516698.528490768,,0.4,5199326.3882153975,,,,28.9%,36.9%,8984817.2686102,,0.2,10232777.089781402,,,,31.3%,52.7%,7516698.528490768,,0.5,5039087.967216063,,,,30.1%,37.3%,7516698.528490768,,0.5,5033621.485562364,,,,29.0%,37.4%
+1751,La Rochelle,20647303.85387986,0.04393320488866381,-0.7,15673750.804663036,0.04393320488866381,,,47.4%,42.5%,8930031.69923278,0.042124396529984634,-0.5,6738826.247586925,0.042124396529984634,,,149.9%,144.1%,11717272.154647084,0.04541958012911686,-0.8,8776502.271053104,0.04541958012911686,,,-0.4%,-1.6%,15569207.777239926,,-1.3,12605741.441664513,,,,44.1%,34.1%,4521448.841936559,,1.8,3362689.115388239,,,,8.1%,-17.7%,6264287.17146678,,-1.0,4643521.15320319,,,,99.7%,86.6%,9304920.605773145,,-1.4,7672212.211312532,,,,7.4%,2.2%,2260724.4209682797,,1.8,1664191.5696673796,,,,9.3%,-17.2%,2260724.4209682797,,1.8,1681344.557694134,,,,8.1%,-17.7%
+1761,Marseille,79304676.76851721,0.2536895863167885,1.1,125302984.83882347,0.2536895863167885,179149708.18378964,129920441.19723321,-39.5%,-30.6%,47979838.72922086,0.3581372667613391,1.8,66133711.978456005,0.3581372667613391,94778604.66693728,66619572.30772985,-40.0%,-29.8%,31324838.039296355,0.17535701551428262,0.4,56774095.334157705,0.17535701551428262,79089285.17380854,59010263.421738334,-41.6%,-33.6%,73677209.60001858,,0.9,106485207.11091359,,154344974.80394235,106163091.54130344,-38.2%,-27.0%,88277865.529417,,1.5,109041197.67681886,,176693019.65956077,105621362.95374578,-35.9%,-21.0%,44138932.7647085,,1.6,56723925.8539644,,81727211.51222399,52758207.68074373,-38.0%,-24.8%,29538276.835310083,,0.1,47889339.25429823,,66440288.73407114,48115795.41865598,-40.0%,-29.9%,44138932.7647085,,1.5,54330116.89576573,,80427445.51149154,47310963.48418465,-35.4%,-19.2%,44138932.7647085,,1.5,54520598.838409334,,88346509.82978022,52810681.47687279,-35.9%,-21.0%
+1761,Rouen,,0.0,2.5,52998212.88194155,0.0,37930808.485848546,37930808.485848546,30.0%,25.3%,,0.0,3.3,30070356.62638827,0.0,16140991.81188045,16140991.81188045,53.9%,47.8%,,0.0,1.3,22607940.656955536,0.0,23105982.942496013,23105982.942496013,6.6%,3.6%,,,2.0,37705246.74531254,,19795738.078837086,19795738.078837086,97.5%,93.3%,,,3.1,34142484.4496789,,11826977.654215973,11826977.654215973,157.2%,145.3%,,,3.0,21836733.957371686,,8529849.035960712,8529849.035960712,126.8%,119.7%,,,0.1,15534649.667002313,,11937026.15782948,11937026.15782948,71.2%,70.8%,,,3.1,17071242.224839415,,5913488.827107975,5913488.827107975,157.2%,145.3%,,,3.1,17071242.224839415,,5913488.827107975,5913488.827107975,157.2%,145.3%
+1761,Bordeaux,32110333.543749347,0.102718497384277,3.7,73678316.66562364,0.102718497384277,140131723.33306727,173534423.87859166,-49.2%,-57.2%,11761993.868604999,0.08779538338048574,4.2,27623788.192136653,0.08779538338048574,40912794.64854265,32977615.942917414,-38.5%,-53.8%,20348339.67514435,0.11391037717826083,3.2,44606870.18028828,0.11391037717826083,97942324.18814848,153039901.71326128,-56.9%,-60.6%,28476337.69468049,,2.2,39514010.20880573,,72024560.88428736,84237498.11731091,-53.2%,-55.5%,14499778.648908837,,3.0,16361730.63450998,,23781743.763514515,11434573.258517921,-46.2%,-38.5%,9022853.974535158,,2.9,12341102.222884286,,15276224.035293063,8091016.303511165,-47.7%,-40.4%,19453483.720145334,,1.9,26720347.92028882,,54924959.62911325,88716309.46169995,-53.5%,-55.1%,7249889.324454418,,3.0,8414966.965187255,,12002691.676730987,5717286.629258949,-47.0%,-41.8%,7249889.324454418,,3.0,8180865.317255034,,11890871.881757235,5717286.629258949,-46.2%,-38.5%
+1761,Nantes,12148698.207461763,0.03886275498650027,1.2,31726593.633598287,0.03886275498650027,27222815.151407555,22410880.575839274,-41.9%,-38.6%,2497940.9186654636,0.01864545102352171,1.1,13682184.66983008,0.01864545102352171,14632540.015232634,10923814.718035417,-48.6%,-46.3%,9650757.2887963,0.05402511558058302,0.6,15813783.467416089,0.05402511558058302,16765897.460800594,19364839.254651994,-24.4%,13.7%,11460645.018835468,,0.6,18999296.90301836,,12452908.538105687,7748323.378908675,-23.1%,6.9%,4079634.2382257106,,-0.2,9396831.736796737,,6999068.701047673,1420480.5566499569,-30.2%,53.9%,2039817.1191128553,,0.0,6848080.088148963,,5431221.644581958,1586459.2572821279,-34.6%,31.5%,9420827.899722613,,0.6,10570197.137912655,,8926148.797640057,13638164.446490765,-6.7%,42.0%,2039817.1191128553,,-0.1,4726419.149773066,,3499534.35052383,710240.2783249771,-31.5%,56.8%,2039817.1191128553,,-0.2,4698415.868398384,,3499534.35052383,710240.2783249771,-30.2%,53.9%
+1761,Bayonne,23598481.575110856,0.07548973493667722,0.1,17990721.99833564,0.07548973493667722,17964686.37102178,17964686.37102178,22.6%,40.3%,6892727.48136392,0.051449580617348806,0.3,6458825.631017765,0.051449580617348806,6626192.449656495,6626192.449656495,13.4%,23.8%,16705754.093746938,0.09351911655919855,-0.4,11744705.014178168,0.09351911655919855,11443959.559485465,11443959.559485465,29.2%,49.7%,22004797.632015135,,0.3,15836841.029089218,,14976823.636349471,14976823.636349471,31.5%,49.0%,12331056.959006818,,0.5,10591648.365112577,,8472813.799564736,8472813.799564736,29.0%,37.4%,6168488.479503409,,0.4,5407616.215026847,,4612657.388672475,4612657.388672475,28.9%,36.9%,15836309.152511727,,0.2,10389196.702569174,,10752687.25277356,10752687.25277356,31.3%,52.7%,6165528.479503409,,0.5,5279928.816046784,,4236406.8997823605,4236406.8997823605,30.1%,37.3%,6165528.479503409,,0.5,5295824.182556288,,4236406.8997823605,4236406.8997823605,29.0%,37.4%
+1761,La Rochelle,6125383.682661703,0.01959463320204777,-0.7,14564815.922698343,0.01959463320204777,21146805.455415756,14114613.85569708,47.4%,42.5%,1736264.4450184542,0.012960047786386134,-0.5,6390613.502402433,0.012960047786386134,10823235.025898889,7714511.001187689,149.9%,144.1%,4389119.237643248,0.024570369662691233,-0.8,8080367.691723795,0.024570369662691233,10330330.608791053,6529126.479826897,-0.4%,-1.6%,5986341.283390173,,-1.3,11099815.192897126,,16071592.884861438,13096417.614494823,44.1%,34.1%,2195025.891434608,,1.8,4043381.3916491386,,4748735.994577544,8960653.883137055,8.1%,-17.7%,1640371.1957462041,,-1.0,4217394.278150701,,7762492.513491546,7463445.751207096,99.7%,86.6%,4345970.087643969,,-1.4,6696736.197304344,,8317125.657014132,5844503.81703407,7.4%,2.2%,1097512.945717304,,1.8,1997375.0220938195,,2374367.9972887714,4480326.941568519,9.3%,-17.2%,1097512.945717304,,1.8,2021690.6958245728,,2374367.9972887714,4480326.941568519,8.1%,-17.7%
+1753,Marseille,,0.0,1.1,114457340.48269352,0.0,,,-39.5%,-30.6%,67731312.8675276,0.2791135659623957,1.8,57266111.566232726,0.2791135659623957,,,-40.0%,-29.8%,,0.0,0.4,54891865.07202258,0.0,,,-41.6%,-33.6%,,,0.9,99134891.13706559,,,,-38.2%,-27.0%,,,1.5,96930305.36341442,,,,-35.9%,-21.0%,58563002.97366647,,1.6,49912429.51435353,,,,-38.0%,-24.8%,,,0.1,47461214.89452758,,,,-40.0%,-29.9%,57727467.47049629,,1.5,48036419.72959735,,,,-35.4%,-19.2%,,,1.5,48465152.68170729,,,,-35.9%,-21.0%
+1753,Rouen,,0.0,2.5,43247248.65359076,0.0,,,30.0%,25.3%,,0.0,3.3,23051906.183581144,0.0,,,53.9%,47.8%,,0.0,1.3,20437284.61097416,0.0,,,6.6%,3.6%,,,2.0,32155159.54959657,,,,97.5%,93.3%,,,3.1,26610924.22128483,,,,157.2%,145.3%,,,3.0,17137235.228125088,,,,126.8%,119.7%,,,0.1,15400118.027912853,,,,71.2%,70.8%,,,3.1,13305462.11064239,,,,157.2%,145.3%,,,3.1,13305462.11064239,,,,157.2%,145.3%
+1753,Bordeaux,128147799.04138356,0.23969938057957085,3.7,54772841.92055931,0.23969938057957085,,,-49.2%,-57.2%,31241378.94684226,0.12874241343129542,4.2,19810161.39747899,0.12874241343129542,,,-38.5%,-53.8%,96906420.09454131,0.3319246938267478,3.2,34617683.919113696,0.3319246938267478,,,-56.9%,-60.6%,77803153.54717268,,2.2,33038509.21066158,,,,-53.2%,-55.5%,15113547.163444798,,3.0,12896694.6852329,,,,-46.2%,-38.5%,11037228.183258358,,2.9,9766798.332945067,,,,-47.7%,-40.4%,66765925.36391432,,1.9,22972333.63727993,,,,-53.5%,-55.1%,7556773.581722399,,3.0,6595769.714651695,,,,-47.0%,-41.8%,7556773.581722399,,3.0,6448347.342616484,,,,-46.2%,-38.5%
+1753,Nantes,,0.0,1.2,28868559.21509939,0.0,,,-41.9%,-38.6%,,0.0,1.1,12554775.707414314,0.0,,,-48.6%,-46.3%,21939713.34752571,0.07514809264875828,0.6,15066317.20170442,0.07514809264875828,,,-24.4%,13.7%,,,0.6,18175715.501060665,,,,-23.1%,6.9%,,,-0.2,9547546.728575554,,,,-30.2%,53.9%,,,0.0,6835631.446851056,,,,-34.6%,31.5%,13170095.837917892,,0.6,10064302.031164432,,,,-6.7%,42.0%,,,-0.1,4782778.736643961,,,,-31.5%,56.8%,,,-0.2,4773773.364287784,,,,-30.2%,53.9%
+1753,Bayonne,15127865.798115622,0.028296545773120754,0.1,17851334.66763188,0.028296545773120754,,,22.6%,40.3%,5891327.052754796,0.02427753475207583,0.3,6319565.054562729,0.02427753475207583,,,13.4%,23.8%,9236538.745360825,0.03163707102255738,-0.4,12128592.771615906,0.03163707102255738,,,29.2%,49.7%,12185144.764885966,,0.3,15427122.247141954,,,,31.5%,49.0%,8354569.901693509,,0.5,10170004.640833616,,,,29.0%,37.4%,4254871.700846754,,0.4,5240332.419664141,,,,28.9%,36.9%,7930273.064039211,,0.2,10263871.464072319,,,,31.3%,52.7%,4177284.9508467545,,0.5,5086360.821886447,,,,30.1%,37.3%,4177284.9508467545,,0.5,5085002.3204168165,,,,29.0%,37.4%
+1753,La Rochelle,17274754.971163396,0.03231228391924649,-0.7,15445406.763611412,0.03231228391924649,,,47.4%,42.5%,8358230.425187,0.03444338224584738,-0.5,6667697.945334481,0.03444338224584738,,,149.9%,144.1%,8916524.545976397,0.030540955666657738,-0.8,8632635.429806031,0.030540955666657738,,,-0.4%,-1.6%,13689581.505469998,,-1.3,12289037.3904649,,,,44.1%,34.1%,4884924.281235419,,1.8,3488978.683931822,,,,8.1%,-17.7%,6117667.016289091,,-1.0,4554983.24201476,,,,99.7%,86.6%,7571914.489180908,,-1.4,7466363.395917773,,,,7.4%,2.2%,2442462.1406177096,,1.8,1726054.7887113867,,,,9.3%,-17.2%,2442462.1406177096,,1.8,1744489.3419659138,,,,8.1%,-17.7%
 1774,Marseille,154534027.9831894,0.2514664924274066,1.1,145161947.51141036,0.2514664924274066,,,-39.5%,-30.6%,81034010.6166285,0.2741315292831629,1.8,83565373.21178752,0.2741315292831629,,,-40.0%,-29.8%,73500017.3665609,0.23045914228163403,0.4,59971354.17137792,0.23045914228163403,,,-41.6%,-33.6%,124081140.41220024,,0.9,119609656.18662284,,,,-38.2%,-27.0%,117489717.19887938,,1.5,132031798.81116514,,,,-35.9%,-21.0%,63014959.7999412,,1.6,69830850.76302019,,,,-38.0%,-24.8%,61066180.612259045,,0.1,48593293.51355787,,,,-40.0%,-29.9%,58744858.59943969,,1.5,66363518.451480605,,,,-35.4%,-19.2%,58744858.59943969,,1.5,66015899.40558245,,,,-35.9%,-21.0%
 1774,Rouen,79898324.58004877,0.1300150633176852,2.5,73748498.22748713,0.1300150633176852,,,30.0%,25.3%,54178534.07285963,0.18328161578942337,3.3,46314304.71238606,0.18328161578942337,,,53.9%,47.8%,25719790.507189132,0.08064434638687303,1.3,26637744.457118824,0.08064434638687303,,,6.6%,3.6%,60262159.94954714,,2.0,48839628.80166634,,,,97.5%,93.3%,71223644.22090293,,3.1,51189072.262110874,,,,157.2%,145.3%,43916294.36045147,,3.0,32375310.048422195,,,,126.8%,119.7%,16345865.589095673,,0.1,15755774.695080794,,,,71.2%,70.8%,35611822.11045147,,3.1,25594536.13105539,,,,157.2%,145.3%,35611822.11045147,,3.1,25594536.13105539,,,,157.2%,145.3%
 1774,Bordeaux,124391553.8938669,0.20241695731045184,3.7,119288376.28011872,0.20241695731045184,,,-49.2%,-57.2%,60394667.57609494,0.2043102946182672,4.2,47416060.715306796,0.2043102946182672,,,-38.5%,-53.8%,63996886.31777196,0.2006620958459654,3.2,67347322.8004462,0.2006620958459654,,,-56.9%,-60.6%,47560379.24970479,,2.2,52852244.895891,,,,-53.2%,-55.5%,35272226.88367971,,3.0,24086534.587108064,,,,-46.2%,-38.5%,22579105.591838352,,2.9,18049150.226238813,,,,-47.7%,-40.4%,24981273.65786644,,1.9,34158769.93822405,,,,-53.5%,-55.1%,17636113.441839855,,3.0,12501328.821147185,,,,-47.0%,-41.8%,17636113.441839855,,3.0,12043267.293554181,,,,-46.2%,-38.5%
 1774,Nantes,50732127.234810024,0.08255418082097989,1.2,36986713.472020656,0.08255418082097989,,,-41.9%,-38.6%,28423559.14010851,0.09615461058210863,1.1,15734157.501014981,0.09615461058210863,,,-48.6%,-46.3%,22308568.094701517,0.06994846603907541,0.6,17108321.177567575,0.06994846603907541,,,-24.4%,13.7%,17957623.083509676,,0.6,20417957.768974457,,,,-23.1%,6.9%,9076830.996900218,,-0.2,9156977.435206054,,,,-30.2%,53.9%,8220381.153757415,,0.0,6868357.50098992,,,,-34.6%,31.5%,9737241.929752262,,0.6,11447078.306209192,,,,-6.7%,42.0%,4538415.498450109,,-0.1,4636247.8118421035,,,,-31.5%,56.8%,4538415.498450109,,-0.2,4578488.717603035,,,,-30.2%,53.9%
 1774,Bayonne,13806653.202568356,0.022466965355935505,0.1,18219551.469697945,0.022466965355935505,,,22.6%,40.3%,5343625.9829942705,0.018077056182813068,0.3,6691699.238555493,0.018077056182813068,,,13.4%,23.8%,8463027.219574085,0.026535803174061547,-0.4,11146630.986611009,0.026535803174061547,,,29.2%,49.7%,12716619.025744345,,0.3,16525970.237920968,,,,31.5%,49.0%,9486904.817442743,,0.5,11314424.24309061,,,,29.0%,37.4%,4765611.408721372,,0.4,5690917.322448082,,,,28.9%,36.9%,7951007.6170229735,,0.2,10596122.270604204,,,,31.3%,52.7%,4743452.408721372,,0.5,5610312.249942833,,,,30.1%,37.3%,4743452.408721372,,0.5,5657212.121545314,,,,29.0%,37.4%
 1774,La Rochelle,21859271.800731614,0.03557064083869776,-0.7,13239655.397360122,0.03557064083869776,,,47.4%,42.5%,10279879.885690115,0.03477600543855082,-0.5,5964696.283863268,0.03477600543855082,,,149.9%,144.1%,11579391.915041497,0.03630715780071951,-0.8,7257276.562925543,0.03630715780071951,,,-0.4%,-1.6%,18616683.3785916,,-1.3,9407783.33724409,,,,44.1%,34.1%,13664799.809120934,,1.8,5138307.548279963,,,,8.1%,-17.7%,8172829.335032317,,-1.0,3721345.6760573396,,,,99.7%,86.6%,10443854.043559285,,-1.4,5611623.8324321825,,,,7.4%,2.2%,6832399.904560467,,1.8,2532169.658167182,,,,9.3%,-17.2%,6832399.904560467,,1.8,2569153.7741399864,,,,8.1%,-17.7%
+1770,Marseille,151567891.1033504,0.23796213791096818,1.1,138737512.37419125,0.23796213791096818,,,-39.5%,-30.6%,88861607.23503114,0.26233363587958486,1.8,77761343.39885685,0.26233363587958486,,,-40.0%,-29.8%,62706283.86831925,0.21027832791921208,0.4,58968860.77425385,0.21027832791921208,,,-41.6%,-33.6%,124001305.58759302,,0.9,115407722.09855165,,,,-38.2%,-27.0%,138117320.9658601,,1.5,124483853.59632729,,,,-35.9%,-21.0%,73671184.88459273,,1.6,65504109.622463554,,,,-38.0%,-24.8%,50330120.70300029,,0.1,48375597.068024196,,,,-40.0%,-29.9%,69058660.48293005,,1.5,62401409.439780794,,,,-35.4%,-19.2%,69058660.48293005,,1.5,62241926.79816376,,,,-35.9%,-21.0%
+1770,Rouen,49023498.41898596,0.0769670700485124,2.5,66619567.674024835,0.0769670700485124,,,30.0%,25.3%,32609788.676224675,0.0962692966611852,3.3,40550786.40914294,0.0962692966611852,,,53.9%,47.8%,16413709.742761288,0.05504149228340543,1.3,25326696.29332992,0.05504149228340543,,,6.6%,3.6%,30513479.967916988,,2.0,45102103.30004735,,,,97.5%,93.3%,32102338.629373036,,3.1,45191803.93713323,,,,157.2%,145.3%,20786020.31468678,,3.0,28680748.003553424,,,,126.8%,119.7%,9727459.653230209,,0.1,15687403.044739531,,,,71.2%,70.8%,16051169.314686518,,3.1,22595901.968566574,,,,157.2%,145.3%,16051169.314686518,,3.1,22595901.968566574,,,,157.2%,145.3%
+1770,Bordeaux,213694561.32338905,0.33550123513815977,3.7,102851568.04906753,0.33550123513815977,,,-49.2%,-57.2%,120965561.67024802,0.3571096291927337,4.2,40153911.695268184,0.3571096291927337,,,-38.5%,-53.8%,92728999.65314104,0.3109560604425327,3.2,59329196.16813666,0.3109560604425327,,,-56.9%,-60.6%,92374263.95316303,,2.2,48327920.251229994,,,,-53.2%,-55.5%,66916100.588454366,,3.0,21384490.68153178,,,,-46.2%,-38.5%,46825406.99482773,,2.9,16056685.280039357,,,,-47.7%,-40.4%,45548856.9583353,,1.9,31672600.764338035,,,,-53.5%,-55.1%,33458050.294227183,,3.0,11067835.94097283,,,,-47.0%,-41.8%,33458050.294227183,,3.0,10692245.340765946,,,,-46.2%,-38.5%
+1770,Nantes,49078708.3759675,0.07705374988090738,1.2,35281462.11690149,0.07705374988090738,,,-41.9%,-38.6%,31402321.577535108,0.09270466122344877,1.1,15071977.894141765,0.09270466122344877,,,-48.6%,-46.3%,17676386.798432395,0.059275734907733836,0.6,16699099.56715334,0.059275734907733836,,,-24.4%,13.7%,25811000.358326323,,0.6,19970516.376713756,,,,-23.1%,6.9%,27769979.1473788,,-0.2,9230119.317150965,,,,-30.2%,53.9%,16681840.624508172,,0.0,6862111.9102567,,,,-34.6%,31.5%,9129159.733818153,,0.6,11169788.270930488,,,,-6.7%,42.0%,13884989.5736894,,-0.1,4663808.070696755,,,,-31.5%,56.8%,13884989.5736894,,-0.2,4615059.6585754985,,,,-30.2%,53.9%
+1770,Bayonne,14311781.78460992,0.022469549229650436,0.1,18148834.108221862,0.022469549229650436,,,22.6%,40.3%,5648601.76058723,0.01667557321545393,0.3,6619165.311582235,0.01667557321545393,,,13.4%,23.8%,8663180.02402269,0.02905098018150885,-0.4,11327335.775695983,0.02905098018150885,,,29.2%,49.7%,12634141.669589087,,0.3,16310795.704026746,,,,31.5%,49.0%,9074784.10517896,,0.5,11086928.772435987,,,,29.0%,37.4%,4564002.05259678,,0.4,5602201.99756737,,,,28.9%,36.9%,8070139.616992308,,0.2,10532017.665642763,,,,31.3%,52.7%,4537392.05258948,,0.5,5506511.9011617,,,,30.1%,37.3%,4537392.05258948,,0.5,5543464.386217993,,,,29.0%,37.4%
+1770,La Rochelle,10849680.535732154,0.017034037731470233,-0.7,13634017.792166917,0.017034037731470233,,,47.4%,42.5%,4675885.09933538,0.013803958506168631,-0.5,6092632.982181558,0.013803958506168631,,,149.9%,144.1%,6173795.436396774,0.02070311460342599,-0.8,7501183.887087909,0.02070311460342599,,,-0.4%,-1.6%,7075367.338507866,,-1.3,9898932.56651135,,,,44.1%,34.1%,4327096.426158779,,1.8,4773060.057997743,,,,8.1%,-17.7%,2830310.11217157,,-1.0,3867419.681634663,,,,99.7%,86.6%,4245057.226336296,,-1.4,5925316.010673673,,,,7.4%,2.2%,2163548.2130793897,,1.8,2353912.3191079902,,,,9.3%,-17.2%,2163548.2130793897,,1.8,2386530.028998875,,,,8.1%,-17.7%
+1748,Marseille,,0.0,1.1,108160838.83336072,0.0,166379999.61753914,166379999.61753914,-39.5%,-30.6%,40122103.95795721,0.29481119863438454,1.8,52338279.50441622,0.29481119863438454,90349504.67389138,90349504.67389138,-40.0%,-29.8%,,0.0,0.4,53747292.27892585,0.0,70507480.88629614,70507480.88629614,-41.6%,-33.6%,,,0.9,94800868.884383,,153123497.42145857,153123497.42145857,-38.2%,-27.0%,,,1.5,90053933.20286769,,146422140.39803717,146422140.39803717,-35.9%,-21.0%,36626721.924818955,,1.6,46077109.60310916,,79216449.5684532,79216449.5684532,-38.0%,-24.8%,,,0.1,47195582.93725034,,66700527.03479432,66700527.03479432,-40.0%,-29.9%,36420566.623689994,,1.5,44478678.50866976,,65254319.91993697,65254319.91993697,-35.4%,-19.2%,,,1.5,45026966.60143376,,73211070.19901843,73211070.19901843,-35.9%,-21.0%
+1748,Rouen,,0.0,2.5,38086342.58578964,0.0,,,30.0%,25.3%,,0.0,3.3,19523694.74730237,0.0,,,53.9%,47.8%,,0.0,1.3,19187772.50721131,0.0,,,6.6%,3.6%,,,2.0,29109263.665746696,,,,97.5%,93.3%,,,3.1,22772619.093927357,,,,157.2%,145.3%,,,3.0,14728598.713397296,,,,126.8%,119.7%,,,0.1,15316628.026665144,,,,71.2%,70.8%,,,3.1,11386309.546963658,,,,157.2%,145.3%,,,3.1,11386309.546963658,,,,157.2%,145.3%
+1748,Bordeaux,32208934.610555325,0.10193106356926113,3.7,45507320.29357612,0.10193106356926113,166480179.7911622,166480179.7911622,-49.2%,-57.2%,12264367.507695038,0.09011673189484111,4.2,16093147.818956075,0.09011673189484111,40905167.30418812,40905167.30418812,-38.5%,-53.8%,19944567.102860287,0.11086893588643132,3.2,29544943.80091244,0.11086893588643132,138603523.43777716,138603523.43777716,-56.9%,-60.6%,19988647.22155146,,2.2,29541924.01585181,,117311500.25667997,117311500.25667997,-53.2%,-55.5%,15102973.890862776,,3.0,11114352.228134388,,75083990.44091326,75083990.44091326,-46.2%,-38.5%,8336408.944307788,,2.9,8438225.742853617,,22722825.43646227,22722825.43646227,-47.7%,-40.4%,11652238.277243672,,1.9,20901718.483203776,,100014789.58946195,100014789.58946195,-53.5%,-55.1%,7551486.945431388,,3.0,5664331.371350552,,35169584.62379305,35169584.62379305,-47.0%,-41.8%,7551486.945431388,,3.0,5557176.114067262,,37541995.220452294,37541995.220452294,-46.2%,-38.5%
+1748,Nantes,,0.0,1.2,27214549.472013187,0.0,49302112.42904861,49302112.42904861,-41.9%,-38.6%,,0.0,1.1,11897820.225026764,0.0,50187204.114292435,50187204.114292435,-48.6%,-46.3%,,0.0,0.6,14617199.721631464,0.0,12476886.259844212,12476886.259844212,-24.4%,13.7%,,,0.6,17679206.064259272,,34279025.8367247,34279025.8367247,-23.1%,6.9%,,,-0.2,9642968.688574005,,221555863.31853095,221555863.31853095,-30.2%,53.9%,,,0.0,6827862.540198768,,53159235.62927847,53159235.62927847,-34.6%,31.5%,,,0.6,9760487.745919598,,7501255.208370965,7501255.208370965,-6.7%,42.0%,,,-0.1,4818344.248614619,,110777931.65925898,110777931.65925898,-31.5%,56.8%,,,-0.2,4821484.344287011,,110777931.65925898,110777931.65925898,-30.2%,53.9%
+1748,Bayonne,,0.0,0.1,17764766.52346276,0.0,,,22.6%,40.3%,,0.0,0.3,6234056.1111197295,0.0,,,13.4%,23.8%,15283047.050639473,0.08495622666904923,-0.4,12374868.786429578,0.08495622666904923,,,29.2%,49.7%,,,0.3,15176448.351887867,,,,31.5%,49.0%,,,0.5,9915044.078243649,,,,29.0%,37.4%,,,0.4,5138418.197304254,,,,28.9%,36.9%,11998852.330056598,,0.2,10186312.064754985,,,,31.3%,52.7%,,,0.5,4969001.200032175,,,,30.1%,37.3%,,,0.5,4957522.039121815,,,,29.0%,37.4%
+1748,La Rochelle,23030805.99066665,0.07288519716254867,-0.7,16022612.106987804,0.07288519716254867,5605692.8009478105,5605692.8009478105,47.4%,42.5%,8188965.940917931,0.06017129279032662,-0.5,6846943.916922576,0.06017129279032662,734949.1250001653,734949.1250001653,149.9%,144.1%,14841840.04974872,0.08250362138350326,-0.8,8996810.506989026,0.08250362138350326,8785777.044530276,8785777.044530276,-0.4%,-1.6%,17366464.300394785,,-1.3,13096166.535714643,,4432533.922023923,4432533.922023923,44.1%,34.1%,2395405.608495061,,1.8,3181773.9449650906,,710791.7701116788,710791.7701116788,8.1%,-17.7%,4638988.30455933,,-1.0,4779565.255604671,,488243.6632729781,488243.6632729781,99.7%,86.6%,12727475.995835455,,-1.4,7991675.321695464,,6909290.400946994,6909290.400946994,7.4%,2.2%,1197702.8042475304,,1.8,1575529.0985407073,,355395.88505583873,355395.88505583873,9.3%,-17.2%,1197702.8042475304,,1.8,1590886.972482548,,355395.88505583873,355395.88505583873,8.1%,-17.7%
+1780,Marseille,95011300.43057716,0.2102003969982643,1.1,155360678.9809802,0.2102003969982643,177858080.09946787,165796396.3765717,-39.5%,-30.6%,65428244.06186197,0.3026626953454921,1.8,93093693.34256062,0.3026626953454921,102971661.22121336,94417266.65641995,-40.0%,-29.8%,29583056.368715186,0.12544336869302708,0.4,61507139.82008072,0.12544336869302708,77778157.35447113,73468061.76107332,-41.6%,-33.6%,84088793.57815945,,0.9,126201146.81635578,,143476981.071206,130619501.17687808,-38.2%,-27.0%,115675003.22457734,,1.5,144220439.35275578,,149928846.00842616,136703959.3214379,-35.9%,-21.0%,59098273.96229381,,1.6,76862677.90173697,,83650388.55865665,75361773.32149582,-38.0%,-24.8%,24990519.615865637,,0.1,48921676.425342634,,62535817.585945085,57482324.882127084,-40.0%,-29.9%,57837501.61228867,,1.5,72783328.0021056,,77759143.22072354,70835665.74953486,-35.4%,-19.2%,57837501.61228867,,1.5,72110219.67637776,,74964423.00421321,68351979.66071858,-35.9%,-21.0%
+1780,Rouen,,0.0,2.5,85897443.31303592,0.0,70366163.10957097,79867615.88042514,30.0%,25.3%,,0.0,3.3,56531297.068402745,0.0,45316523.92865779,52904256.150025964,53.9%,47.8%,,0.0,1.3,28732658.22561316,0.0,24646877.070586648,26959325.78478123,6.6%,3.6%,,,2.0,55034584.66046734,,42283872.71888897,46309814.64162124,97.5%,93.3%,,,3.1,61709727.70656949,,44798943.21786077,57000171.8897382,157.2%,145.3%,,,3.0,38828367.370374836,,29797286.740127616,34846432.707909815,126.8%,119.7%,,,0.1,15858891.30668527,,12575181.644967714,12640433.564962285,71.2%,70.8%,,,3.1,30854863.853284687,,22399471.608930424,28500085.94486925,157.2%,145.3%,,,3.1,30854863.853284687,,22399471.608930424,28500085.94486925,157.2%,145.3%
+1780,Bordeaux,,0.0,3.7,148997486.43266582,0.0,153120795.8909721,228695701.79638478,-49.2%,-57.2%,32531869.528393723,0.1504882708877534,4.2,60844578.44359869,0.1504882708877534,68344272.59058487,199895051.14215633,-38.5%,-53.8%,,0.0,3.2,81451323.2643818,0.0,86332867.48406138,84533072.09778437,-56.9%,-60.6%,,,2.2,60445146.92518969,,61478007.657121785,61317497.059465215,-53.2%,-55.5%,,,3.0,28793034.39626824,,27146565.087033257,86330546.09106256,-46.2%,-38.5%,18009549.7860847,,2.9,21510874.009813897,,25347720.9773876,61041559.06664655,-47.7%,-40.4%,,,1.9,38258678.816267155,,36698847.06924672,25353646.535847593,-53.5%,-55.1%,12413681.046296002,,3.0,15007086.19259742,,15557166.656016389,51468113.244374044,-47.0%,-41.8%,,,3.0,14396517.198134195,,13573282.543516653,43165273.0455312,-46.2%,-38.5%
+1780,Nantes,,0.0,1.2,39700364.608895436,0.0,50817136.664814845,54520712.405822225,-41.9%,-38.6%,,0.0,1.1,16782372.64936562,0.0,18559389.425348256,21640040.670996133,-48.6%,-46.3%,,0.0,0.6,17741033.0775604,0.0,18681046.70635985,6011515.008847204,-24.4%,13.7%,,,0.6,21107986.6689656,,23137265.027346533,16884780.459455322,-23.1%,6.9%,,,-0.2,9048349.917007957,,7797704.880398656,22557297.654288273,-30.2%,53.9%,,,0.0,6877736.547069685,,6623468.5609585615,9247343.134184109,-34.6%,31.5%,,,0.6,11875973.583838856,,11534020.160000216,3091434.859548668,-6.7%,42.0%,,,-0.1,4595212.493153747,,4059239.2366264793,9137970.065656086,-31.5%,56.8%,,,-0.2,4524174.958503986,,3898852.4401993207,11278648.827144116,-30.2%,53.9%
+1780,Bayonne,21189102.21787706,0.046878188994886744,0.1,18326144.5070385,0.046878188994886744,14578417.209688835,9768777.207313351,22.6%,40.3%,8029685.778411877,0.037144300222602414,0.3,6801993.170243185,0.037144300222602414,5182287.291909951,4198744.616755915,13.4%,23.8%,13159416.439465184,0.05580091210408651,-0.4,10880964.615766058,0.05580091210408651,9291899.859900393,5734496.250215612,29.2%,49.7%,19624503.716763504,,0.3,16854066.12622462,,13349802.048229951,9061163.099810928,31.5%,49.0%,13661573.939025719,,0.5,11664449.87406238,,8721469.16006067,7292652.842231999,29.0%,37.4%,6874541.969512859,,0.4,5826631.394129358,,4351782.479845685,3719743.729983517,28.9%,36.9%,12749961.747250644,,0.2,10693011.510293104,,8960200.762544202,5469280.730532648,31.3%,52.7%,6830786.969512859,,0.5,5769693.057950459,,4335816.186037538,3755229.339180913,30.1%,37.3%,6830786.969512859,,0.5,5832224.93703118,,4360734.580030312,3646326.4211159665,29.0%,37.4%
+1780,La Rochelle,7694879.291011558,0.017023940041807996,-0.7,12669396.234794552,0.017023940041807996,14205047.622171113,30256841.807577323,47.4%,42.5%,3697571.203999307,0.017104491842638927,-0.5,5777810.730029467,0.017104491842638927,6268741.397501469,11315019.808775969,149.9%,144.1%,3997308.087012251,0.016950100959445737,-0.8,6906205.007297434,0.016950100959445737,7964362.342377235,15893884.862093108,-0.4%,-1.6%,4534275.061012156,,-1.3,8716371.234782198,,10195979.336607676,28503486.098193467,44.1%,34.1%,3082827.7191817546,,1.8,5739246.6438288735,,6808054.017476993,28855398.205552198,8.1%,-17.7%,2086377.8581137871,,-1.0,3512514.1241753977,,3919022.2829681407,10636643.184545847,99.7%,86.6%,2447897.2028983696,,-1.4,5171947.427449631,,6138070.634358033,15840680.734483471,7.4%,2.2%,1541413.8595908773,,1.8,2825182.963356145,,3242540.5680037225,13170261.200398115,9.3%,-17.2%,1541413.8595908773,,1.8,2869623.3219144414,,3404027.0087384963,14427699.102776071,8.1%,-17.7%
 1758,Marseille,,0.0,1.1,121120388.22622897,0.0,168481512.69769582,135582241.13426584,-39.5%,-30.6%,36837276.13591482,0.29294446307754707,1.8,62657916.25113535,0.29294446307754707,87247448.20310876,69248627.99456328,-40.0%,-29.8%,,0.0,0.4,56060812.05818354,0.0,76542630.49125656,62833163.68624761,-41.6%,-33.6%,,,0.9,103667052.38475734,,144858066.30174312,112453184.2496333,-38.2%,-27.0%,,,1.5,104331746.14016314,,159746383.2608438,112835507.2133093,-35.9%,-21.0%,33598548.635578014,,1.6,54066989.91069541,,75245363.81711917,56494010.203237176,-38.0%,-24.8%,,,0.1,47728341.91410394,,64269530.80512364,51681290.13741663,-40.0%,-29.9%,33579598.635128014,,1.5,51878736.01029496,,73539130.66875932,51992870.14349262,-35.4%,-19.2%,,,1.5,52165873.07008147,,79873191.63042176,56417753.60665455,-35.9%,-21.0%
 1758,Rouen,,0.0,2.5,49107485.495426446,0.0,42683256.85514293,42683256.85514293,30.0%,25.3%,,0.0,3.3,27217715.989441685,0.0,19826215.17808375,19826215.17808375,53.9%,47.8%,,0.0,1.3,21768165.22673407,0.0,23390402.46364891,23390402.46364891,6.6%,3.6%,,,2.0,35519767.78020285,,25074852.293490905,25074852.293490905,97.5%,93.3%,,,3.1,31096172.337058913,,17405973.277499244,17405973.277499244,157.2%,145.3%,,,3.0,19939767.317915346,,11772899.609895226,11772899.609895226,126.8%,119.7%,,,0.1,15484063.1280437,,13607981.399804043,13607981.399804043,71.2%,70.8%,,,3.1,15548086.168529538,,8702986.638749853,8702986.638749853,157.2%,145.3%,,,3.1,15548086.168529538,,8702986.638749853,8702986.638749853,157.2%,145.3%
 1758,Bordeaux,31759352.620401185,0.10874004833368103,3.7,65924870.827388026,0.10874004833368103,117838820.91855362,135033818.7876812,-49.2%,-57.2%,4681610.656391415,0.03723000351639998,4.2,24385688.804268867,0.03723000351639998,36150686.17847423,31348121.470215287,-38.5%,-53.8%,27077741.96400977,0.1628066290720129,3.2,40561391.756198,0.1628066290720129,80218895.37782186,106866909.09555627,-56.9%,-60.6%,30521420.05424381,,2.2,36948950.59229257,,62688313.28758476,69167804.5493837,-53.2%,-55.5%,8346756.944408504,,3.0,14964860.78451663,,21370831.8695789,13183459.179793822,-46.2%,-38.5%,4269072.852204252,,2.9,11304550.575363059,,14267494.318810713,9402716.238783948,-47.7%,-40.4%,26252347.20203956,,1.9,25248072.935561508,,46753115.569438234,63626532.216367275,-53.5%,-55.1%,4173378.472204252,,3.0,7680373.070819082,,10751724.740867143,6591729.589896899,-47.0%,-41.8%,4173378.472204252,,3.0,7482430.392258355,,10685415.934789432,6591729.589896899,-46.2%,-38.5%
 1758,Nantes,6539151.7942396235,0.0223892372954141,1.2,30623094.16559498,0.0223892372954141,29754044.344740715,26092750.98771311,-41.9%,-38.6%,3041718.790162194,0.02418894042353497,1.1,13248005.944141423,0.02418894042353497,15978676.427382138,13057152.194547527,-48.6%,-46.3%,3497433.0040774294,0.021028536225652483,0.6,15529233.939825948,0.021028536225652483,17394901.177344114,19140281.633571852,-24.4%,13.7%,5707331.839890473,,0.6,18686169.094626542,,14366181.0680274,10439103.000331467,-23.1%,6.9%,4734808.073083548,,-0.2,9453069.016219504,,8386305.020316265,2834308.481244497,-30.2%,53.9%,2551087.235807074,,0.0,6843409.193152668,,6402658.648251858,2783780.2733532134,-34.6%,31.5%,3156244.6040833993,,0.6,10377573.130691743,,9548645.790188584,12610484.97588453,-6.7%,42.0%,2367404.036541774,,-0.1,4747475.743409306,,4193152.5101581845,1417154.2406222457,-31.5%,56.8%,2367404.036541774,,-0.2,4726534.508109751,,4193152.5101581845,1417154.2406222457,-30.2%,53.9%
 1758,Bayonne,15894623.246832106,0.05442120060709035,0.1,17938324.660496626,0.05442120060709035,17654904.461511463,17654904.461511463,22.6%,40.3%,4042965.1683435,0.03215124419383727,0.3,6406246.874745753,0.03215124419383727,6770492.110623713,6770492.110623713,13.4%,23.8%,11851658.078488607,0.0712588406831501,-0.4,11887217.970424717,0.0712588406831501,10928232.575599086,10928232.575599086,29.2%,49.7%,14635349.214256875,,0.3,15681936.597415933,,14759981.558543514,14759981.558543514,31.5%,49.0%,7109123.3390406,,0.5,10431521.390966872,,9385534.837216018,9385534.837216018,29.0%,37.4%,3554561.6695203,,0.4,5344267.985620509,,4988224.497093784,4988224.497093784,28.9%,36.9%,11080787.544736575,,0.2,10342021.406893937,,9921561.011772698,9921561.011772698,31.3%,52.7%,3554561.6695203,,0.5,5206492.284657509,,4692767.418608,4692767.418608,30.1%,37.3%,3554561.6695203,,0.5,5215760.695483416,,4692767.418608,4692767.418608,29.0%,37.4%
 1758,La Rochelle,7892832.619919436,0.027024071014230017,-0.7,14888994.90922411,0.027024071014230017,20791080.818215717,15831112.950460147,47.4%,42.5%,2489366.1284004296,0.0197964154894914,-0.5,6493144.44950204,0.0197964154894914,10470326.853373151,8337557.097408553,149.9%,144.1%,5403466.491519006,0.032488682621950565,-0.8,8283201.519699755,0.032488682621950565,10303070.405372174,7558818.3616327895,-0.4%,-1.6%,7586784.620068386,,-1.3,11531652.378762517,,16016204.294508496,13954470.860519515,44.1%,34.1%,2525963.4521148596,,1.8,3825844.4715073155,,4739491.705523677,7280930.355910096,8.1%,-17.7%,2354563.6284004296,,-1.0,4340953.878745688,,7580454.801024504,7388461.036279878,99.7%,86.6%,5232220.991667957,,-1.4,6975581.478962554,,8423213.82912079,6638322.831474954,7.4%,2.2%,1262981.7260574298,,1.8,1890961.6689358435,,2369745.852761838,3640465.177955041,9.3%,-17.2%,1262981.7260574298,,1.8,1912922.235753661,,2369745.852761838,3640465.177955041,8.1%,-17.7%
+1742,Marseille,,0.0,1.1,101060565.08314164,0.0,,,-39.5%,-30.6%,52176220.79880458,0.2966922991564212,1.8,46981355.05222049,0.2966922991564212,,,-40.0%,-29.8%,,0.0,0.4,52405264.01391359,0.0,,,-41.6%,-33.6%,,,0.9,89849415.94829157,,,,-38.2%,-27.0%,,,1.5,82443118.63253199,,,,-35.9%,-21.0%,44357692.08332365,,1.6,41861718.224279135,,,,-38.0%,-24.8%,,,0.1,46878786.29247541,,,,-40.0%,-29.9%,40873649.5817131,,1.5,40555463.49601087,,,,-35.4%,-19.2%,,,1.5,41221559.31626592,,,,-35.9%,-21.0%
+1742,Rouen,,0.0,2.5,32699582.901943095,0.0,,,30.0%,25.3%,,0.0,3.3,15995145.9550637,0.0,,,53.9%,47.8%,,0.0,1.3,17788781.55773273,0.0,,,6.6%,3.6%,,,2.0,25832585.83481475,,,,97.5%,93.3%,,,3.1,18890202.36711358,,,,157.2%,145.3%,,,3.0,12280788.04798911,,,,126.8%,119.7%,,,0.1,15217037.282723915,,,,71.2%,70.8%,,,3.1,9445101.183556773,,,,157.2%,145.3%,,,3.1,9445101.183556773,,,,157.2%,145.3%
+1742,Bordeaux,52762324.43943313,0.13614507921673594,3.7,36433462.58148543,0.13614507921673594,,,-49.2%,-57.2%,19306091.253180537,0.10978120902464905,4.2,12541358.549987776,0.10978120902464905,,,-38.5%,-53.8%,33456233.186252587,0.15804714754216567,3.2,24428981.47673444,0.15804714754216567,,,-56.9%,-60.6%,34951524.60524518,,2.2,25830973.737462133,,,,-53.2%,-55.5%,13994372.040238822,,3.0,9297603.915999865,,,,-46.2%,-38.5%,10343686.270788386,,2.9,7080270.378888162,,,,-47.7%,-40.4%,24607838.334456794,,1.9,18661830.85960899,,,,-53.5%,-55.1%,6997186.020119411,,3.0,4718548.831959281,,,,-47.0%,-41.8%,6997186.020119411,,3.0,4648801.957999957,,,,-46.2%,-38.5%
+1742,Nantes,58012489.230124384,0.1496923235605687,1.2,25354345.06729807,0.1496923235605687,,,-41.9%,-38.6%,36260581.93065922,0.20619039204164727,1.1,11154690.772905042,0.20619039204164727,,,-48.6%,-46.3%,21751907.29946517,0.10275594634768119,0.6,14095895.456653412,0.10275594634768119,,,-24.4%,13.7%,38714571.65784699,,0.6,17101265.434271403,,,,-23.1%,6.9%,46371799.01820723,,-0.2,9758734.741645494,,,,-30.2%,53.9%,25612612.794653185,,0.0,6818551.506408441,,,,-34.6%,31.5%,13101958.863193799,,0.6,9407992.258115225,,,,-6.7%,42.0%,23185899.509103615,,-0.1,4861372.137332873,,,,-31.5%,56.8%,23185899.509103615,,-0.2,4879367.370822747,,,,-30.2%,53.9%
+1742,Bayonne,,0.0,0.1,17661438.71107684,0.0,,,22.6%,40.3%,,0.0,0.3,6132971.246485496,0.0,,,13.4%,23.8%,,0.0,-0.4,12677009.873756537,0.0,,,29.2%,49.7%,,,0.3,14881010.428124215,,,,31.5%,49.0%,,,0.5,9617514.439291934,,,,29.0%,37.4%,,,0.4,5018734.00786677,,,,28.9%,36.9%,,,0.2,10094014.02222151,,,,31.3%,52.7%,,,0.5,4831738.538345051,,,,30.1%,37.3%,,,0.5,4808757.219645966,,,,29.0%,37.4%
+1742,La Rochelle,,0.0,-0.7,16743802.066865262,0.0,,,47.4%,42.5%,,0.0,-0.5,7068411.002947493,0.0,,,149.9%,144.1%,,0.0,-0.8,9454156.365827926,0.0,,,-0.4%,-1.6%,,,-1.3,14134998.842732115,,,,44.1%,34.1%,,,1.8,2848620.0529321805,,,,8.1%,-17.7%,,,-1.0,5063727.537765816,,,,99.7%,86.6%,,,-1.4,8671061.785792515,,,,7.4%,2.2%,,,1.8,1412123.4024946003,,,,9.3%,-17.2%,,,1.8,1424310.0264660926,,,,8.1%,-17.7%
+1757,Marseille,,0.0,1.1,119757448.19924584,0.0,165068537.12571332,137523816.31666926,-39.5%,-30.6%,53358505.38187696,0.3626710159482725,1.8,61540397.53241262,0.3626710159482725,84872476.49264306,70147837.01797822,-40.0%,-29.8%,,0.0,0.4,55825047.96835137,0.0,75712100.35260348,64161728.00815517,-41.6%,-33.6%,,,0.9,102744340.06137924,,141827162.22616228,114631636.11099684,-38.2%,-27.0%,,,1.5,102807570.67456913,,154466716.47692856,115348103.42296164,-35.9%,-21.0%,49250171.02619471,,1.6,53209293.84011222,,73201070.91774376,57797163.83497492,-38.0%,-24.8%,,,0.1,47674796.501979776,,63561821.66443849,52927563.94560822,-40.0%,-29.9%,49247496.02619471,,1.5,51086439.4841047,,71376716.21958092,53654290.816327535,-35.4%,-19.2%,,,1.5,51403785.33728447,,77233358.23846413,57674051.711480714,-35.9%,-21.0%
+1757,Rouen,,0.0,2.5,47875117.65730987,0.0,44396223.93874587,44396223.93874587,30.0%,25.3%,,0.0,3.3,26328293.52347641,0.0,21232917.944641374,21232917.944641374,53.9%,47.8%,,0.0,1.3,21495230.11447457,0.0,23485984.857401334,23485984.857401334,6.6%,3.6%,,,2.0,34819796.451909944,,27130675.78929834,27130675.78929834,97.5%,93.3%,,,3.1,30142379.90631796,,19798843.578453537,19798843.578453537,157.2%,145.3%,,,3.0,19344798.95066017,,13107830.17299884,13107830.17299884,126.8%,119.7%,,,0.1,15467237.581226738,,14215415.58727552,14215415.58727552,71.2%,70.8%,,,3.1,15071189.953158952,,9899421.78922675,9899421.78922675,157.2%,145.3%,,,3.1,15071189.953158952,,9899421.78922675,9899421.78922675,157.2%,145.3%
+1757,Bordeaux,39823112.57058905,0.11848076947732528,3.7,63526142.58475932,0.11848076947732528,111225840.64176345,124201884.94352253,-49.2%,-57.2%,11011190.5447474,0.07484167019078293,4.2,23392984.04428134,0.07484167019078293,34689843.83439013,30823049.893489968,-38.5%,-53.8%,28811922.02584165,0.15245363081507063,3.2,39296138.90094225,0.15245363081507063,75054851.14819013,94810427.6065879,-56.9%,-60.6%,29760802.33692637,,2.2,36131481.982252166,,59853365.201187834,64769443.8704954,-53.2%,-55.5%,9770474.583932959,,3.0,14526260.513817577,,20622786.148718953,13823961.575908313,-46.2%,-38.5%,6699487.901823809,,2.9,10978754.784454009,,13946276.50294165,9885608.666920975,-47.7%,-40.4%,23061314.435102563,,1.9,24775567.548071906,,44308885.58733169,56952988.282906964,-53.5%,-55.1%,4885237.291966479,,3.0,7450045.923266258,,10364411.154019706,6911980.787954241,-47.0%,-41.8%,4885237.291966479,,3.0,7263130.256908879,,10311393.07435953,6911980.787954241,-46.2%,-38.5%
+1757,Nantes,,0.0,1.2,30263857.107198473,0.0,30649048.508631703,27449863.28545698,-41.9%,-38.6%,,0.0,1.1,13106363.32920537,0.0,16454366.364679879,13857126.446971772,-48.6%,-46.3%,4984994.270048742,0.026377291850908827,0.6,15435526.485324636,0.026377291850908827,17609770.086215705,19066009.25927136,-24.4%,13.7%,,,0.6,18582944.202398196,,15067163.987115646,11529620.102061639,-23.1%,6.9%,,,-0.2,9471889.468718931,,8907328.17482843,3568215.35096687,-30.2%,53.9%,,,0.0,6841852.9362377785,,6763652.540534975,3357661.9016005564,-34.6%,31.5%,4489054.24027548,,0.6,10314148.366438346,,9765646.595460422,12285431.39758419,-6.7%,42.0%,,,-0.1,4754515.43377466,,4453664.08741427,1784107.6754834317,-31.5%,56.8%,,,-0.2,4735944.734359474,,4453664.08741427,1784107.6754834317,-30.2%,53.9%
+1757,Bayonne,18611987.65773474,0.05537393932435841,0.1,17920892.81549939,0.05537393932435841,17552835.4867688,17552835.4867688,22.6%,40.3%,5846503.622570667,0.039737946056921075,0.3,6388815.911520225,0.039737946056921075,6819286.967828287,6819286.967828287,13.4%,23.8%,12765484.035164073,0.06754649649985409,-0.4,11935105.543719435,0.06754649649985409,10761541.067738337,10761541.067738337,29.2%,49.7%,16603588.978483865,,0.3,15630639.224430766,,14688400.80210848,14688400.80210848,31.5%,49.0%,9782492.759856459,,0.5,10378685.515385514,,9711123.57535645,9711123.57535645,29.0%,37.4%,5012054.379928229,,0.4,5323317.251931034,,5120089.923046211,5120089.923046211,28.9%,36.9%,11591534.598555636,,0.2,10326343.959511226,,9659048.314344099,9659048.314344099,31.3%,52.7%,4891246.379928229,,0.5,5182241.124483654,,4855561.78767825,4855561.78767825,30.1%,37.3%,4891246.379928229,,0.5,5189342.757692748,,4855561.78767825,4855561.78767825,29.0%,37.4%
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diff --git a/data/wheat_correlations.gexf b/data/wheat_correlations.gexf
index 8b43a47..7313b9c 100644
--- a/data/wheat_correlations.gexf
+++ b/data/wheat_correlations.gexf
@@ -1273,877 +1273,877 @@
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\ No newline at end of file
diff --git a/data/wheat_correlations_links.csv b/data/wheat_correlations_links.csv
index 6091332..d5b4c91 100644
--- a/data/wheat_correlations_links.csv
+++ b/data/wheat_correlations_links.csv
@@ -1,872 +1,872 @@
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diff --git a/main.bundle.js b/main.bundle.js
index 3535eaf..c911712 100644
--- a/main.bundle.js
+++ b/main.bundle.js
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LC(d,u),f=(0,r.useRef)();dC((()=>(f.current=p,Uf(u,(e=>Wh(e,p))),()=>{f.current&&(Uf(f.current.deps,(e=>Gh(e,f.current))),Mf.cancel(f.current.update))}))),(0,r.useEffect)(d,[]),hC((()=>()=>{const e=f.current;Uf(e.deps,(t=>Gh(t,e)))}));const h=t.getComponentProps(l.getValue());return r.createElement(e,{...h,ref:s})}))},LC=class{constructor(e,t){this.update=e,this.deps=t}eventObserved(e){"change"==e.type&&Mf.write(this.update)}},SC=Symbol.for("AnimatedComponent"),PC=e=>Bf.str(e)?e:e&&Bf.str(e.displayName)?e.displayName:Bf.fun(e)&&e.name||null;function AC(e,...t){return Bf.fun(e)?e(...t):e}var TC=(e,t)=>!0===e||!!(t&&e&&(Bf.fun(e)?e(t):Gf(e).includes(t))),NC=(e,t)=>Bf.obj(e)?t&&e[t]:e,OC=(e,t)=>!0===e.default?e[t]:e.default?e.default[t]:void 0,qC=e=>e,IC=(e,t=qC)=>{let n=RC;e.default&&!0!==e.default&&(e=e.default,n=Object.keys(e));const r={};for(const i of n){const n=t(e[i],i);Bf.und(n)||(r[i]=n)}return 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WC={tension:170,friction:26,mass:1,damping:1,easing:Ih.linear,clamp:!1},GC=class{constructor(){this.velocity=0,Object.assign(this,WC)}};function XC(e,t){if(Bf.und(t.decay)){const n=!Bf.und(t.tension)||!Bf.und(t.friction);!n&&Bf.und(t.frequency)&&Bf.und(t.damping)&&Bf.und(t.mass)||(e.duration=void 0,e.decay=void 0),n&&(e.frequency=void 0)}else e.duration=void 0}var YC=[],KC=class{constructor(){this.changed=!1,this.values=YC,this.toValues=null,this.fromValues=YC,this.config=new GC,this.immediate=!1}};function QC(e,{key:t,props:n,defaultProps:r,state:i,actions:a}){return new Promise(((o,s)=>{let l,u,c=TC(n.cancel??r?.cancel,t);if(c)f();else{Bf.und(n.pause)||(i.paused=TC(n.pause,t));let e=r?.pause;!0!==e&&(e=i.paused||TC(e,t)),l=AC(n.delay||0,t),e?(i.resumeQueue.add(p),a.pause()):(a.resume(),p())}function d(){i.resumeQueue.add(p),i.timeouts.delete(u),u.cancel(),l=u.time-Mf.now()}function p(){l>0&&!Df.skipAnimation?(i.delayed=!0,u=Mf.setTimeout(f,l),i.pauseQueue.add(d),i.timeouts.add(u)):f()}function f(){i.delayed&&(i.delayed=!1),i.pauseQueue.delete(d),i.timeouts.delete(u),e<=(i.cancelId||0)&&(c=!0);try{a.start({...n,callId:e,cancel:c},o)}catch(e){s(e)}}}))}var JC=(e,t)=>1==t.length?t[0]:t.some((e=>e.cancelled))?nm(e.get()):t.every((e=>e.noop))?em(e.get()):tm(e.get(),t.every((e=>e.finished))),em=e=>({value:e,noop:!0,finished:!0,cancelled:!1}),tm=(e,t,n=!1)=>({value:e,finished:t,cancelled:n}),nm=e=>({value:e,cancelled:!0,finished:!1});function rm(e,t,n,r){const{callId:i,parentId:a,onRest:o}=t,{asyncTo:s,promise:l}=n;return a||e!==s||t.reset?n.promise=(async()=>{n.asyncId=i,n.asyncTo=e;const u=IC(t,((e,t)=>"onRest"===t?void 0:e));let c,d;const p=new Promise(((e,t)=>(c=e,d=t))),f=e=>{const t=i<=(n.cancelId||0)&&nm(r)||i!==n.asyncId&&tm(r,!1);if(t)throw e.result=t,d(e),e},h=(e,t)=>{const a=new am,o=new om;return(async()=>{if(Df.skipAnimation)throw im(n),o.result=tm(r,!1),d(o),o;f(a);const s=Bf.obj(e)?{...e}:{...t,to:e};s.parentId=i,Wf(u,((e,t)=>{Bf.und(s[t])&&(s[t]=e)}));const l=await r.start(s);return f(a),n.paused&&await new Promise((e=>{n.resumeQueue.add(e)})),l})()};let C;if(Df.skipAnimation)return im(n),tm(r,!1);try{let t;t=Bf.arr(e)?(async e=>{for(const t of e)await h(t)})(e):Promise.resolve(e(h,r.stop.bind(r))),await Promise.all([t.then(c),p]),C=tm(r.get(),!0,!1)}catch(e){if(e instanceof am)C=e.result;else{if(!(e instanceof om))throw e;C=e.result}}finally{i==n.asyncId&&(n.asyncId=a,n.asyncTo=a?s:void 0,n.promise=a?l:void 0)}return Bf.fun(o)&&Mf.batchedUpdates((()=>{o(C,r,r.item)})),C})():l}function im(e,t){Xf(e.timeouts,(e=>e.cancel())),e.pauseQueue.clear(),e.resumeQueue.clear(),e.asyncId=e.asyncTo=e.promise=void 0,t&&(e.cancelId=t)}var am=class extends Error{constructor(){super("An async animation has been interrupted. You see this error because you forgot to use `await` or `.catch(...)` on its returned promise.")}},om=class extends Error{constructor(){super("SkipAnimationSignal")}},sm=e=>e instanceof um,lm=1,um=class extends $h{constructor(){super(...arguments),this.id=lm++,this._priority=0}get priority(){return this._priority}set priority(e){this._priority!=e&&(this._priority=e,this._onPriorityChange(e))}get(){const e=vC(this);return e&&e.getValue()}to(...e){return Df.to(this,e)}interpolate(...e){return lC(`${oC}The "interpolate" function is deprecated in v9 (use "to" instead)`),Df.to(this,e)}toJSON(){return this.get()}observerAdded(e){1==e&&this._attach()}observerRemoved(e){0==e&&this._detach()}_attach(){}_detach(){}_onChange(e,t=!1){Bh(this,{type:"change",parent:this,value:e,idle:t})}_onPriorityChange(e){this.idle||lh.sort(this),Bh(this,{type:"priority",parent:this,priority:e})}},cm=Symbol.for("SpringPhase"),dm=e=>(1&e[cm])>0,pm=e=>(2&e[cm])>0,fm=e=>(4&e[cm])>0,hm=(e,t)=>t?e[cm]|=3:e[cm]&=-3,Cm=(e,t)=>t?e[cm]|=4:e[cm]&=-5,mm=class extends um{constructor(e,t){if(super(),this.animation=new KC,this.defaultProps={},this._state={paused:!1,delayed:!1,pauseQueue:new Set,resumeQueue:new Set,timeouts:new Set},this._pendingCalls=new Set,this._lastCallId=0,this._lastToId=0,this._memoizedDuration=0,!Bf.und(e)||!Bf.und(t)){const n=Bf.obj(e)?{...e}:{...t,from:e};Bf.und(n.default)&&(n.default=!0),this.start(n)}}get idle(){return!(pm(this)||this._state.asyncTo)||fm(this)}get goal(){return Dh(this.animation.to)}get velocity(){const e=vC(this);return e instanceof wC?e.lastVelocity||0:e.getPayload().map((e=>e.lastVelocity||0))}get hasAnimated(){return dm(this)}get isAnimating(){return pm(this)}get isPaused(){return fm(this)}get isDelayed(){return this._state.delayed}advance(e){let t=!0,n=!1;const r=this.animation;let{toValues:i}=r;const{config:a}=r,o=bC(r.to);!o&&Fh(r.to)&&(i=Gf(Dh(r.to))),r.values.forEach(((s,l)=>{if(s.done)return;const u=s.constructor==_C?1:o?o[l].lastPosition:i[l];let c=r.immediate,d=u;if(!c){if(d=s.lastPosition,a.tension<=0)return void(s.done=!0);let t=s.elapsedTime+=e;const n=r.fromValues[l],i=null!=s.v0?s.v0:s.v0=Bf.arr(a.velocity)?a.velocity[l]:a.velocity;let o;const p=a.precision||(n==u?.005:Math.min(1,.001*Math.abs(u-n)));if(Bf.und(a.duration))if(a.decay){const e=!0===a.decay?.998:a.decay,r=Math.exp(-(1-e)*t);d=n+i/(1-e)*(1-r),c=Math.abs(s.lastPosition-d)<=p,o=i*r}else{o=null==s.lastVelocity?i:s.lastVelocity;const t=a.restVelocity||p/10,r=a.clamp?0:a.bounce,l=!Bf.und(r),f=n==u?s.v0>0:n<u;let h,C=!1;const m=1,g=Math.ceil(e/m);for(let e=0;e<g&&(h=Math.abs(o)>t,h||(c=Math.abs(u-d)<=p,!c));++e)l&&(C=d==u||d>u==f,C&&(o=-o*r,d=u)),o+=(1e-6*-a.tension*(d-u)+.001*-a.friction*o)/a.mass*m,d+=o*m}else{let r=1;a.duration>0&&(this._memoizedDuration!==a.duration&&(this._memoizedDuration=a.duration,s.durationProgress>0&&(s.elapsedTime=a.duration*s.durationProgress,t=s.elapsedTime+=e)),r=(a.progress||0)+t/this._memoizedDuration,r=r>1?1:r<0?0:r,s.durationProgress=r),d=n+a.easing(r)*(u-n),o=(d-s.lastPosition)/e,c=1==r}s.lastVelocity=o,Number.isNaN(d)&&(console.warn("Got NaN while animating:",this),c=!0)}o&&!o[l].done&&(c=!1),c?s.done=!0:t=!1,s.setValue(d,a.round)&&(n=!0)}));const s=vC(this),l=s.getValue();if(t){const e=Dh(r.to);l===e&&!n||a.decay?n&&a.decay&&this._onChange(l):(s.setValue(e),this._onChange(e)),this._stop()}else n&&this._onChange(l)}set(e){return Mf.batchedUpdates((()=>{this._stop(),this._focus(e),this._set(e)})),this}pause(){this._update({pause:!0})}resume(){this._update({pause:!1})}finish(){if(pm(this)){const{to:e,config:t}=this.animation;Mf.batchedUpdates((()=>{this._onStart(),t.decay||this._set(e,!1),this._stop()}))}return this}update(e){return(this.queue||(this.queue=[])).push(e),this}start(e,t){let n;return Bf.und(e)?(n=this.queue||[],this.queue=[]):n=[Bf.obj(e)?e:{...t,to:e}],Promise.all(n.map((e=>this._update(e)))).then((e=>JC(this,e)))}stop(e){const{to:t}=this.animation;return this._focus(this.get()),im(this._state,e&&this._lastCallId),Mf.batchedUpdates((()=>this._stop(t,e))),this}reset(){this._update({reset:!0})}eventObserved(e){"change"==e.type?this._start():"priority"==e.type&&(this.priority=e.priority+1)}_prepareNode(e){const t=this.key||"";let{to:n,from:r}=e;n=Bf.obj(n)?n[t]:n,(null==n||BC(n))&&(n=void 0),r=Bf.obj(r)?r[t]:r,null==r&&(r=void 0);const i={to:n,from:r};return dm(this)||(e.reverse&&([n,r]=[r,n]),r=Dh(r),Bf.und(r)?vC(this)||this._set(n):this._set(r)),i}_update({...e},t){const{key:n,defaultProps:r}=this;e.default&&Object.assign(r,IC(e,((e,t)=>/^on/.test(t)?NC(e,n):e))),_m(this,e,"onProps"),Mm(this,"onProps",e,this);const i=this._prepareNode(e);if(Object.isFrozen(this))throw Error("Cannot animate a `SpringValue` object that is frozen. Did you forget to pass your component to `animated(...)` before animating its props?");const a=this._state;return QC(++this._lastCallId,{key:n,props:e,defaultProps:r,state:a,actions:{pause:()=>{fm(this)||(Cm(this,!0),Qf(a.pauseQueue),Mm(this,"onPause",tm(this,gm(this,this.animation.to)),this))},resume:()=>{fm(this)&&(Cm(this,!1),pm(this)&&this._resume(),Qf(a.resumeQueue),Mm(this,"onResume",tm(this,gm(this,this.animation.to)),this))},start:this._merge.bind(this,i)}}).then((n=>{if(e.loop&&n.finished&&(!t||!n.noop)){const t=vm(e);if(t)return this._update(t,!0)}return n}))}_merge(e,t,n){if(t.cancel)return this.stop(!0),n(nm(this));const r=!Bf.und(e.to),i=!Bf.und(e.from);if(r||i){if(!(t.callId>this._lastToId))return n(nm(this));this._lastToId=t.callId}const{key:a,defaultProps:o,animation:s}=this,{to:l,from:u}=s;let{to:c=l,from:d=u}=e;!i||r||t.default&&!Bf.und(c)||(c=d),t.reverse&&([c,d]=[d,c]);const p=!$f(d,u);p&&(s.from=d),d=Dh(d);const f=!$f(c,l);f&&this._focus(c);const h=BC(t.to),{config:C}=s,{decay:m,velocity:g}=C;(r||i)&&(C.velocity=0),t.config&&!h&&function(e,t,n){n&&(XC(n={...n},t),t={...n,...t}),XC(e,t),Object.assign(e,t);for(const t in WC)null==e[t]&&(e[t]=WC[t]);let{frequency:r,damping:i}=e;const{mass:a}=e;Bf.und(r)||(r<.01&&(r=.01),i<0&&(i=0),e.tension=Math.pow(2*Math.PI/r,2)*a,e.friction=4*Math.PI*i*a/r)}(C,AC(t.config,a),t.config!==o.config?AC(o.config,a):void 0);let v=vC(this);if(!v||Bf.und(c))return n(tm(this,!0));const y=Bf.und(t.reset)?i&&!t.default:!Bf.und(d)&&TC(t.reset,a),b=y?d:this.get(),x=DC(c),w=Bf.num(x)||Bf.arr(x)||cC(x),_=!h&&(!w||TC(o.immediate||t.immediate,a));if(f){const e=HC(c);if(e!==v.constructor){if(!_)throw Error(`Cannot animate between ${v.constructor.name} and ${e.name}, as the "to" prop suggests`);v=this._set(x)}}const M=v.constructor;let V=Fh(c),k=!1;if(!V){const e=y||!dm(this)&&p;(f||e)&&(k=$f(DC(b),x),V=!k),($f(s.immediate,_)||_)&&$f(C.decay,m)&&$f(C.velocity,g)||(V=!0)}if(k&&pm(this)&&(s.changed&&!y?V=!0:V||this._stop(l)),!h&&((V||Fh(l))&&(s.values=v.getPayload(),s.toValues=Fh(c)?null:M==_C?[1]:Gf(x)),s.immediate!=_&&(s.immediate=_,_||y||this._set(l)),V)){const{onRest:e}=s;Uf(wm,(e=>_m(this,t,e)));const r=tm(this,gm(this,l));Qf(this._pendingCalls,r),this._pendingCalls.add(n),s.changed&&Mf.batchedUpdates((()=>{s.changed=!y,e?.(r,this),y?AC(o.onRest,r):s.onStart?.(r,this)}))}y&&this._set(b),h?n(rm(t.to,t,this._state,this)):V?this._start():pm(this)&&!f?this._pendingCalls.add(n):n(em(b))}_focus(e){const t=this.animation;e!==t.to&&(Zh(this)&&this._detach(),t.to=e,Zh(this)&&this._attach())}_attach(){let e=0;const{to:t}=this.animation;Fh(t)&&(Wh(t,this),sm(t)&&(e=t.priority+1)),this.priority=e}_detach(){const{to:e}=this.animation;Fh(e)&&Gh(e,this)}_set(e,t=!0){const n=Dh(e);if(!Bf.und(n)){const e=vC(this);if(!e||!$f(n,e.getValue())){const r=HC(n);e&&e.constructor==r?e.setValue(n):yC(this,r.create(n)),e&&Mf.batchedUpdates((()=>{this._onChange(n,t)}))}}return vC(this)}_onStart(){const e=this.animation;e.changed||(e.changed=!0,Mm(this,"onStart",tm(this,gm(this,e.to)),this))}_onChange(e,t){t||(this._onStart(),AC(this.animation.onChange,e,this)),AC(this.defaultProps.onChange,e,this),super._onChange(e,t)}_start(){const e=this.animation;vC(this).reset(Dh(e.to)),e.immediate||(e.fromValues=e.values.map((e=>e.lastPosition))),pm(this)||(hm(this,!0),fm(this)||this._resume())}_resume(){Df.skipAnimation?this.finish():lh.start(this)}_stop(e,t){if(pm(this)){hm(this,!1);const n=this.animation;Uf(n.values,(e=>{e.done=!0})),n.toValues&&(n.onChange=n.onPause=n.onResume=void 0),Bh(this,{type:"idle",parent:this});const r=t?nm(this.get()):tm(this.get(),gm(this,e??n.to));Qf(this._pendingCalls,r),n.changed&&(n.changed=!1,Mm(this,"onRest",r,this))}}};function gm(e,t){const n=DC(t);return $f(DC(e.get()),n)}function vm(e,t=e.loop,n=e.to){const r=AC(t);if(r){const i=!0!==r&&FC(r),a=(i||e).reverse,o=!i||i.reset;return ym({...e,loop:t,default:!1,pause:void 0,to:!a||BC(n)?n:void 0,from:o?e.from:void 0,reset:o,...i})}}function ym(e){const{to:t,from:n}=e=FC(e),r=new Set;return Bf.obj(t)&&xm(t,r),Bf.obj(n)&&xm(n,r),e.keys=r.size?Array.from(r):null,e}function bm(e){const t=ym(e);return Bf.und(t.default)&&(t.default=IC(t)),t}function xm(e,t){Wf(e,((e,n)=>null!=e&&t.add(n)))}var wm=["onStart","onRest","onChange","onPause","onResume"];function _m(e,t,n){e.animation[n]=t[n]!==OC(t,n)?NC(t[n],e.key):void 0}function Mm(e,t,...n){e.animation[t]?.(...n),e.defaultProps[t]?.(...n)}var Vm=["onStart","onChange","onRest"],km=1,jm=class{constructor(e,t){this.id=km++,this.springs={},this.queue=[],this._lastAsyncId=0,this._active=new Set,this._changed=new Set,this._started=!1,this._state={paused:!1,pauseQueue:new Set,resumeQueue:new Set,timeouts:new Set},this._events={onStart:new Map,onChange:new Map,onRest:new Map},this._onFrame=this._onFrame.bind(this),t&&(this._flush=t),e&&this.start({default:!0,...e})}get idle(){return!this._state.asyncTo&&Object.values(this.springs).every((e=>e.idle&&!e.isDelayed&&!e.isPaused))}get item(){return this._item}set item(e){this._item=e}get(){const e={};return this.each(((t,n)=>e[n]=t.get())),e}set(e){for(const t in e){const n=e[t];Bf.und(n)||this.springs[t].set(n)}}update(e){return e&&this.queue.push(ym(e)),this}start(e){let{queue:t}=this;return e?t=Gf(e).map(ym):this.queue=[],this._flush?this._flush(this,t):(Tm(this,t),Hm(this,t))}stop(e,t){if(e!==!!e&&(t=e),t){const n=this.springs;Uf(Gf(t),(t=>n[t].stop(!!e)))}else im(this._state,this._lastAsyncId),this.each((t=>t.stop(!!e)));return this}pause(e){if(Bf.und(e))this.start({pause:!0});else{const t=this.springs;Uf(Gf(e),(e=>t[e].pause()))}return this}resume(e){if(Bf.und(e))this.start({pause:!1});else{const t=this.springs;Uf(Gf(e),(e=>t[e].resume()))}return 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t=e.keyCode;if(e.altKey&&!e.ctrlKey||e.metaKey||t>=uy.F1&&t<=uy.F12)return!1;switch(t){case uy.ALT:case uy.CAPS_LOCK:case uy.CONTEXT_MENU:case uy.CTRL:case uy.DOWN:case uy.END:case uy.ESC:case uy.HOME:case uy.INSERT:case uy.LEFT:case uy.MAC_FF_META:case uy.META:case uy.NUMLOCK:case uy.NUM_CENTER:case uy.PAGE_DOWN:case uy.PAGE_UP:case uy.PAUSE:case uy.PRINT_SCREEN:case uy.RIGHT:case uy.SHIFT:case uy.UP:case uy.WIN_KEY:case uy.WIN_KEY_RIGHT:return!1;default:return!0}},isCharacterKey:function(e){if(e>=uy.ZERO&&e<=uy.NINE)return!0;if(e>=uy.NUM_ZERO&&e<=uy.NUM_MULTIPLY)return!0;if(e>=uy.A&&e<=uy.Z)return!0;if(-1!==window.navigator.userAgent.indexOf("WebKit")&&0===e)return!0;switch(e){case uy.SPACE:case uy.QUESTION_MARK:case uy.NUM_PLUS:case uy.NUM_MINUS:case uy.NUM_PERIOD:case uy.NUM_DIVISION:case uy.SEMICOLON:case uy.DASH:case uy.EQUALS:case uy.COMMA:case uy.PERIOD:case uy.SLASH:case uy.APOSTROPHE:case uy.SINGLE_QUOTE:case uy.OPEN_SQUARE_BRACKET:case uy.BACKSLASH:case 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e=this.sliderRef,t=this.props,n=t.vertical,r=t.reverse,i=e.getBoundingClientRect();return n?r?i.bottom:i.top:window.pageXOffset+(r?i.right:i.left)}},{key:"getSliderLength",value:function(){var e=this.sliderRef;if(!e)return 0;var t=e.getBoundingClientRect();return this.props.vertical?t.height:t.width}},{key:"addDocumentTouchEvents",value:function(){this.onTouchMoveListener=ny(this.document,"touchmove",this.onTouchMove),this.onTouchUpListener=ny(this.document,"touchend",this.onEnd)}},{key:"addDocumentMouseEvents",value:function(){this.onMouseMoveListener=ny(this.document,"mousemove",this.onMouseMove),this.onMouseUpListener=ny(this.document,"mouseup",this.onEnd)}},{key:"removeDocumentEvents",value:function(){this.onTouchMoveListener&&this.onTouchMoveListener.remove(),this.onTouchUpListener&&this.onTouchUpListener.remove(),this.onMouseMoveListener&&this.onMouseMoveListener.remove(),this.onMouseUpListener&&this.onMouseUpListener.remove()}},{key:"focus",value:function(){var e;this.props.disabled||null===(e=this.handlesRefs[0])||void 0===e||e.focus()}},{key:"blur",value:function(){var e=this;this.props.disabled||Object.keys(this.handlesRefs).forEach((function(t){var n,r;null===(n=e.handlesRefs[t])||void 0===n||null===(r=n.blur)||void 0===r||r.call(n)}))}},{key:"calcValue",value:function(e){var t=this.props,n=t.vertical,r=t.min,i=t.max,a=Math.abs(Math.max(e,0)/this.getSliderLength());return n?(1-a)*(i-r)+r:a*(i-r)+r}},{key:"calcValueByPos",value:function(e){var t=(this.props.reverse?-1:1)*(e-this.getSliderStart());return this.trimAlignValue(this.calcValue(t))}},{key:"calcOffset",value:function(e){var t=this.props,n=t.min,r=(e-n)/(t.max-n);return Math.max(0,100*r)}},{key:"saveHandle",value:function(e,t){this.handlesRefs[e]=t}},{key:"render",value:function(){var e,t=this.props,i=t.prefixCls,a=t.className,o=t.marks,s=t.dots,l=t.step,u=t.included,c=t.disabled,d=t.vertical,p=t.reverse,f=t.min,h=t.max,C=t.children,m=t.maximumTrackStyle,g=t.style,v=t.railStyle,y=t.dotStyle,b=t.activeDotStyle,x=ty(Dv(n.prototype),"render",this).call(this),w=x.tracks,_=x.handles,M=dn()(i,(Nv(e={},"".concat(i,"-with-marks"),Object.keys(o).length),Nv(e,"".concat(i,"-disabled"),c),Nv(e,"".concat(i,"-vertical"),d),Nv(e,a,a),e));return r.createElement("div",{ref:this.saveSlider,className:M,onTouchStart:c?_y:this.onTouchStart,onMouseDown:c?_y:this.onMouseDown,onMouseUp:c?_y:this.onMouseUp,onKeyDown:c?_y:this.onKeyDown,onFocus:c?_y:this.onFocus,onBlur:c?_y:this.onBlur,style:g},r.createElement("div",{className:"".concat(i,"-rail"),style:qv(qv({},m),v)}),w,r.createElement(ry,{prefixCls:i,vertical:d,reverse:p,marks:o,dots:s,step:l,included:u,lowerBound:this.getLowerBound(),upperBound:this.getUpperBound(),max:h,min:f,dotStyle:y,activeDotStyle:b}),_,r.createElement(iy,{className:"".concat(i,"-mark"),onClickLabel:c?_y:this.onClickMarkLabel,vertical:d,marks:o,included:u,lowerBound:this.getLowerBound(),upperBound:this.getUpperBound(),max:h,min:f,reverse:p}),C)}}]),n}(e),t.displayName="ComponentEnhancer(".concat(e.displayName,")"),t.defaultProps=qv(qv({},e.defaultProps),{},{prefixCls:"rc-slider",className:"",min:0,max:100,step:1,marks:{},handle:function(e){var t=e.index,n=ey(e,["index"]);return delete n.dragging,null===n.value?null:r.createElement(ay,Object.assign({},n,{key:t}))},onBeforeChange:_y,onChange:_y,onAfterChange:_y,included:!0,disabled:!1,dots:!1,vertical:!1,reverse:!1,trackStyle:[{}],handleStyle:[{}],railStyle:{},dotStyle:{},activeDotStyle:{}}),t}var Vy=function(e){Fv(n,e);var t=$v(n);function n(e){var r;Iv(this,n),(r=t.call(this,e)).onEnd=function(e){var t=r.state.dragging;r.removeDocumentEvents(),(t||e)&&r.props.onAfterChange(r.getValue()),r.setState({dragging:!1})};var i=void 0!==e.defaultValue?e.defaultValue:e.min,a=void 0!==e.value?e.value:i;return r.state={value:r.trimAlignValue(a),dragging:!1},Qv(!("minimumTrackStyle"in e),"minimumTrackStyle will be deprecated, please use trackStyle instead."),Qv(!("maximumTrackStyle"in e),"maximumTrackStyle will be deprecated, please use railStyle instead."),r}return zv(n,[{key:"calcValueByPos",value:function(e){return 0}},{key:"calcOffset",value:function(e){return 0}},{key:"saveHandle",value:function(e,t){}},{key:"removeDocumentEvents",value:function(){}},{key:"componentDidUpdate",value:function(e,t){var n=this.props,r=n.min,i=n.max,a=n.value,o=n.onChange;if("min"in this.props||"max"in this.props){var s=void 0!==a?a:t.value,l=this.trimAlignValue(s,this.props);l!==t.value&&(this.setState({value:l}),r===e.min&&i===e.max||!py(s,this.props)||o(l))}}},{key:"onChange",value:function(e){var t=this.props,n=!("value"in t),r=e.value>this.props.max?qv(qv({},e),{},{value:this.props.max}):e;n&&this.setState(r);var i=r.value;t.onChange(i)}},{key:"onStart",value:function(e){this.setState({dragging:!0});var t=this.props,n=this.getValue();t.onBeforeChange(n);var r=this.calcValueByPos(e);this.startValue=r,this.startPosition=e,r!==n&&(this.prevMovedHandleIndex=0,this.onChange({value:r}))}},{key:"onMove",value:function(e,t){xy(e);var n=this.state.value,r=this.calcValueByPos(t);r!==n&&this.onChange({value:r})}},{key:"onKeyboard",value:function(e){var t=this.props,n=t.reverse,r=wy(e,t.vertical,n);if(r){xy(e);var i=this.state.value,a=r(i,this.props),o=this.trimAlignValue(a);if(o===i)return;this.onChange({value:o}),this.props.onAfterChange(o),this.onEnd()}}},{key:"getValue",value:function(){return this.state.value}},{key:"getLowerBound",value:function(){var e=this.props.startPoint||this.props.min;return this.state.value>e?e:this.state.value}},{key:"getUpperBound",value:function(){return this.state.value<this.props.startPoint?this.props.startPoint:this.state.value}},{key:"trimAlignValue",value:function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{};if(null===e)return null;var n=qv(qv({},this.props),t);return by(yy(e,n),n)}},{key:"render",value:function(){var e=this,t=this.props,n=t.prefixCls,i=t.vertical,a=t.included,o=t.disabled,s=t.minimumTrackStyle,l=t.trackStyle,u=t.handleStyle,c=t.tabIndex,d=t.ariaLabelForHandle,p=t.ariaLabelledByForHandle,f=t.ariaValueTextFormatterForHandle,h=t.min,C=t.max,m=t.startPoint,g=t.reverse,v=t.handle,y=this.state,b=y.value,x=y.dragging,w=this.calcOffset(b),_=v({className:"".concat(n,"-handle"),prefixCls:n,vertical:i,offset:w,value:b,dragging:x,disabled:o,min:h,max:C,reverse:g,index:0,tabIndex:c,ariaLabel:d,ariaLabelledBy:p,ariaValueTextFormatter:f,style:u[0]||u,ref:function(t){return e.saveHandle(0,t)}}),M=void 0!==m?this.calcOffset(m):0,V=l[0]||l;return{tracks:r.createElement(Jv,{className:"".concat(n,"-track"),vertical:i,included:a,offset:M,reverse:g,length:w-M,style:qv(qv({},s),V)}),handles:_}}}]),n}(r.Component);const ky=My(Vy);var jy=function(e){var t=e.value,n=e.handle,r=e.bounds,i=e.props,a=i.allowCross,o=i.pushable,s=Number(o),l=yy(t,i),u=l;return a||null==n||void 0===r||(n>0&&l<=r[n-1]+s&&(u=r[n-1]+s),n<r.length-1&&l>=r[n+1]-s&&(u=r[n+1]-s)),by(u,i)},Hy=function(e){Fv(n,e);var t=$v(n);function n(e){var r;Iv(this,n),(r=t.call(this,e)).onEnd=function(e){var t=r.state.handle;r.removeDocumentEvents(),(null!==t||e)&&r.props.onAfterChange(r.getValue()),r.setState({handle:null})};var i=e.count,a=e.min,o=e.max,s=Array.apply(void 0,ly(Array(i+1))).map((function(){return a})),l="defaultValue"in e?e.defaultValue:s,u=(void 0!==e.value?e.value:l).map((function(t,n){return jy({value:t,handle:n,props:e})})),c=u[0]===o?0:u.length-1;return r.state={handle:null,recent:c,bounds:u},r}return zv(n,[{key:"calcValueByPos",value:function(e){return 0}},{key:"calcOffset",value:function(e){return 0}},{key:"saveHandle",value:function(e,t){}},{key:"removeDocumentEvents",value:function(){}},{key:"componentDidUpdate",value:function(e,t){var n=this,r=this.props,i=r.onChange,a=r.value,o=r.min,s=r.max;if(("min"in this.props||"max"in this.props)&&(o!==e.min||s!==e.max)){var l=a||t.bounds;l.some((function(e){return py(e,n.props)}))&&i(l.map((function(e){return yy(e,n.props)})))}}},{key:"onChange",value:function(e){var t=this.props;if("value"in t){var n={};["handle","recent"].forEach((function(t){void 0!==e[t]&&(n[t]=e[t])})),Object.keys(n).length&&this.setState(n)}else this.setState(e);var r=qv(qv({},this.state),e).bounds;t.onChange(r)}},{key:"onStart",value:function(e){var t=this.props,n=this.state,r=this.getValue();t.onBeforeChange(r);var i=this.calcValueByPos(e);this.startValue=i,this.startPosition=e;var a=this.getClosestBound(i);if(this.prevMovedHandleIndex=this.getBoundNeedMoving(i,a),this.setState({handle:this.prevMovedHandleIndex,recent:this.prevMovedHandleIndex}),i!==r[this.prevMovedHandleIndex]){var o=ly(n.bounds);o[this.prevMovedHandleIndex]=i,this.onChange({bounds:o})}}},{key:"onMove",value:function(e,t){xy(e);var n=this.state,r=this.calcValueByPos(t);r!==n.bounds[n.handle]&&this.moveTo(r)}},{key:"onKeyboard",value:function(e){var t=this.props,n=t.reverse,r=wy(e,t.vertical,n);if(r){xy(e);var i=this.state,a=this.props,o=i.bounds,s=i.handle,l=o[null===s?i.recent:s],u=r(l,a),c=jy({value:u,handle:s,bounds:i.bounds,props:a});if(c===l)return;this.moveTo(c,!0)}}},{key:"getValue",value:function(){return this.state.bounds}},{key:"getClosestBound",value:function(e){for(var t=this.state.bounds,n=0,r=1;r<t.length-1;r+=1)e>=t[r]&&(n=r);return Math.abs(t[n+1]-e)<Math.abs(t[n]-e)&&(n+=1),n}},{key:"getBoundNeedMoving",value:function(e,t){var n=this.state,r=n.bounds,i=n.recent,a=t,o=r[t+1]===r[t];return o&&r[i]===r[t]&&(a=i),o&&e!==r[t+1]&&(a=e<r[t+1]?t:t+1),a}},{key:"getLowerBound",value:function(){return this.state.bounds[0]}},{key:"getUpperBound",value:function(){var e=this.state.bounds;return e[e.length-1]}},{key:"getPoints",value:function(){var e=this.props,t=e.marks,n=e.step,r=e.min,i=e.max,a=this.internalPointsCache;if(!a||a.marks!==t||a.step!==n){var o=qv({},t);if(null!==n)for(var s=r;s<=i;s+=n)o[s]=s;var 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i.isMouseEnterToShow()&&(k.onMouseEnter=i.onPopupMouseEnter),i.isMouseLeaveToHide()&&(k.onMouseLeave=i.onPopupMouseLeave),k.onMouseDown=i.onPopupMouseDown,k.onTouchStart=i.onPopupMouseDown,r.createElement(sw,hc({prefixCls:t,destroyPopupOnHide:n,visible:_,point:v&&M,className:a,align:V,onAlign:o,animation:l,getClassNameFromAlign:i.getPopupClassNameFromAlign},k,{stretch:g,getRootDomNode:i.getRootDomNode,style:c,mask:d,zIndex:C,transitionName:u,maskAnimation:p,maskTransitionName:f,maskMotion:h,ref:i.popupRef,motion:s,mobile:y,forceRender:b,onClick:x}),"function"==typeof m?m():m)})),Nv(Bv(i),"attachParent",(function(e){Oy.cancel(i.attachId);var t,n=i.props,r=n.getPopupContainer,a=n.getDocument,o=i.getRootDomNode();r?(o||0===r.length)&&(t=r(o)):t=a(i.getRootDomNode()).body,t?t.appendChild(e):i.attachId=Oy((function(){i.attachParent(e)}))})),Nv(Bv(i),"getContainer",(function(){if(!i.portalContainer){var e=(0,i.props.getDocument)(i.getRootDomNode()).createElement("div");e.style.position="absolute",e.style.top="0",e.style.left="0",e.style.width="100%",i.portalContainer=e}return i.attachParent(i.portalContainer),i.portalContainer})),Nv(Bv(i),"setPoint",(function(e){i.props.alignPoint&&e&&i.setState({point:{pageX:e.pageX,pageY:e.pageY}})})),Nv(Bv(i),"handlePortalUpdate",(function(){i.state.prevPopupVisible!==i.state.popupVisible&&i.props.afterPopupVisibleChange(i.state.popupVisible)})),Nv(Bv(i),"triggerContextValue",{onPopupMouseDown:i.onPopupMouseDown}),a="popupVisible"in e?!!e.popupVisible:!!e.defaultPopupVisible,i.state={prevPopupVisible:a,popupVisible:a},cw.forEach((function(e){i["fire".concat(e)]=function(t){i.fireEvents(e,t)}})),i}return zv(n,[{key:"componentDidMount",value:function(){this.componentDidUpdate()}},{key:"componentDidUpdate",value:function(){var e,t=this.props;if(this.state.popupVisible)return this.clickOutsideHandler||!this.isClickToHide()&&!this.isContextMenuToShow()||(e=t.getDocument(this.getRootDomNode()),this.clickOutsideHandler=ny(e,"mousedown",this.onDocumentClick)),this.touchOutsideHandler||(e=e||t.getDocument(this.getRootDomNode()),this.touchOutsideHandler=ny(e,"touchstart",this.onDocumentClick)),!this.contextMenuOutsideHandler1&&this.isContextMenuToShow()&&(e=e||t.getDocument(this.getRootDomNode()),this.contextMenuOutsideHandler1=ny(e,"scroll",this.onContextMenuClose)),void(!this.contextMenuOutsideHandler2&&this.isContextMenuToShow()&&(this.contextMenuOutsideHandler2=ny(window,"blur",this.onContextMenuClose)));this.clearOutsideHandler()}},{key:"componentWillUnmount",value:function(){this.clearDelayTimer(),this.clearOutsideHandler(),clearTimeout(this.mouseDownTimeout),Oy.cancel(this.attachId)}},{key:"getPopupDomNode",value:function(){var e;return(null===(e=this.popupRef.current)||void 0===e?void 0:e.getElement())||null}},{key:"getPopupAlign",value:function(){var e=this.props,t=e.popupPlacement,n=e.popupAlign,r=e.builtinPlacements;return t&&r?function(e,t,n){return qv(qv({},e[t]||{}),n)}(r,t,n):n}},{key:"setPopupVisible",value:function(e,t){var n=this.props.alignPoint,r=this.state.popupVisible;this.clearDelayTimer(),r!==e&&("popupVisible"in this.props||this.setState({popupVisible:e,prevPopupVisible:r}),this.props.onPopupVisibleChange(e)),n&&t&&e&&this.setPoint(t)}},{key:"delaySetPopupVisible",value:function(e,t,n){var r=this,i=1e3*t;if(this.clearDelayTimer(),i){var a=n?{pageX:n.pageX,pageY:n.pageY}:null;this.delayTimer=window.setTimeout((function(){r.setPopupVisible(e,a),r.clearDelayTimer()}),i)}else this.setPopupVisible(e,n)}},{key:"clearDelayTimer",value:function(){this.delayTimer&&(clearTimeout(this.delayTimer),this.delayTimer=null)}},{key:"clearOutsideHandler",value:function(){this.clickOutsideHandler&&(this.clickOutsideHandler.remove(),this.clickOutsideHandler=null),this.contextMenuOutsideHandler1&&(this.contextMenuOutsideHandler1.remove(),this.contextMenuOutsideHandler1=null),this.contextMenuOutsideHandler2&&(this.contextMenuOutsideHandler2.remove(),this.contextMenuOutsideHandler2=null),this.touchOutsideHandler&&(this.touchOutsideHandler.remove(),this.touchOutsideHandler=null)}},{key:"createTwoChains",value:function(e){var t=this.props.children.props,n=this.props;return t[e]&&n[e]?this["fire".concat(e)]:t[e]||n[e]}},{key:"isClickToShow",value:function(){var e=this.props,t=e.action,n=e.showAction;return-1!==t.indexOf("click")||-1!==n.indexOf("click")}},{key:"isContextMenuOnly",value:function(){var e=this.props.action;return"contextMenu"===e||1===e.length&&"contextMenu"===e[0]}},{key:"isContextMenuToShow",value:function(){var e=this.props,t=e.action,n=e.showAction;return-1!==t.indexOf("contextMenu")||-1!==n.indexOf("contextMenu")}},{key:"isClickToHide",value:function(){var e=this.props,t=e.action,n=e.hideAction;return-1!==t.indexOf("click")||-1!==n.indexOf("click")}},{key:"isMouseEnterToShow",value:function(){var e=this.props,t=e.action,n=e.showAction;return-1!==t.indexOf("hover")||-1!==n.indexOf("mouseEnter")}},{key:"isMouseLeaveToHide",value:function(){var e=this.props,t=e.action,n=e.hideAction;return-1!==t.indexOf("hover")||-1!==n.indexOf("mouseLeave")}},{key:"isFocusToShow",value:function(){var e=this.props,t=e.action,n=e.showAction;return-1!==t.indexOf("focus")||-1!==n.indexOf("focus")}},{key:"isBlurToHide",value:function(){var e=this.props,t=e.action,n=e.hideAction;return-1!==t.indexOf("focus")||-1!==n.indexOf("blur")}},{key:"forcePopupAlign",value:function(){var e;this.state.popupVisible&&(null===(e=this.popupRef.current)||void 0===e||e.forceAlign())}},{key:"fireEvents",value:function(e,t){var n=this.props.children.props[e];n&&n(t);var r=this.props[e];r&&r(t)}},{key:"close",value:function(){this.setPopupVisible(!1)}},{key:"render",value:function(){var e=this.state.popupVisible,t=this.props,n=t.children,i=t.forceRender,a=t.alignPoint,o=t.className,s=t.autoDestroy,l=r.Children.only(n),u={key:"trigger"};this.isContextMenuToShow()?u.onContextMenu=this.onContextMenu:u.onContextMenu=this.createTwoChains("onContextMenu"),this.isClickToHide()||this.isClickToShow()?(u.onClick=this.onClick,u.onMouseDown=this.onMouseDown,u.onTouchStart=this.onTouchStart):(u.onClick=this.createTwoChains("onClick"),u.onMouseDown=this.createTwoChains("onMouseDown"),u.onTouchStart=this.createTwoChains("onTouchStart")),this.isMouseEnterToShow()?(u.onMouseEnter=this.onMouseEnter,a&&(u.onMouseMove=this.onMouseMove)):u.onMouseEnter=this.createTwoChains("onMouseEnter"),this.isMouseLeaveToHide()?u.onMouseLeave=this.onMouseLeave:u.onMouseLeave=this.createTwoChains("onMouseLeave"),this.isFocusToShow()||this.isBlurToHide()?(u.onFocus=this.onFocus,u.onBlur=this.onBlur):(u.onFocus=this.createTwoChains("onFocus"),u.onBlur=this.createTwoChains("onBlur"));var c=dn()(l&&l.props&&l.props.className,o);c&&(u.className=c);var d=qv({},u);Zy(l)&&(d.ref=Dy(this.triggerRef,l.ref));var p,f=r.cloneElement(l,d);return(e||this.popupRef.current||i)&&(p=r.createElement(pw,{key:"portal",getContainer:this.getContainer,didUpdate:this.handlePortalUpdate},this.getComponent())),!e&&s&&(p=null),r.createElement(lw.Provider,{value:this.triggerContextValue},f,p)}}],[{key:"getDerivedStateFromProps",value:function(e,t){var n=e.popupVisible,r={};return void 0!==n&&t.popupVisible!==n&&(r.popupVisible=n,r.prevPopupVisible=t.popupVisible),r}}]),n}(r.Component),Nv(fw,"contextType",lw),Nv(fw,"defaultProps",{prefixCls:"rc-trigger-popup",getPopupClassNameFromAlign:function(){return""},getDocument:function(e){return e?e.ownerDocument:window.document},onPopupVisibleChange:uw,afterPopupVisibleChange:uw,onPopupAlign:uw,popupClassName:"",mouseEnterDelay:0,mouseLeaveDelay:.1,focusDelay:0,blurDelay:.15,popupStyle:{},destroyPopupOnHide:!1,popupAlign:{},defaultPopupVisible:!1,mask:!1,maskClosable:!0,action:[],showAction:[],hideAction:[],autoDestroy:!1}),fw);var pw,fw,hw={adjustX:1,adjustY:1},Cw=[0,0],mw={left:{points:["cr","cl"],overflow:hw,offset:[-4,0],targetOffset:Cw},right:{points:["cl","cr"],overflow:hw,offset:[4,0],targetOffset:Cw},top:{points:["bc","tc"],overflow:hw,offset:[0,-4],targetOffset:Cw},bottom:{points:["tc","bc"],overflow:hw,offset:[0,4],targetOffset:Cw},topLeft:{points:["bl","tl"],overflow:hw,offset:[0,-4],targetOffset:Cw},leftTop:{points:["tr","tl"],overflow:hw,offset:[-4,0],targetOffset:Cw},topRight:{points:["br","tr"],overflow:hw,offset:[0,-4],targetOffset:Cw},rightTop:{points:["tl","tr"],overflow:hw,offset:[4,0],targetOffset:Cw},bottomRight:{points:["tr","br"],overflow:hw,offset:[0,4],targetOffset:Cw},rightBottom:{points:["bl","br"],overflow:hw,offset:[4,0],targetOffset:Cw},bottomLeft:{points:["tl","bl"],overflow:hw,offset:[0,4],targetOffset:Cw},leftBottom:{points:["br","bl"],overflow:hw,offset:[-4,0],targetOffset:Cw}};function gw(e){var t=e.showArrow,n=e.arrowContent,i=e.children,a=e.prefixCls,o=e.id,s=e.overlayInnerStyle,l=e.className,u=e.style;return r.createElement("div",{className:dn()("".concat(a,"-content"),l),style:u},!1!==t&&r.createElement("div",{className:"".concat(a,"-arrow"),key:"arrow"},n),r.createElement("div",{className:"".concat(a,"-inner"),id:o,role:"tooltip",style:s},"function"==typeof i?i():i))}var vw=["overlayClassName","trigger","mouseEnterDelay","mouseLeaveDelay","overlayStyle","prefixCls","children","onVisibleChange","afterVisibleChange","transitionName","animation","motion","placement","align","destroyTooltipOnHide","defaultVisible","getTooltipContainer","overlayInnerStyle","arrowContent","overlay","id","showArrow"],yw=function(e,t){var n=e.overlayClassName,i=e.trigger,a=void 0===i?["hover"]:i,o=e.mouseEnterDelay,s=void 0===o?0:o,l=e.mouseLeaveDelay,u=void 0===l?.1:l,c=e.overlayStyle,d=e.prefixCls,p=void 0===d?"rc-tooltip":d,f=e.children,h=e.onVisibleChange,C=e.afterVisibleChange,m=e.transitionName,g=e.animation,v=e.motion,y=e.placement,b=void 0===y?"right":y,x=e.align,w=void 0===x?{}:x,_=e.destroyTooltipOnHide,M=void 0!==_&&_,V=e.defaultVisible,k=e.getTooltipContainer,j=e.overlayInnerStyle,H=e.arrowContent,E=e.overlay,L=e.id,S=e.showArrow,P=void 0===S||S,A=ey(e,vw),T=(0,r.useRef)(null);(0,r.useImperativeHandle)(t,(function(){return T.current}));var N=qv({},A);"visible"in e&&(N.popupVisible=e.visible);var O=!1,q=!1;if("boolean"==typeof M)O=M;else if(M&&"object"===Av(M)){var I=M.keepParent;O=!0===I,q=!1===I}return r.createElement(dw,hc({popupClassName:n,prefixCls:p,popup:function(){return r.createElement(gw,{showArrow:P,arrowContent:H,key:"content",prefixCls:p,id:L,overlayInnerStyle:j},E)},action:a,builtinPlacements:mw,popupPlacement:b,ref:T,popupAlign:w,getPopupContainer:k,onPopupVisibleChange:h,afterPopupVisibleChange:C,popupTransitionName:m,popupAnimation:g,popupMotion:v,defaultPopupVisible:V,destroyPopupOnHide:O,autoDestroy:q,mouseLeaveDelay:u,popupStyle:c,mouseEnterDelay:s},N),f)};const bw=(0,r.forwardRef)(yw);const xw=r.forwardRef((function(e,t){var n=e.visible,i=e.overlay,a=r.useRef(null),o=Dy(t,a),s=r.useRef(null);function l(){Oy.cancel(s.current)}return r.useEffect((function(){return n?s.current=Oy((function(){var e;null===(e=a.current)||void 0===e||e.forcePopupAlign()})):l(),l}),[n,i]),r.createElement(bw,Object.assign({ref:o},e))}));var ww=ky;ww.Range=Ey,ww.Handle=ay,ww.createSliderWithTooltip=function(e){var t;return t=function(t){Fv(i,t);var n=$v(i);function i(){var e;return 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zv(i,[{key:"render",value:function(){return r.createElement(e,Object.assign({},this.props,{handle:this.handleWithTooltip}))}}]),i}(r.Component),t.defaultProps={tipFormatter:function(e){return e},handleStyle:[{}],tipProps:{},getTooltipContainer:function(e){return e.parentNode}},t};const _w=ww;var Mw=i(8607),Vw={};Vw.styleTagTransform=_v(),Vw.setAttributes=yv(),Vw.insert=gv().bind(null,"head"),Vw.domAPI=Cv(),Vw.insertStyleElement=xv(),fv()(Mw.A,Vw),Mw.A&&Mw.A.locals&&Mw.A.locals;const{createSliderWithTooltip:kw}=_w,jw=kw(_w.Range),Hw=({title:e,min:t,max:n,value:r,onChange:i,style:a={}})=>{const o={width:300,margin:50,...a};return(0,dc.jsxs)("div",{style:o,children:[(0,dc.jsx)("p",{children:e}),(0,dc.jsx)(jw,{allowCross:!1,min:t,max:n,value:r,onChange:i})]})};function Ew(e,t,n){e=+e,t=+t,n=(i=arguments.length)<2?(t=e,e=0,1):i<3?1:+n;for(var r=-1,i=0|Math.max(0,Math.ceil((t-e)/n)),a=new Array(i);++r<i;)a[r]=e+r*n;return a}class Lw extends 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Elle montre que le port de Marseille un des trois grands ports commerciaux français à la fin du XVIIIe siècle et que ses échanges allaient bien au-delà des rivages méditerranéens.  ","description_en":"This map allows you to locate Marseille among the other major French ports, on the one hand (Scale = France), and to visualize the relations of the Marseille port with foreign countries and markets (Scale = World). It shows that the port of Marseille was one of the three major French commercial ports at the end of the 18th century and that its trade went well beyond the Mediterranean shores.  ","comment_lire_fr":"Cette visualisation permet une interaction aussi bien au niveau de l\'échelle (France / Monde) qu\'au niveau des sources (Navigation / Commerce).<br/> Avec la combinaison \\"Navigation/France\\" , la carte affiche les départs depuis les 10 principaux ports de France: la largeur supérieure du triangle est proportionnelle au nombre des congés délivrés, la hauteur au tonnage moyen constaté. En survolant un port, une infobulle fournit les données précises pour ces deux variables. Pour Marseille, le tonnage moyen est le fruit d\'une estimation. En bas de la légende, il est possible d\'interagir avec la carte pour augmenter ou diminuer le nombre des ports français qui s\'affichent. Tous les registres des congés n\'étant pas conservés, les données pour la Provence, le Languedoc et une partie de la Bretagne ainsi que de la plupart des ports coloniaux ne s\'affichent pas. Pour plus de précisions sur la complétude des sources, voir http://vizsources.portic.fr/. <br/>La combinaison \\"Navigation\\"/Monde permet de visualiser le nombre des voyages qui aboutissent à Marseille en 1789, par pays (ou groupes de pays) de départ. Les catégories utilisées sont celles de la Balance du Commerce, ce qui permet de comparaisons. La largeur du triangle est proportionnelle au nombre de voyages et la hauteur au tonnage moyen, estimé à partir du type de navire. En sélectionnant l\'icône commerce, on fera apparaître alternativement les flux de commerce de Marseille par rapport aux autres ports français (en cliquant sur l\'icône \\"France\\") ou les flux de commerce du port de Marseille avec l\'étranger (comme des exportations et importations) en sélectionnant l\'icône Monde. Les flux sont représentés sous forme de cercles proportionnels, en pointant le curseur de la souris/du touchpad sur  le cercle, on fera apparaître le montant du flux illustré par le cercle.","comment_lire_en":"This visualization allows interaction both at the scale level (France / World) and at the source level (Navigation / Commerce).<br/> With the \\"Navigation/France\\" combination, the map displays departures from the 10 main ports in France: the upper width of the triangle is proportional to the number of departures issued, the height to the average tonnage observed. When hovering over a port, a tooltip provides precise data for these two variables. For Marseille, the average tonnage is the result of an estimate. At the bottom of the legend, it is possible to interact with the map to increase or decrease the number of French ports displayed. Not all leave records are kept, so data for Provence, Languedoc and part of Brittany as well as most colonial ports are not displayed. For more details on the completeness of the sources, see http://vizsources.portic.fr/. <br/>The \\"Navigation\\"/World combination allows you to visualize the number of voyages which ended in Marseille in 1789, by country (or groups of countries) of departure. The categories used are those of the Balance of Commerce, which allows comparisons. The width of the triangle is proportional to the number of voyages and the height to the average tonnage, estimated from the type of ship. By selecting the trade icon, we will alternately display the trade flows of Marseille in relation to other French ports (by clicking on the \\"France\\" icon) or the trade flows of the port of Marseille with foreign countries (such as exports and imports) by selecting the World icon. The flows are represented in the form of proportional circles, by pointing the mouse/touchpad cursor on the circle, the amount of flow illustrated by the circle will appear.","comment_cest_fait_fr":"Les données du commerce sont tirées de la base de données toflit18 pour l\'année 1789, et plus particulièrement : des données rapportées par la direction des fermes de Marseille pour les partenaires non-français, et des données du commerce local portant sur les partenaires non-français.<br/>Les données de la navigation internationale sont tirées de la base de données Navigocorpus pour l\'année 1789, avec un filtrage sur le port de départ dans le cas d\'un itinéraire comportant des escales, pour ce qui est des données internationales.<br/>Pour ce qui est de la navigation nationale et du classement des plus grands ports de France, nous avons utilisé les données des registres des congés de 1787 insérés dans Navigocorpus pour connaître leur nombre et calculer le tonnage moyen. Pour Marseille, port pour lequel le registre des congés n\'est pas conservé, nous avons calculé un tonnage moyen à partir des estimations du tonnage de navires entrés (connus grâce aux registres des dépositions des capitaines auprès du bureau de la Santé), en fonction de leur type (tartane, pinque, ...), puis multiplié ce tonnage moyen par le nombre des congés qui est connu grâce au compte-rendu des congés délivré en 1787.","comment_cest_fait_en":"Trade data are taken from the toflit18 database for the year 1789, and more particularly: data reported by the management of Marseille farms for non-French partners, and local trade data relating to non-French partners. -French.<br/>International navigation data are taken from the Navigocorpus database for the year 1789, with filtering on the port of departure in the case of an itinerary with stopovers, for international data.<br/>Regarding national navigation and the classification of the largest ports in France, we used data from the 1787 leave registers inserted in Navigocorpus to know their number and calculate the average tonnage. For Marseille, a port for which the leave register is not kept, we calculated an average tonnage from estimates of the tonnage of ships entered (known thanks to the registers of captains\' statements to the Health office), depending on of their type (tartane, pinque, etc.), then multiplied this average tonnage by the number of holidays which is known thanks to the leave report issued in 1787.","inputs":[],"outputs":["map_backgrounds/intro_map.geojson","intro_data_world.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données toflit18 - commerce international : année 1789, direction des fermes de Marseille, best guess region prodxpart, partenaires non Français, classés par partner_grouping (ou wars pour Italie et Allemagne)<br/>Données toflit18 - commerce local : année 1789, best guess region prod x part, partenaires non français, exclusion des customs_region \\"France\\" et \\"directions de terre\\"<br/>Données navigo navigation internationale - pays de départ des navires à destination de Marseille : pointcalls, outdate_fixed = 1789, pointcall_rank_dedieu = 1, state != France<br/>Données navigation nationale - plus grands ports de France : pour le tonnage moyen navigo pointcalls \\"Out\\" en France en 1787, pour le nombre de départs données des décomptes réalisés à partir des compte-rendus par ports (https://docs.google.com/spreadsheets/d/e/2PACX-1vRNAeIEFhB_RTm2xBgeuXl5oMtNIrGhWT6uCB2S9wEUblwDidRBwv9dp8D0S-YIPUyoASaG2p-NgfWD/pub)<br/>Tonnages calculés à partir des estimations par classe quand tonnage non indiqué (https://docs.google.com/spreadsheets/d/e/2PACX-1vTYdeIwpzaVpY_KS91cXiHxb309iYBS4JN_1_hW-_oyeysuwcIpC2VJ5fWeZJl4tA/pub)."},"dynamique-du-commerce":{"id":"dynamique-du-commerce","partie":"1.A","n_chapitre":1,"lien_permanent_visualisation":"/vizualisation/dynamique-du-commerce","titre_fr":"Dynamisme du commerce des principales directions de ferme","titre_en":"Dynamism of trade of the main farm managements","description_fr":"Le graphique représente les flux du commerce d\'exportations et d\'importations de marchandises de la France et de ses principaux ports de 1740 à 1789 et leurs tendances de moyen terme.","description_en":"The graph represents the flows of trade in exports and imports of goods from France and its main ports from 1740 to 1789 and their medium-term trends.","comment_lire_fr":"D’après les données liées au Bureau de la balance du commerce recueillies par Toflit18, le commerce total de Marseille double entre 1725 et 1738, passant de 11 M de livres tournois à 22 M de livres tournois, puis est multiplié par plus de cinq en deux ans pour atteindre 110 M de lt en 1740. Cette augmentation brutale ne peut être qu’un artefact statistique que nous ne sommes pas arrivés à expliquer. Peut-être est-ce que, comme à Dunkerque en 1789, les Fermes (qui prélevaient les traites et rassemblaient à cette occasion des informations sur les flux) ont-elles pu étendre le champ de leurs investigations ? Dans l’incertitude, nous avons choisi de ne représenter les données sur les graphiques qu’à partir de 1740.  <br/>Le graphique pour les données nationales (\\"France\\") comprend les courbes des importations/importations et leur tendance (la courbe foncée). Les graphiques pour chacune des directions comprennent deux courbes de même nature que celles des données nationales, ainsi qu’un histogramme qui donne le pourcentage que représentent les flux de ce port proportionnellement au total des ports français.  <br/>Il est possible d\'interagir avec la visualisation en sélectionnant dans le menu déroulant en bas le type de données qu\'on souhaite afficher (importations, exportations, avec ou sans les produits coloniaux et avec ou sans les partenaires coloniaux). L\'utilisateur peut également cocher les directions des Fermes dont il souhaite afficher les données. Les données pour chaque année peuvent être obtenues en pointant le curseur sur la courbe/l\'histogramme à l\'endroit approprié.","comment_lire_en":"According to data linked to the Office of the Balance of Trade collected by Toflit18, Marseille\'s total trade doubled between 1725 and 1738, going from 11 million tournament pounds to 22 million tournament books, then multiplied by more than five in two years to reach 110 million lt in 1740. This sudden increase can only be a statistical artifact that we have not been able to explain. Perhaps, as in Dunkirk in 1789, the Farms (which collected the drafts and on this occasion gathered information on the flows) were able to extend the scope of their investigations? Given the uncertainty, we have chosen to only represent the data on the graphs from 1740.  <br/>The graph for national data (\\"France\\") includes import/import curves and their trend (the dark curve). The graphs for each direction include two curves of the same nature as those of the national data, as well as a histogram which gives the percentage represented by the flows of this port in proportion to the total of French ports.  <br/>It is possible to interact with the visualization by selecting from the drop-down menu at the bottom the type of data you wish to display (imports, exports, with or without colonial products and with or without colonial partners). The user can also check the directions of the Farms whose data they wish to display. Data for each year can be obtained by pointing the cursor over the curve/histogram at the appropriate location.","comment_cest_fait_fr":"Les données du commerce sont tirées de la base de données toflit18, avec les sources issues des directions de fermes pour ce qui est des métriques locales et les sources nationales pour le niveau français, avec exclusion des partenaires français.<br/>Les séries \\"sans produits coloniaux\\" excluent les typologies de produits \\"Plantation foodstuffs\\".<br/>Les séries \\"sans colonies\\" excluent les partenaires correspondant à des colonies françaises (\\"Outre-mers\\", \\"Afrique\\", \\"Amériques\\", \\"Asie\\").<br/>Les régressions ont été calculées avec le module python regress.","comment_cest_fait_en":"Trade data are taken from the toflit18 database, with sources from farm management for local metrics and national sources for the French level, with exclusion of French partners.<br/>The “colonial products free” series exclude “Plantation foodstuffs” product types.<br/>The \\"without colonies\\" series exclude partners corresponding to French colonies (\\"Overseas\\", \\"Africa\\", \\"Americas\\", \\"Asia\\").<br/>Regressions were calculated with the Python regress module.","inputs":[],"outputs":["tradeDynamics.csv","tradeDynamics_reference_france_trade.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données toflit18, best guess region prodxpart pour les directions et best guess national partner pour le national, exclusion des partenaires français.<br/>Séries \\"sans produits coloniaux\\" : product = != \\"Plantation foodstuffs\\"<br/>Séries \\"sans colonies\\" : partner_grouping != [\\"Outre-mers\\", \\"Afrique\\", \\"Amériques\\", \\"Asie\\"]<br/>Régressions calculées avec le module python regress"},"correlation-prix":{"id":"correlation-prix","partie":"1.B","n_chapitre":1,"lien_permanent_visualisation":"/vizualisation/correlation-prix","titre_fr":"Corrélation des prix du blé dans la France du XVIIIe siècle","titre_en":"Correlation of wheat prices in 18th century France","description_fr":"Le graphique permet de visualiser les corrélations des prix du blé des différentes régions françaises et de voir le poids des déterminants géographiques qui influent sur l\'évolution de ces prix.","description_en":"The graph allows you to visualize the correlations of wheat prices in the different French regions and to see the weight of the geographical determinants which influence the evolution of these prices.","comment_lire_fr":"Cette visualisation permet de montrer que les prix du blé en France sont corrélés entre eux.  <br/>Elle propose deux types de représentations graphiques: via un réseau ou plus traditionnellement, par une carte.  <br/>Dans le réseau (menu \\"Positions des villes\\", avec choix: \\"Réseaux de corrélation de prix\\"), la place d\'une ville (dont le nom apparaît lorsque le curseur est placé dessus) par rapport à une autre indique la corrélation plus (lorsqu\'elle est proche) ou moins forte (lorsqu\'elle est éloignée) des prix du blé. Le placement des points n\'a donc rien à voir avec leur emplacement géographique.  Les points seront colorés en fonction de leur appartenance à un ensemble géographique (bassin versant) ou à une communauté de prix (les villes dont le mouvement des prix du blé ressemble à la ville principale). <br/>En sélectionnant, \\"Géographie\\" dans le menu \\"Position des villes\\", le réseau se transformera en carte géographique - cette fois-ci la place des villes correspond à leur place géographique sur le territoire métropolitain. La couleur de la ville est liée dans le cas des bassins versants à leur appartenance à un ensemble géographique dominé par un fleuve ou une grande rivière (la zone bleue pour la Loire par exemple). Si l\'on choisit \\"groupe de prix\\", la couleur sera celle établie par l\'algorithme d\'extraction de communautés. On peut ainsi constater l\'importance de la géographie pour expliquer les corrélations des prix du blé au XVIIIe siècle.","comment_lire_en":"This visualization shows that wheat prices in France are correlated with each other.  <br/>It offers two types of graphic representations: via a network or more traditionally, by a map.  <br/>In the network (\\"Positions of cities\\" menu, with choice: \\"Price correlation networks\\"), the place of a city (whose name appears when the cursor is placed on it) in relation to another indicates the correlation more (when it is close) or less strong (when it is far away) from wheat prices. The placement of the points therefore has nothing to do with their geographical location.  The points will be colored according to their belonging to a geographical group (watershed) or to a price community (cities whose wheat price movement resembles the main city). <br/>By selecting \\"Geography\\" in the \\"Position of cities\\" menu, the network will transform into a geographical map - this time the location of the cities corresponds to their geographic location on the metropolitan territory. The color of the city is linked in the case of watersheds to their belonging to a geographical area dominated by a river or a large river (the blue zone for the Loire for example). If we choose \\"price group\\", the color will be that established by the community extraction algorithm. We can thus see the importance of geography in explaining the correlations of wheat prices in the 18th century.","comment_cest_fait_fr":"La corrélation des prix est calculée à partir de  Federico, G., Schulze, M. S., & Volckart, O. (2021). European goods market integration in the very long run: from the Black Death to the First World War. The Journal of Economic History, 81(1), 276-308.<br/>La coloration topographique est effectuée au moyen l\'algorithme d\'extraction de communautés dit de la méthode de Louvain.","comment_cest_fait_en":"Price correlation is calculated from Federico, G., Schulze, M. S., & Volckart, O. (2021). European goods market integration in the very long run: from the Black Death to the First World War. The Journal of Economic History, 81(1), 276-308.<br/>Topographic coloring is carried out using the community extraction algorithm known as the Louvain method.","inputs":[],"outputs":["wheat_correlations_cities.csv","wheat_correlations_links.csv","map_backgrounds/bassins_versants.json"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Corrélation des prix calculée à partir de  Federico, G., Schulze, M. S., & Volckart, O. (2021). European goods market integration in the very long run: from the Black Death to the First World War. The Journal of Economic History, 81(1), 276-308.par Daudin & Pignède (Daudin et Pignède, Le cmmerce de la France au XVIIIe : inflation et révolution - https://drive.google.com/file/d/1-X-be9zeDtCVx6S80eKV-6MaCQuwx039/view?usp=sharing)<br/>Coloration topographique effectuée avec l\'algorithme de Louvain."},"exportations-sud-est":{"id":"exportations-sud-est","partie":"1.C","n_chapitre":1,"lien_permanent_visualisation":"/vizualisation/exportations-sud-est","titre_fr":"Marseille, exportateur des produits du sud-est","titre_en":"Marseille, exporter of products from the southeast","description_fr":"","description_en":"","comment_lire_fr":"","comment_lire_en":"","comment_cest_fait_fr":"Les données sont tirées de la base de données toflit18, pour les exports de l\'année 1789, en excluant les partenaires français,  et en agrégeant par province d\'origine des produits (valeur en lt.).<br/>Les provinces d\'origine \\"\\"Amérique\\" \\"Outre-Mers\\", ont été reclassées en \\"colonies\\", et les noms de pays ainsi que la dénomination \\"Monde\\" regroupés en \\"étranger\\".<br/>Les exports de Marseille sont repérés en isolant ceux déclarés par la direction des fermes de Marseille.","comment_cest_fait_en":"The data are taken from the toflit18 database, for exports for the year 1789, excluding French partners, and aggregating by province of origin of the products (value in lt.).<br/>The provinces of origin \\"America\\" ​​\\"Overseas\\" were reclassified as \\"colonies\\", and the names of countries as well as the name \\"World\\" grouped together as \\"foreign\\".<br/>Exports from Marseille are identified by isolating those declared by the Marseille farm management.","inputs":[],"outputs":["origins_for_marseille_exports.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données de toflit18, année 1789, partner_grouping != France, best guess region prod x part, exports, aggrégées par origin_province ( et valeur en lt.).<br/>Les provinces d\'origine \\"\\"Amérique\\" \\"Outre-Mers\\", ont été reclassées en \\"colonies\\", et les noms de pays + \\"Monde\\" regroupés en \\"étranger\\".<br/>Les exports de Marseille sont repérés avec customs_region= \'Marseille\'"},"marseille-port-structurant":{"id":"marseille-port-structurant","partie":"1.C","n_chapitre":1,"lien_permanent_visualisation":"/vizualisation/marseille-port-structurant","titre_fr":"Marseille, port structurant de la côte méditerranéenne","titre_en":"Marseille, a key port on the Mediterranean coast","description_fr":"Cette carte permet de visualiser la force d\'attraction de Marseille sur la navigation des ports français en Méditerranée","description_en":"This map allows you to visualize the force of attraction of Marseille on the navigation of French ports in the Mediterranean","comment_lire_fr":"Cette carte représente le nombre des congés délivrés dans les ports français en Méditerranée en 1789. Les couleurs distinguent les 4 provinces concernées (Roussillon, Languedoc, Provence et Corse). Chaque carré est proportionnel au nombre des congés délivrés, qui est indiqué plus précisément dans l\'infobulle qui s\'affiche en survolant chaque carré. La partie en rouge du carré représente le nombre de navires entrés à Marseille en 1789 en provenance du port représenté. La visualisation permet ainsi d\'apprécier la force d\'attraction du port de Marseille sur les ports français proches. Par ex., on retrouve à l\'entrée de Marseille en 1789 un nombre de navires partis depuis Toulon correspondant à 47% du total des congés délivrés à Toulon. ","comment_lire_en":"This map represents the number of leaves issued in French ports in the Mediterranean in 1789. The colors distinguish the 4 provinces concerned (Roussillon, Languedoc, Provence and Corsica). Each square is proportional to the number of leaves issued, which is indicated more precisely in the tooltip that appears when hovering over each square. The red part of the square represents the number of ships entering Marseille in 1789 from the port represented. The visualization thus makes it possible to appreciate the force of attraction of the port of Marseille on nearby French ports. For example, we find at the entrance to Marseille in 1789 a number of ships leaving from Toulon corresponding to 47% of the total leave delivered to Toulon. ","comment_cest_fait_fr":"Les données sont tirées de la base de données Navigocorpus (format \\"pointcalls\\"), pour l\'année 1789. Elles sont issues des registres du petit cabotage et du registre de déclarations des capitaines à la Santé de Marseille. Les doublons ont été éliminés.<br/>Les données ont été agrégées selon le port qui précède l\'entrée à Marseille et filtrées pour ne retenir que les navires en provenance d\'un port français en Méditerranée.<br/>Le nombre de sorties totales de chaque port est connu à partir des compte-rendus des congés (fonds G5 aux Archives Nationales).","comment_cest_fait_en":"The data are taken from the Navigocorpus database (\\"pointcalls\\" format), for the year 1789. They come from the registers of small coastal shipping and the register of captains\' declarations to Marseille Health. Duplicates have been eliminated.<br/>The data was aggregated according to the port preceding entry into Marseille and filtered to only retain ships coming from a French port in the Mediterranean.<br/>The number of total departures from each port is known from the leave reports (G5 funds at the National Archives).","inputs":[],"outputs":["map_backgrounds/intro_map.geojson","navigation_frlevant_to_marseille.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données de navigo/pointcalls, date_fixed contient 1789, pointcall_function = O, source_suite = \\"Registre du petit cabotage (1786-1787)\\" ou \\"la Santé registre de patentes de Marseille\\", net_route_marker != \\"Q\'.<br/>Pointcall original de chaque trajet reconstitué en allant chercher source_doc_id et un pointcall_rank_dedieu inférieur à celui de Marseille.<br/>Agrégation par nombre de voyages vers Marseille à partir de navigo.<br/>Calcul du nombre de sorties totales de chaque port à partir des compte-rendus du G5 (https://docs.google.com/spreadsheets/d/e/2PACX-1vS1YPWol3pcsjiTlDPVPW9ZVpWeu2wcIoobEM_c-MKk9YfeIMvmanCCoPEFjPA0xUPJEnQ9hM4AAgwI/pub)"},"diversite-produits-exportes":{"id":"diversite-produits-exportes","partie":"2.A","n_chapitre":2,"lien_permanent_visualisation":"/vizualisation/diversite-produits-exportes","titre_fr":"Le commerce de Marseille: un commerce diversifié","titre_en":"The trade of Marseille: a diversified trade","description_fr":"Ce graphique permet de visualliser la grande diversité des produits échangés à Marseille comparativement aux autres ports, en particulier Bordeaux, le plus important en valeur.","description_en":"This graph allows you to visualize the great diversity of products traded in Marseille compared to other ports, in particular Bordeaux, the most important in value.","comment_lire_fr":"Chaque brique représente une année d\'échanges pour chacun des ports listés. Plus la brique est rouge, plus le port en question a, dans cette année, commercé un grand nombre de produits, sans qu\'un seul ou un petit nombre représente une part très importante de ses échanges. Inversement, la teinte grise indique une grande concentration des échanges sur un nombre relativement petit de produits (pour Bordeaux, il s\'agit essentiellement de trois types de marchandises: le vin, le sucre et le café). L\'indice de concentration des échanges utilisé est l\'indice Herfindahl-Hirschmann qui mesure la concentration de 0 (le moins concentré) à 100% (le monopole d\'un seul produit). En déplaçant la souris sur le diagramme, il est possible de mettre en évidence une année en particulier.","comment_lire_en":"Each brick represents a year of trade for each of the ports listed. The redder the brick, the more the port in question has, in that year, traded a large number of products, without a single or small number representing a very significant part of its trade. Conversely, the gray tint indicates a large concentration of trade on a relatively small number of products (for Bordeaux, this concerns essentially three types of goods: wine, sugar and coffee). The trade concentration index used is the Herfindahl-Hirschmann index which measures concentration from 0 (the least concentrated) to 100% (the monopoly of a single product). By moving the mouse over the diagram, it is possible to highlight a particular year.","comment_cest_fait_fr":"Les données du commerce sont tirées de la base de données toflit18, limitée aux exports agrégés par bureau des fermes.<br/>Le calcul de la diversité du commerce est réalisé au moyen de l\'indice Herfindahl-Hirschmann, appliqué sur les typologies de produits de la classification toflit18 intitulée \\"Revolution&Empire aggregate\\", rapportées à la valeur d\'export en livre tournoi de chaque catégorie de produit.","comment_cest_fait_en":"Trade data are taken from the toflit18 database, limited to exports aggregated by farm office.<br/>The calculation of trade diversity is carried out using the Herfindahl-Hirschmann index, applied to the product typologies of the toflit18 classification entitled \\"Revolution & Empire aggregate\\", compared to the export value in tournament pounds of each product category .","inputs":[],"outputs":["herfindal-exports-marseille.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données toflit18, exports, best guess region prod_x_part, agrégation par bureau des fermes (customs_office).<br/>Calcul avec l\'indice Herfindahl-Hirschmann à partir des typologies de produits Revolution&Empire aggregate, rapportées à la valeur d\'export en livre tournoi de chaque catégorie de produit.Notes sur la réponse à cette question:Pour certains bureaux et directions et bureaux, on a calculé l\'indice Herfindhal en tout année dont les données sur les produits exportés étaient enregistrées en toflit18_all_flows.Les six directions principales sélectionnées étaient : BordeauxMarseilleRouenNantesLa RochelleBayonneLes huit bureaux de ferme sélectionnées pour l\'année 1789 étaient : BordeauxMarseilleRouenNantesLa RochelleBayonneSaint-MaloLe HavrePuisqu\'il y a plus de données pour les directions que pour les bureaux, on a bouclé sur toute année enregistrée et on a calculé l\'indice Herfindhal.La calculation étaient fait selon les étapes suivantes : calculer la somme de la valeur de tout produit exporté par la direction / le bureau ciblé → all_product_valueagréger les exports par type et sommé leur valeur agrégéeles agrégations étaient fait sur la colonne \'product_revolutionempire\'GROUP BY product_revolutionempire → product_revolutionempire, SUM(value) AS sum_valuecalculer le ratio entre la totale en valeur d\'un produit et la totale du bureau / direction et le multiplier par lui-même(sum_value/all_product_value)2 → carre_part_marchecalculer la somme du ratio"},"part-des-etrangers-dans-navigation":{"id":"part-des-etrangers-dans-navigation","partie":"2.B","n_chapitre":2,"lien_permanent_visualisation":"/vizualisation/part-des-etrangers-dans-navigation","titre_fr":"Part des navires étrangers dans la navigation marseillaise en comparaison avec d\'autres ports","titre_en":"Share of foreign ships in Marseille navigation in comparison with other ports","description_fr":"Le graphique montre la part de la navigation assurée par de navires étrangers dans les principaux ports de France en 1787. Le bas du graphique indique la distribution des pavillons des navires étrangers arrivés à Marseille en 1789,","description_en":"The graph shows the share of navigation carried out by foreign ships in the main ports of France in 1787. The bottom of the graph indicates the distribution of flags of foreign ships arriving in Marseille in 1789,","comment_lire_fr":"La partie supérieure de cette visualisation permet de situer la part de la navigation effectuée par des navires étrangers dans les 10 principaux ports français en 1787. Les données expriment le tonnage total, connu par les registres des congés (et estimé dans le cas de Marseille à partir du type du navire). Le cas de Marseille n\'est pas tout-à-fait comparable, car il prend en compte les entrées des navires, le registre des congés n\'étant plus conservé. La forte internationalisation du transport est néanmoins évidente. En survolant le graphique, l\'infobulle précise le pourcentage du tonnage des navires étrangers.<br/>La partie inférieure de cette visualisation montre le degré d\'implication des différents pavillons étrangers qui arrivent à Marseille en 1789. Le tonnage est estimé à partir du type de navire, le total s\'affiche dans l\'infobulle en survolant un pavillon ou groupe de pavillon. On constate ainsi l\'importance des marines méditerranéennes, qu\'il s\'agisse des anciens Etats italiens, des Espagnols (pour l\'essentiel, des Catalans), ou encore de Ragusois, c\'est à dire des navires de l\'actuelle Dubrovnik. La part des trois principales flottes nordiques (britanniques, néerlandais et danois) est d\'environ un tiers, le pavillon suédois étant quasiment absent en 1789 en raison de la guerre qui oppose la Suède à la Russie de 1788 à 1790.","comment_lire_en":"The upper part of this visualization allows us to locate the share of navigation carried out by foreign ships in the 10 main French ports in 1787. The data expresses the total tonnage, known from the leave registers (and estimated in the case of Marseille at from the type of vessel). The case of Marseille is not completely comparable, because it takes into account the entries of ships, the leave register is no longer kept. The strong internationalization of transport is nevertheless evident. When hovering over the graph, the tooltip specifies the percentage of foreign vessel tonnage.<br/>The lower part of this visualization shows the degree of involvement of the different foreign flags arriving in Marseille in 1789. The tonnage is estimated from the type of ship, the total is displayed in the tooltip when hovering over a flag or group of flag. We thus see the importance of the Mediterranean navies, whether they are the former Italian States, the Spanish (mainly the Catalans), or even the Ragusois, that is to say the ships of today\'s Dubrovnik. . The share of the three main Nordic fleets (British, Dutch and Danish) is around a third, the Swedish flag being almost absent in 1789 due to the war between Sweden and Russia from 1788 to 1790.","comment_cest_fait_fr":"Pour le calcul de la part des pavillons étrangers sur le total, le graphique utilise les données de Navigocorpus pour l\'année 1787 : pour l\'ensemble des ports de la façade atlantique représentés, il s\'agit des navires sortis, connus par les registres des congés. Pour Marseille, nous avons utilisé les entrées et les tonnages estimés à partir des types de navires.  <br />Pour la répartition des pavillons des navires étrangers arrivés à Marseille, nous avons utilisé les données de 1789. Le tonnage est basé sur des estimations fondées sur le type de navire (tratane, pinque, etc.), quand celui-ci n\'est pas directement mentionné par la source. ","comment_cest_fait_en":"To calculate the share of foreign flags in the total, the graph uses data from Navigocorpus for the year 1787: for all the ports on the Atlantic coast represented, these are ships released, known from the registers leave. For Marseille, we used the entries and tonnages estimated from the types of ships.  <br />For the distribution of flags of foreign ships arriving in Marseille, we used data from 1789. The tonnage is based on estimates based on the type of ship (tratane, pinque, etc.), when this is not directly mentioned by the source. ","inputs":[],"outputs":["share_of_strangers_1787_french_ports.csv","share_of_strangers_marseille_1789.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données navigo (flows), année 1787 et 1789 (indate_fixed), regroupement du détail par flag.<br/>Aggrégation par tonnage, calculés à partir des estimations fondées sur les classes de navire quand nécessaire (https://docs.google.com/spreadsheets/d/e/2PACX-1vTYdeIwpzaVpY_KS91cXiHxb309iYBS4JN_1_hW-_oyeysuwcIpC2VJ5fWeZJl4tA/pub)"},"part-des-francais-dans-provenance":{"id":"part-des-francais-dans-provenance","partie":"2.B","n_chapitre":2,"lien_permanent_visualisation":"/vizualisation/part-des-francais-dans-provenance","titre_fr":"Part des Français dans les provenances de voyages arrivés à Marseille","titre_en":"Share of French people in the origins of trips arriving in Marseille","description_fr":"Le graphique montre la part des entrées à Marseille effectuées par de navires de pavillon français par grandes catégories de provenance et pour les années de paix dont nous avons collecté les données. ","description_en":"The graph shows the share of entries into Marseille made by French-flagged ships by major categories of origin and for the years of peace for which we collected the data. ","comment_lire_fr":"Cette visualisation représente la présence de navires français dans les années de paix étudiées, en pourcentage du nombre d\'arrivées à Marseille (partie haute) ou en tonnage cumulé (estimé à partir du type de navire) (partie basse de la visualisation). Les infobulles fournissent le détail des données et les pourcentages. Les barres en couleur distinguent les ports de départ des navires, agrégés par pays ou groupes de pays. Le graphique permet tout d\'abord de constater le quasi-monopole de la flotte française dans le commerce en provenance des ports français et de l\'Empire ottoman. Dans le premier cas, cela s\'explique par la législation qui empêche aux étrangers de commercer entre deux ports français (s\'ils le font, ils sont alors vides ou en transit). Dans le second cas, c\'est l\'effet des droits prohibitifs qui pèsent sur les navires étrangers qui arrivent à Marseille depuis l\'Empire ottoman. En termes de tonnage cumulé, la navigation nationale et celle avec l\'Empire ottoman constituent les deux secteurs les plus importants. Ils sont suivis par les Etats de la péninsule italienne et de l\'Espagne (pour l\'essentiel, provenant des ports de ses côtes méditerranéennes), marchés sur lesquels la part de la navigation française n\'est pas négligeable, se situant autour de 40-50% des voyages. La navigation française depuis l\'Espagne est en perte de vitesse relative, les tonnages étant quant à eux plus stables. Dans le commerce avec les Provinces-Unies, la part des Français est très modeste; pour ce qui est des arrivées depuis de ports sous souveraineté britannique, la force des Français s\'explique par leur présence dans la pêche à Terre-Neuve: une quarantaine de navires par an viennent vendre leur poisson à Marseille, la pêche française étant protégée de la concurrence étrangère, frappée par de droits dissuasifs et des interdictions. Ainsi, le pourcentage important de navires français revèle en creux la relative faiblesse de la navigation vers Marseille depuis les Îles britanniques.","comment_lire_en":"This visualization represents the presence of French ships in the peace years studied, as a percentage of the number of arrivals in Marseille (upper part) or in cumulative tonnage (estimated from the type of ship) (lower part of the visualization). Tooltips provide data details and percentages. The colored bars distinguish the ports of departure of ships, aggregated by country or group of countries. The graph first allows us to see the quasi-monopoly of the French fleet in trade coming from French ports and the Ottoman Empire. In the first case, this is explained by legislation which prevents foreigners from trading between two French ports (if they do so, they are then empty or in transit). In the second case, it is the effect of the prohibitive duties which weigh on foreign ships which arrive in Marseille from the Ottoman Empire. In terms of cumulative tonnage, national navigation and that with the Ottoman Empire constitute the two most important sectors. They are followed by the States of the Italian peninsula and Spain (mainly from ports on its Mediterranean coasts), markets on which the share of French shipping is not negligible, standing at around 40 -50% of trips. French shipping from Spain is losing relative speed, with tonnages being more stable. In trade with the United Provinces, the French share is very modest; As for arrivals from ports under British sovereignty, the strength of the French is explained by their presence in fishing in Newfoundland: around forty ships per year come to sell their fish in Marseille, French fishing being protected from foreign competition, hit by dissuasive duties and bans. Thus, the large percentage of French ships implicitly reveals the relative weakness of navigation to Marseille from the British Isles.","comment_cest_fait_fr":"Les données de ce graphique ont été produites à partir de la base navigocorpus dans laquelle on a sélectionné les flux concernant des année de paix (1749,1769,1787,1789) à destination de Marseille. Les provenances ont été regroupées selon une classification ad hoc réalisée en fonction des questions de recherche que la visualisation sert à explorer.<br/>Les quantités correspondent à des agrégations des tonnages des navires ayant effectué les voyages, qui sont estimés à partir des types de navires quand c\'est nécessaire.","comment_cest_fait_en":"The data for this graph were produced from the navigocorpus database from which we selected the flows concerning peace years (1749, 1769, 1787, 1789) to Marseille. The provenances were grouped according to an ad hoc classification carried out based on the research questions that the visualization is used to explore.<br/>The quantities correspond to aggregations of the tonnages of the ships having carried out the voyages, which are estimated from the types of ships when necessary.","inputs":[],"outputs":["compare_french_ships_to_marseille_accross_time.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données navigo (flows), année de paix (1749,1769,1787,1789) (indate_fixed), regroupement par departure_state_1789_fr, destination = Marseille.<br/>Aggrégation des groupes de provenances selon les règles suivantes (pour departure_state_1789_fr) : <br/>\\"France\\": \\"France\\",<br/>\\"République de Gênes\\": \\"Péninsule italienne\\",<br/>\\"Royaume de Naples\\": \\"Péninsule italienne\\",<br/>\\"multi-Etat\\": \\"autre\\",<br/>\\"Espagne\\": \\"Espagne\\",<br/>\\"Royaume de Piémont-Sardaigne\\": \\"Péninsule italienne\\",<br/>\\"Empire ottoman\\": \\"Empire ottoman\\",<br/>\\"zone maritime\\": \\"autre\\",<br/>\\"Etats pontificaux\\": \\"Péninsule italienne\\",<br/>\\"Toscane\\": \\"Péninsule italienne\\",<br/>\\"Duché de Massa et Carrare\\": \\"Péninsule italienne\\",<br/>\\"Monaco\\": \\"France\\",<br/>\\"Principauté de Piombino\\": \\"Péninsule italienne\\",<br/>\\"République de Lucques\\": \\"Péninsule italienne\\",<br/>\\"République de Raguse\\": \\"Péninsule italienne\\",<br/>\\"Malte\\": \\"autre\\",<br/>\\"Autriche\\": \\"autre\\",<br/>\\"République de Venise\\": \\"Péninsule italienne\\",<br/>\\"Grande-Bretagne\\": \\"Grande-Bretagne\\",<br/>\\"Maroc\\": \\"autre\\",<br/>\\"Principauté de Lampédouse\\": \\"Péninsule italienne\\",<br/>\\"Provinces-Unies\\": \\"Provinces-Unies\\",<br/>\\"Portugal\\": \\"autre\\",<br/>\\"Hambourg\\": \\"autre\\",<br/>\\"Pologne\\": \\"autre\\",<br/>\\"Danemark\\": \\"autre\\",<br/>\\"Empire russe\\": \\"autre\\",<br/>\\"\\": \\"autre\\"<br/>Aggrégation par tonnage, calculés à partir des estimations fondées sur les classes de navire quand nécessaire (https://docs.google.com/spreadsheets/d/e/2PACX-1vTYdeIwpzaVpY_KS91cXiHxb309iYBS4JN_1_hW-_oyeysuwcIpC2VJ5fWeZJl4tA/pub)"},"styles-navigation":{"id":"styles-navigation","partie":"2.C","n_chapitre":2,"lien_permanent_visualisation":"/vizualisation/styles-navigation","titre_fr":"Des types de navigation variés","titre_en":"Various types of navigation","description_fr":"Cette visualisation permet d\'apprécier les caractéristiques des navires qui arrivent à Marseille dans les années de paix étudiées (1749, 1769, 1787, 1789). Plus particulièrement, il indique la distribution de leurs tonnage estimé, et le nombre d\'escales qu\'ils effectuent avant d\'arriver à Marseille. ","description_en":"This visualization allows us to appreciate the characteristics of the ships that arrived in Marseille in the years of peace studied (1749, 1769, 1787, 1789). More particularly, it indicates the distribution of their estimated tonnage, and the number of stopovers they make before arriving in Marseille. ","comment_lire_fr":"La carte en haut à gauche distingue par couleur trois grandes aires de provenance des navires arrivés à Marseille en 1749, 1769, 1787 et 1789. Le terme “Ponant” désigne, dans la France d’Ancien Régime, la façade atlantique, par opposition à celle méditerranéenne. Nous y incluons le Portugal, les ports de la France métropolitaine sur l’Atlantique et la Manche, les ports européens en Atlantique, mer du Nord et Baltique, ainsi que les navires de pêche en provenance de Terre-Neuve. Pour les ports des Pays-Bas autrichiens, ceux dans l\'actuelle Belgique ont été rattachés à la catégorie \\"Ponant\\" alors que ceux en Méditerranée (Trieste et Fiume, aujourd’hui Rijeka) ont été rattachés à la catégorie \\"Méditerranée occidentale\\". Cette dernière s\'étend dans cette visualisation à l\'ensemble des Etats italiens ainsi que Ragusa (Dubrovnik) et inclut donc une partie des ports dans la mer Adriatique. Nous y rattachons aussi les départs depuis les ports espagnols situés en Atlantique et l\'ensemble des départs depuis le Maroc.  Sur cette carte, les cercles représentent les différents ports de départ, dont le toponyme s\'affiche en les survolant. La taille du cercle est proportionnelle au nombre de départ des navires arrivés à Marseille depuis ces ports. Les mêmes couleurs se retrouvent dans les trois diagrammes correspondants à ces trois grandes aires géographiques.  <br/>Les diagrammes agrègent le nombre des voyages arrivés à Marseille depuis l\'ensemble des ports de cette aire géographique sur les 4 années étudiées. Les diagrammes affichent la distribution des tonnages (axe horizontal), estimé à partir du type de navire indiqué par les sources. La taille des cercles est proportionnelle au nombre des voyages (voir la légende à la verticale à gauche de chaque diagramme ; attention: l\'échelle change en fonction de l\'aire géographique). Les données s\'affichent en prenant en compte le nombre d\'escales effectués sur la route qui amène le navire depuis le port de départ déclaré jusqu\'à Marseille.  <br/>Le total des voyages par nombre d\'escale s\'affiche dans le rectangle en couleur à droite. Ainsi, on dénombre 317 voyages depuis l\'Empire ottoman et la mer Noire dont les capitaines ont effectué 2 escales. Le total des voyages par catégorie de tonnage s\'affiche dans le rectangle de couleur en dessous de chaque graphique : ainsi, on dénombre 3108 voyages de navires estimés à 50 tonneaux depuis l\'Europe méditerranéenne.  <br/>La visualisation permet de constater que la navigation depuis l\'Europe méditerranéenne est le fait pour l\'essentiel de petites unités, celle depuis l\'Empire ottoman est le fait de navires de taille moyenne, alors que celle depuis le Ponant concerne de navires de grande taille. Les navires depuis l\'Empire ottoman effectuent un nombre nettement plus élevé d\'escales que tous les autres.","comment_lire_en":"The map at the top left distinguishes by color three large areas of origin of the ships arriving in Marseille in 1749, 1769, 1787 and 1789. The term “Ponant” designates, in Ancien Régime France, the Atlantic coast, as opposed to the Mediterranean one. We include Portugal, the ports of mainland France on the Atlantic and the Channel, European ports in the Atlantic, North Sea and Baltic, as well as fishing vessels from Newfoundland. For the ports of the Austrian Netherlands, those in what is now Belgium were attached to the \\"Ponant\\" category while those in the Mediterranean (Trieste and Fiume, today Rijeka) were attached to the \\"Western Mediterranean\\" category. The latter extends in this visualization to all Italian states as well as Ragusa (Dubrovnik) and therefore includes part of the ports in the Adriatic Sea. We also include departures from Spanish ports located in the Atlantic and all departures from Morocco.  On this map, the circles represent the different departure ports, whose toponyms are displayed when hovering over them. The size of the circle is proportional to the departure number of ships arriving in Marseille from these ports. The same colors are found in the three diagrams corresponding to these three large geographical areas.  <br/>The diagrams aggregate the number of trips arriving in Marseille from all the ports in this geographical area over the 4 years studied. The diagrams display the distribution of tonnages (horizontal axis), estimated from the type of vessel indicated by the sources. The size of the circles is proportional to the number of trips (see the vertical legend to the left of each diagram; note: the scale changes depending on the geographical area). The data is displayed taking into account the number of stops made on the route which takes the ship from the declared port of departure to Marseille.  <br/>The total trips by number of stopovers are displayed in the colored rectangle on the right. Thus, there are 317 voyages from the Ottoman Empire and the Black Sea whose captains made 2 stopovers. The total voyages by tonnage category are displayed in the colored rectangle below each graph: thus, there are 3,108 voyages of ships estimated at 50 tons from Mediterranean Europe.  <br/>The visualization shows that navigation from Mediterranean Europe is mainly carried out by small units, that from the Ottoman Empire is carried out by medium-sized ships, while that from Ponant involves large ships. size. Ships from the Ottoman Empire make a significantly higher number of port calls than all others.","comment_cest_fait_fr":"Les données de ce graphique ont été fabriquées à partir de la base navigocorpus, dans laquelle on a sélectionné les flux provenant de la source archivistique correspondant au registre de patentes de Marseille, réduits à ceux se déroulant durant des années de paix (1759, 1779, 1799). Dans cet ensemble, nous avons identifié le premier port de départ des voyages enregistrés.<br/>Nous avons regroupé les ports français en deux groupes \\"Ponant\\" et \\"méditerrannée occidentale\\" à partir de la province de départ des voyages, et nous avons groupé les ports étrangers au moyen d\'une classification manuelle réalisée à partir des états de départ.<br/>Les tonnages sont calculés à partir des estimations fondées sur les classes de navire quand c\'est nécessaire.","comment_cest_fait_en":"The data for this graph were produced from the navigocorpus database, in which we selected the flows coming from the archival source corresponding to the Marseille patent register, reduced to those taking place during years of peace (1759, 1779, 1799). In this set, we identified the first port of departure for recorded voyages.<br/>We grouped French ports into two groups \\"Ponant\\" and \\"Western Mediterranean\\" based on the province of departure of the trips, and we grouped foreign ports by means of a manual classification carried out from the states of departure.<br/>Tonnages are calculated from estimates based on ship classes when necessary.","inputs":[],"outputs":["map_backgrounds/intro_map.geojson","styles_navigation_long_cours.csv","styles_navigation_long_cours_ports.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données issues de navigo/flows, destination_function=\\"O\\", source_suite = \\"la Santé registre de patentes de Marseille\\".<br/>Premier flow de chaque voyage (et nombre d\'étapes intermédiaires) retrouvé avec source_doc_id et travel_rank.<br/>Filtrage sur les années de paix (indate_fixed du premier flow différent de \\"1759\\", \\"1779\\", \\"1799\\")<br/>Sélection des ports français des groupes \\"Ponant\\" et \\"méditerrannée occidentale\\" à partir de departure_province selon les règles suivantes :<br/>\'Normandie\': \'Ponant\', <br/>\'Aunis\': \'Ponant\', <br/>\'Guyenne\': \'Ponant\', <br/>\'Languedoc\': \'méditerranée occidentale\', <br/>\'Provence\': \'méditerranée occidentale\', <br/>\'Flandre\': \'Ponant\', <br/>\'Picardie\': \'Ponant\', <br/>\'Corse\': \'méditerranée occidentale\', <br/>\'Bretagne\': \'Ponant\',<br/>\'Roussillon\': \'méditerranée occidentale\'<br/><br/>Sélection des ports étrangers des groupes \\"méditerrannée occidentale\\" à partir de departure_state_1789_fr selon les règles suivantes :<br/>\'Etats pontificaux\': \'méditerranée occidentale\', <br/>\'Hambourg\': \'Ponant\', <br/>\'Monaco\': \'méditerranée occidentale\', <br/>\'Provinces-Unies\': \'Ponant\', <br/>\'Prusse\': \'Ponant\', <br/>\'Grande-Bretagne\': \'Ponant\', <br/>\'République romaine\': \'méditerranée occidentale\', <br/>\'Duché de Massa et Carrare\': \'méditerranée occidentale\', <br/>\'Royaume de Naples\': \'méditerranée occidentale\', <br/>\'Malte\': \'méditerranée occidentale\', <br/>\'République ligurienne\': \'méditerranée occidentale\', <br/>\'Pologne\': \'Ponant\', <br/>\'République de Gênes\': \'méditerranée occidentale\', <br/>\'Autriche\': \'Ponant\', <br/>\'République de Raguse\': \'méditerranée occidentale\', <br/>\'Toscane\': \'méditerranée occidentale\', <br/>\'Danemark\': \'Ponant\',<br/>\'République de Venise\': \'méditerranée occidentale\', <br/>\'Maroc\': \'méditerranée occidentale\', <br/>\'Espagne\': \'méditerranée occidentale\', <br/>\'Empire ottoman\': \'empire ottoman\', <br/>\'Royaume de Piémont-Sardaigne\': \'méditerranée occidentale\', <br/>\'Suède\': \'Ponant\', <br/>\'Portugal\': \'Ponant\', <br/>\'Empire russe\': \'Ponant\', <br/>\'Brême\': \'méditerranée occidentale\', <br/>\'République de Lucques\': \'méditerranée occidentale\'<br/>Tonnages calculés à partir des estimations fondées sur les classes de navire quand nécessaire (https://docs.google.com/spreadsheets/d/e/2PACX-1vTYdeIwpzaVpY_KS91cXiHxb309iYBS4JN_1_hW-_oyeysuwcIpC2VJ5fWeZJl4tA/pub)<br/>"},"impact-guerre-sur-commerce-et-navigation":{"id":"impact-guerre-sur-commerce-et-navigation","partie":"3.A","n_chapitre":3,"lien_permanent_visualisation":"/vizualisation/impact-guerre-sur-commerce-et-navigation","titre_fr":"Impact de la guerre sur la croissance du commerce et de la navigation","titre_en":"Impact of the war on the growth of trade and navigation","description_fr":"Cette visualtion permet de montrer l\'évolution du commerce des principaux ports français au cours du XVIIIe siècle et d\'évaluer le poids relatif des exportations, des importations et du commerce colonial dans cette évolution.","description_en":"This visualization makes it possible to show the evolution of trade in the main French ports during the 18th century and to assess the relative weight of exports, imports and colonial trade in this evolution.","comment_lire_fr":"Les différents graphiques décrivent l\'évolution du commerce des principaux ports français en volume de commerce (en abscisse) en regardant l\'impact que les guerres ont pu avoir sur chacun d\'entre eux, afin de mesurer si cet impact est différent en fonction de la position géographique de ces ports. Afin de mieux comprendre ces évolutions, ils proposent également une lecture ciblant exclusivement les exportations ou les importations. Les trois dernières lignes analysent le commerce de ces ports en ôtant le commerce avec les colonies. En effet, ce dernier est particulièrement touché pendant les guerres du fait de la supériorité de la marine de guerre britannique. Chaque graphique propose deux courbes et deux chiffres qui leur correspondent. Le commerce du port est représenté par la courbe en vert et son évolution moyenne sur l\'ensemble de la période est donnée par le pourcentage indiqué en bleu en haut à gauche. La courbe en rouge décrit le niveau du flux commerce qui aurait existé en l\'absence de conflit (si l\'évolution du commerce avait continué sur le même rythme qu\'avant-guerre) et le chiffre en rouge à droite indique la perte moyenne de commerce due aux guerres sur toute la période. En déplaçant le curseur sur la courbe, vous verrez apparaître le volume de commerce en livres tournois et la perte estimée liée à la guerre (égale à 0 lorsqu\'il n\'y a pas de conflit). Le dernier cadran (navigation de Marseille) intègre des données sur la navigation de Marseille issue de différentes sources: le nombre d\'entrées relevé par Charles Carrière (1973) à partir des dépositions des capitaines; ceux issus de la même source saisis dans Navigocorpus qui permettent 1) d\'ajouter des données pour 1787, 1789 et 1799; 2) d\'indiquer le tonnage total estimé à partir des types de navires ; 3) de représenter les distances parcourues par les navires. Ces trois variables donnent une image différente de l\'impact de la guerre: celui-ci n\'est que de -22,9% en termes de nombre de navires entrés, mais de -44% pour le tonnage, et de -66,4% pour les distances. En d\'autres termes, en temps de guerre, les navires qui entrent à Marseille sont moins nombreux, plus petits, et proviennent des ports plus proches qu\'en temps de paix.","comment_lire_en":"The different graphs describe the evolution of the trade of the main French ports in volume of trade (on the abscissa) by looking at the impact that the wars may have had on each of them, in order to measure whether this impact is different depending on the geographical position of these ports. In order to better understand these developments, they also offer a reading targeting exclusively exports or imports. The last three lines analyze the trade of these ports by removing trade with the colonies. Indeed, the latter is particularly affected during wars due to the superiority of the British navy. Each graph offers two curves and two figures that correspond to them. The port\'s trade is represented by the green curve and its average evolution over the entire period is given by the percentage indicated in blue at the top left. The red curve describes the level of trade flow which would have existed in the absence of conflict (if the evolution of trade had continued at the same pace as before the war) and the red figure on the right indicates the average loss of trade due to wars throughout the period. By moving the cursor on the curve, you will see the trade volume in tournament pounds and the estimated loss linked to the war (equal to 0 when there is no conflict). The last dial (navigation of Marseille) integrates data on the navigation of Marseille from different sources: the number of entries recorded by Charles Carrière (1973) from the captains\' statements; those from the same source entered in Navigocorpus which allow 1) to add data for 1787, 1789 and 1799; 2) to indicate the total tonnage estimated from the types of vessels; 3) to represent the distances traveled by ships. These three variables give a different picture of the impact of the war: it is only -22.9% in terms of number of ships entered, but -44% for tonnage, and -66. 4% for distances. In other words, in times of war, the ships entering Marseille are fewer, smaller, and come from closer ports than in times of peace.","comment_cest_fait_fr":"Les données du commerce de ce graphique sont tirées de la base de données toflit18, agrégées par directions des fermes. Les produits coloniaux sont détectés au moyen de la classification toflit18 \\"product_sitc_simplEN\\" (ici, il s\'agit des produits relevant de la classe \\"Plantation foodstuffs\\" dans cette classification). Les partenaires coloniaux sont repérés au moyen de la classification toflit18 \\"partner_grouping\\" (quand ces derniers correspondent à \\"Outre-mers\\", \\"Afrique\\", \\"Amériques\\", ou \\"Asie\\".<br />Les régressions ont été calculées calculées avec le module python reg, à partir de la régression de l\'évolution de la période de paix précédant chaque guerre.<br />Les données de navigation sont issues de la base navigocorpus Carrière et de : Carrière Charles, Négociants marseillais au XVIIIe siècle. Contribution à l\'étude des économies maritimes, Marseille, Institut historique de Provence, 1973, 2 tomes.","comment_cest_fait_en":"The trade data in this graph are taken from the toflit18 database, aggregated by farm management. Colonial products are detected using the toflit18 classification \\"product_sitc_simplEN\\" (here, these are products falling under the class \\"Plantation foodstuffs\\" in this classification). Colonial partners are identified using the toflit18 classification \\"partner_grouping\\" (when the latter correspond to \\"Overseas\\", \\"Africa\\", \\"Americas\\", or \\"Asia\\".<br />The regressions were calculated with the python reg module, from the regression of the evolution of the period of peace preceding each war.<br />The navigation data comes from the Carrière navigocorpus database and from: Carrière Charles, Marseille merchants in the 18th century. Contribution to the study of maritime economies, Marseille, Historical Institute of Provence, 1973, 2 volumes.","inputs":[],"outputs":["impact-guerre-sur-croissance.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données toflit18 : flows, best_guess_region_prodxpart,  aggrégés par directions des fermes.<br/>Détection des produits coloniaux : product_sitc_simplEN = \\"Plantation foodstuffs\\"<br />Détection des partenaires coloniaux : partner_grouping [\\"Outre-mers\\", \\"Afrique\\", \\"Amériques\\", \\"Asie\\"]<br />Régressions calculées avec le module python reg, à partir de la régression de l\'évolution de la période de paix précédant chaque guerre.<br />Données de navigation issues de Carrière et de navigo (même méthode pour les régressions)."},"guerre-et-navigation":{"id":"guerre-et-navigation","partie":"3.B","n_chapitre":3,"lien_permanent_visualisation":"/vizualisation/guerre-et-navigation","titre_fr":"Qui profite de la guerre en termes de navigation ?","titre_en":"Who benefits from war in terms of navigation?","description_fr":"Cette visualisation montre les changements provoqués par la guerre sur la navigation de Marseille pour ce qui est des acteurs de la navigation (c\'est-à-dire des pavillons des navires qui arrivent à Marseille).","description_en":"This visualization shows the changes caused by the war on the navigation of Marseille in terms of the actors of navigation (i.e. the flags of the ships arriving in Marseille).","comment_lire_fr":"Le diagramme montre sur l\'axe verticale les années se terminant par \\"9\\" pour lesquelles nous avons collecté les données relatives aux navires entrés à Marseille. Elles alternent une année de paix et une année de guerre. L\'axe horizontal indique pour chaque année la distribution de différents groupes de pavillons. La perte en pourcentage pour chaque groupe, entre l\'année de paix et l\'année de guerre qui suit, s\'affiche en survolant le diagramme. Les groupes de pavillons sont différenciés par couleur, en fonction de leur statut lors de la guerre en cours ou de celle qui suit: neutre, français (en distinguant les navires des ports de la France méditerranéenne - \\"France du Levant\\" de ceux de l\'Atlantique - \\"France du Ponant\\"), belligérants alliés de la France, et ennemis de la France. Les données représentent le tonnage estimé agrégé (qui a été calculé sur la base du type de navires), en pourcentage. Elles ne prennent donc pas en compte la diminution globale du tonnage, que nous avons représentée ailleurs. Ainsi, si les navires français des ports méditerranéens ne perdent que quelques points en pourcentage (indiqués en noir \\"pp\\"), la perte est bien plus nette pour les navires de la France atlantique, dont le voyage devient trop risqué. Sans surprise, les pavillons ennemis disparaissent en temps de guerre (sauf pour ce qui est des prises des corsaires ou des navires parlementaires). Le grand gagnant des conflits, ce sont les pavillons neutres, qui accroissent considérablement leur part tant lors de la guerre de Sept Ans (1756-63) que pendant celle d\'Indépendance américaine (1778-1783). Les guerres de la décennie révolutionnaire sont radicalement différentes: en 1799 il n\'y a presque plus de neutres.","comment_lire_en":"The diagram shows on the vertical axis the years ending in \\"9\\" for which we collected data relating to ships entering Marseille. They alternate a year of peace and a year of war. The horizontal axis indicates for each year the distribution of different groups of flags. The percentage loss for each group, between the year of peace and the following year of war, is displayed by hovering over the chart. The groups of flags are differentiated by color, depending on their status during the current or subsequent war: neutral, French (distinguishing the ships from the ports of Mediterranean France - \\"France du Levant\\" from those of the Atlantic - \\"France du Ponant\\"), belligerent allies of France, and enemies of France. The data represents the aggregate estimated tonnage (which was calculated based on vessel type), as a percentage. They therefore do not take into account the overall reduction in tonnage, which we have represented elsewhere. Thus, if French ships from Mediterranean ports only lose a few percentage points (indicated in black \\"pp\\"), the loss is much clearer for ships from Atlantic France, whose journey becomes too risky. Unsurprisingly, enemy flags disappear in time of war (except for the capture of privateers or parliamentary ships). The big winner of the conflicts were the neutral flags, which considerably increased their share both during the Seven Years\' War (1756-63) and during that of American Independence (1778-1783). The wars of the revolutionary decade were radically different: in 1799 there were almost no neutrals left.","comment_cest_fait_fr":"Les données de ce graphique sont produites à partir de la base Navigocorpus, pour laquelle on a sélectionné les flux enregistrés grâce à la source archivistique du registre des patentes de Marseille pour les années 1749, 1759, 1769, 1779, 1787, 1789, et 1799.<br/>Le repérage des statuts des partenaires durant les guerres a été documenté qualitativement année par année par l\'équipe pour les besoins de cette publication.<br/>Les catégorisations sont réalisées en fonction du pavillon pour les navires étrangers, en fonction du lieu de naissance du capitaine pour la distinction entre France du Levant et France du Ponant.<br/>Pour les catégories correspondant à des pays étrangers, on projette sur les années de paix le statut des pays lors de la guerre qui suit afin de mesurer l\'impact du conflit sur la répartition des personnels de navigation.<br/>Les quantifications sont réalisées par tonnage aggrégé, calculé à partir des estimations fondées sur les classes de navire quand c\'est nécessaire.","comment_cest_fait_en":"The data in this graph are produced from the Navigocorpus database, for which we selected the flows recorded using the archival source of the Marseille patent register for the years 1749, 1759, 1769, 1779, 1787, 1789, and 1799 .<br/>The identification of the statuses of partners during the wars was qualitatively documented year by year by the team for the purposes of this publication.<br/>Categorizations are made according to the flag for foreign ships, according to the place of birth of the captain for the distinction between France du Levant and France du Ponant.<br/>For the categories corresponding to foreign countries, the status of the countries during the following war is projected onto the years of peace in order to measure the impact of the conflict on the distribution of navigation personnel.<br/>Quantifications are carried out by aggregate tonnage, calculated from estimates based on ship classes when necessary.","inputs":[],"outputs":["navigation_guerre.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données navigo/pointcalls.<br/>Sélection des années : \\"1749\\", \\"1759\\", \\"1769\\", \\"1779\\", \\"1787\\", \\"1789\\", \\"1799\\" - via date_fixed.<br/>Source_suite = \\"la Santé registre de patentes de Marseille\\".<br/>Utilisation d\'un tableau spécifiant le statut année par année (https://docs.google.com/spreadsheets/d/e/2PACX-1vRxr78qK0zubFIDR7w38JqWOkqD-P6uqZi-pXChSLwYxesUGJwZnxCx-0sYIKKxwr3SJvb5P5HVGW1o/pub)<br/><br/>Catégorisation :<br/>\\"neutre\\", \\"en guerre allié de la France\\", \\"en guerre ennemi de la France\\" : à partir de ship_flag_standardized_fr et du tableau ci-dessus<br/>\\"France du Levant\\" : captain_birthplace dans un port situé dans l\'une des provinces \\"Corse\\", \\"Provence\\", <br/>\\"France du Ponant\\" : tout ce qui n\'est pas Levant<br/>\\"Languedoc\\", \\"Roussillon\\".<br/><br/>Pour les catégories correspondant à des pays étrangers, on projette sur les années de paix le statut des pays lors de la guerre qui suit afin de mesurer l\'impact du conflit sur la répartition des personnels de navigation.<br/><br/>Aggrégation par tonnage, calculés à partir des estimations fondées sur les classes de navire quand nécessaire (https://docs.google.com/spreadsheets/d/e/2PACX-1vTYdeIwpzaVpY_KS91cXiHxb309iYBS4JN_1_hW-_oyeysuwcIpC2VJ5fWeZJl4tA/pub)"},"effets-guerre-sur-commerce-levant":{"id":"effets-guerre-sur-commerce-levant","partie":"3.C","n_chapitre":3,"lien_permanent_visualisation":"/vizualisation/effets-guerre-sur-commerce-levant","titre_fr":"Les effets de la guerre sur les importations du port de Marseille","titre_en":"The effects of the war on imports from the port of Marseille","description_fr":"Les deux graphiques illustrent l\'impact des guerres sur les importations de Marseille détaillées par partenaire. ","description_en":"The two graphs illustrate the impact of wars on Marseille\'s imports detailed by partner. ","comment_lire_fr":"La partie supérieure de la visualisation mesure l\'évolution du commerce par partenaire en valeur absolue (en livres tournois). Les zones grisées correspondent aux périodes de guerre. En plaçant le curseur sur les courbes, on fait apparaître le chiffre exact tiré des statistiques de la balance du commerce. La partie inférieure montre l\'évolution relative pour mieux faire apparaître les changements intervenus pour ce qui est des parts relatives des partenaires pendant les guerres. En plaçant le curseur sur l\'histogramme on fait apparaître le pourcentage exact de chacun des partenaires.","comment_lire_en":"The upper part of the visualization measures the evolution of trade per partner in absolute value (in tournament pounds). The gray areas correspond to periods of war. By placing the cursor on the curves, the exact figure taken from the balance of trade statistics appears. The lower part shows the relative evolution to better show the changes that occurred in the relative shares of the partners during the wars. By placing the cursor on the histogram, the exact percentage of each partner appears.","comment_cest_fait_fr":"Les données du commerce sont tirées de la base de données toflit18, dans laquelle on a sélectionné les imports déclarés par la direction des Fermes de Marseille.<br/>Le groupement des partenaires a été défini manuellement sur la base de la classification toflit18 \\"partner_grouping\\" pour les besoins de cette visualisation spécifique.","comment_cest_fait_en":"The trade data are taken from the toflit18 database, from which we selected the imports declared by the management of Fermes de Marseille.<br/>The partner grouping was manually defined based on the toflit18 classification \\"partner_grouping\\" for the purposes of this specific visualization.","inputs":[],"outputs":["evolution-exports-levant.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données toflit18, best guess region prodxpart, customs_region = Marseille, imports.<br/><br/>Aggrégation par valeur et par partner_grouping selon les règles suivantes :<br/>\\"Italie\\": \\"Italie & Espagne\\",<br/>\\"Espagne\\": \\"Italie & Espagne\\",<br/>\\"Levant et Barbarie\\": \\"Levant & Barbarie\\",<br/>\\"Angleterre\\": \\"Angleterre & Amériques\\",<br/>\\"Amériques\\": \\"Angleterre & Amériques\\",<br/>\\"Nord\\": \\"Nord, Hollande & Flandres\\",<br/>\\"Hollande\\": \\"Nord, Hollande & Flandres\\",<br/>\\"Flandre et autres états de l\'Empereur\\": \\"Nord, Hollande & Flandres\\""},"levant-navigation":{"id":"levant-navigation","partie":"3.C","n_chapitre":3,"lien_permanent_visualisation":"/vizualisation/levant-navigation","titre_fr":"La navigation depuis l’Empire ottoman vers Marseille","titre_en":"Navigation from the Ottoman Empire to Marseille","description_fr":"Cette carte représente le premier port de départ déclaré par les capitaines qui entrent à Marseille depuis un port de l\'Empire ottoman dans les années étudiées.","description_en":"This map represents the first port of departure declared by captains entering Marseille from a port in the Ottoman Empire in the years studied.","comment_lire_fr":"Cette carte montre les ports de départ des capitaines arrivés à Marseille en 1749, 1759, 1769, 1779, 1787, 1789 et 1799 en provenance d\'un port de l\'Empire ottoman. Le cercle est proportionnel au nombre de voyages concernés. En survolant les cercles, l\'infobulle indique le nombre de ceux-ci, le toponyme et le tonnage total agrégé que nous avons estimé à partir du type du navire. Cette carte montre la densité des relations entre Marseille et l\'Empire ottoman, et l\'importance de Smyrne et des ports tunisiens de Tunis et de Bône (aujourd’hui El-Annaba).","comment_lire_en":"This map shows the departure ports of captains arriving in Marseille in 1749, 1759, 1769, 1779, 1787, 1789 and 1799 from a port in the Ottoman Empire. The circle is proportional to the number of trips involved. Hovering over the circles, the tooltip indicates the number of these, the toponym and the total aggregate tonnage that we estimated from the type of vessel. This map shows the density of relations between Marseille and the Ottoman Empire, and the importance of Smyrna and the Tunisian ports of Tunis and Bône (today El-Annaba).","comment_cest_fait_fr":"Les données de cette visualisation sont produites à partir de la base de données Navigocorpus, dans laquelle nous avons sélectionné les flux provenant de la source archivistique du registre du petit cabotage, ou de celle du registre des patentes de Marseille. Dans cette dernière nous avons sélectioné les voyages au départ d\'un port appartenant à l\'Empire ottoman, pour les années 1749, 1759, 1769, 1779, 1787, 1789, ou 1799.<br/>Les tonnages sont calculés à partir des estimations par classe quand c\'est nécessaire.","comment_cest_fait_en":"The data for this visualization are produced from the Navigocorpus database, from which we have selected the flows coming from the archival source of the small cabotage register, or that of the Marseille patent register. In the latter we have selected voyages departing from a port belonging to the Ottoman Empire, for the years 1749, 1759, 1769, 1779, 1787, 1789, or 1799.<br/>Tonnages are calculated from estimates by class when necessary.","inputs":[],"outputs":["map_backgrounds/intro_map.geojson","navigation_depuis_levant.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données navigo, flows, departure_state_1789_fr = \\"Empire ottoman\\", source_suite = \\"\\"Registre du petit cabotage (1786-1787)\\" ou \\"la Santé registre de patentes de Marseille\\".<br/>Sélection des années : 1749, 1759, 1769, 1779, 1787, 1789, 1799<br/>Tonnages calculés à partir des estimations par classe quand nécessaire (https://docs.google.com/spreadsheets/d/e/2PACX-1vTYdeIwpzaVpY_KS91cXiHxb309iYBS4JN_1_hW-_oyeysuwcIpC2VJ5fWeZJl4tA/pub)."},"levant-navigation-guerre":{"id":"levant-navigation-guerre","partie":"3.C","n_chapitre":3,"lien_permanent_visualisation":"/vizualisation/levant-navigation-guerre","titre_fr":"Qui assure la navigation avec le Levant en temps de guerre ?","titre_en":"Who ensures navigation with the Levant in times of war?","description_fr":"Cette visualisation montre les changements provoqués par la guerre sur la navigation de Marseille pour ce qui est des acteurs de la navigation depuis l\'Empire ottoman","description_en":"This visualization shows the changes caused by the war on the navigation of Marseille with regard to the actors of navigation since the Ottoman Empire","comment_lire_fr":"L’axe vertical du diagramme montre les années se terminant par \\"9\\" dont nous avons collecté les données relatives aux navires entrés à Marseille. Elles alternent une année de paix et une année de guerre. Le couleur distingue les différents pavillons, en fonction de leur statut lors de la guerre qui suit: neutre, français (en distinguant les navires des ports de la France méditerranéenne - \\"France du Levant\\" de ceux de l\'Atlantique - \\"France du Ponant\\"), belligérants alliés de la France, et ennemis de la France. Les données représentent le tonnage agrégé estimé (calculé sur la base du type de navires) et sont affichées en pourcentage. Elles ne prennent donc pas en compte la diminution globale du tonnage, que nous avons représentée ailleurs. On constate tout d\'abord que l\'essentiel de la navigation avec l\'Empire ottoman est assuré par des navires français méditerranéens, et ce tant en temps de paix que de guerre (à l\'exception de 1799). La mise en place de convois escortés permet à ainsi de protéger ce commerce des attaques de la Navy et des corsaires britanniques. Les Français des ports méditerranéens perdent certes quelques points en pourcentage (indiqués en noir \\"pp\\") lors des conflits mais ne sont pas supplantés pour autant par les neutres. En 1799, en revanche, le commerce avec l\'Empire ottoman s\'effondre: les pertes pour les Français ne sont pas simplement en parts de marchés (-77%), mais aussi en absolu (ce que le graphique ne montre pas).","comment_lire_en":"The vertical axis of the diagram shows the years ending in \\"9\\" for which we collected data relating to ships entering Marseille. They alternate a year of peace and a year of war. The color distinguishes the different flags, depending on their status during the following war: neutral, French (distinguishing the ships from the ports of Mediterranean France - \\"France du Levant\\" from those of the Atlantic - \\"France du Ponant \\"), belligerent allies of France, and enemies of France. The data represents the estimated aggregate tonnage (calculated based on vessel type) and is displayed as a percentage. They therefore do not take into account the overall reduction in tonnage, which we have represented elsewhere. First of all, we note that most of the navigation with the Ottoman Empire is carried out by French Mediterranean ships, both in times of peace and war (with the exception of 1799). The establishment of escorted convoys thus made it possible to protect this trade from attacks by the Navy and British privateers. The French in Mediterranean ports certainly lose a few percentage points (indicated in black \\"pp\\") during conflicts but are not supplanted by neutrals. In 1799, on the other hand, trade with the Ottoman Empire collapsed: the losses for the French were not simply in market share (-77%), but also in absolute terms (which the graph does not show).","comment_cest_fait_fr":"Les données de cette visualisation sont produites à partir de la base de données Navigocorpus, dans laquelle nous avons sélectionné les flux provenant de la source archivistique du registre du petit cabotage, ou de celle du registre des patentes de Marseille. Dans cette dernière nous avons sélectioné les voyages au départ d\'un port appartenant à l\'Empire ottoman, pour les années 1749, 1759, 1769, 1779, 1787, 1789, ou 1799.<br/>Le repérage des statuts des partenaires durant les guerres a été documenté qualitativement année par année par l\'équipe pour les besoins de cette publication.<br/>Les catégorisations sont réalisées en fonction du pavillon pour les navires étrangers, en fonction du lieu de naissance du capitaine pour la distinction entre France du Levant et France du Ponant.<br/>Pour les catégories correspondant à des pays étrangers, on projette sur les années de paix le statut des pays lors de la guerre qui suit afin de mesurer l\'impact du conflit sur la répartition des personnels de navigation.<br/>Les quantifications sont réalisées par tonnage aggrégé, calculé à partir des estimations fondées sur les classes de navire quand c\'est nécessaire.","comment_cest_fait_en":"The data for this visualization are produced from the Navigocorpus database, from which we have selected the flows coming from the archival source of the small cabotage register, or that of the Marseille patent register. In the latter we have selected voyages departing from a port belonging to the Ottoman Empire, for the years 1749, 1759, 1769, 1779, 1787, 1789, or 1799.<br/>The identification of the statuses of partners during the wars was qualitatively documented year by year by the team for the purposes of this publication.<br/>Categorizations are made according to the flag for foreign ships, according to the place of birth of the captain for the distinction between France du Levant and France du Ponant.<br/>For the categories corresponding to foreign countries, the status of the countries during the following war is projected onto the years of peace in order to measure the impact of the conflict on the distribution of navigation personnel.<br/>Quantifications are carried out by aggregate tonnage, calculated from estimates based on ship classes when necessary.","inputs":[],"outputs":["navigation_levant_guerre.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données navigo/pointcalls.<br/>Sélection des années : \\"1749\\", \\"1759\\", \\"1769\\", \\"1779\\", \\"1787\\", \\"1789\\", \\"1799\\" - via date_fixed.<br/>Source_suite = \\"la Santé registre de patentes de Marseille\\".<br/>state_fr = \\"Empire ottoman\\"<br/>Utilisation d\'un tableau spécifiant le statut année par année (https://docs.google.com/spreadsheets/d/e/2PACX-1vRxr78qK0zubFIDR7w38JqWOkqD-P6uqZi-pXChSLwYxesUGJwZnxCx-0sYIKKxwr3SJvb5P5HVGW1o/pub)<br/><br/>Catégorisation :<br/>\\"neutre\\", \\"en guerre allié de la France\\", \\"en guerre ennemi de la France\\" : à partir de ship_flag_standardized_fr et du tableau ci-dessus<br/>\\"France du Levant\\" : captain_birthplace dans un port situé dans l\'une des provinces \\"Corse\\", \\"Provence\\", <br/>\\"France du Ponant\\" : tout ce qui n\'est pas Levant<br/>\\"Languedoc\\", \\"Roussillon\\".<br/><br/>Pour les catégories correspondant à des pays étrangers, on projette sur les années de paix le statut des pays lors de la guerre qui suit afin de mesurer l\'impact du conflit sur la répartition des personnels de navigation.<br/><br/>Agrégation par tonnage, calculés à partir des estimations fondées sur les classes de navire quand nécessaire (https://docs.google.com/spreadsheets/d/e/2PACX-1vTYdeIwpzaVpY_KS91cXiHxb309iYBS4JN_1_hW-_oyeysuwcIpC2VJ5fWeZJl4tA/pub)"},"fonctionnement-port-franc":{"id":"fonctionnement-port-franc","partie":"annexe","n_chapitre":5,"lien_permanent_visualisation":"/vizualisation/fonctionnement-port-franc","titre_fr":"Le fonctionnement du port franc (1789)","titre_en":"How does the free port work ? (1789)","description_fr":"","description_en":"","comment_lire_fr":"Le graphique montre les valeurs des flux de commerce liés à la Direction des Fermes de Marseille en 1789. Le sens des flèches indique qui est exportateur et qui est importateur. Les données sont abondamment discutées dans l’index.","comment_lire_en":"The graph shows the values ​​of trade flows linked to the Direction des Fermes de Marseille in 1789. The direction of the arrows indicates who is an exporter and who is an importer. The data are discussed extensively in the index.","comment_cest_fait_fr":"Les données de ce diagrammesont tirées de la base de données toflit18 pour l’année 1789, en utilisant le filtre \\"Best Guess customs region product x partner\\" pour identifier les flux pertinents (voir https://toflit18.medialab.sciences-po.fr/#/exploration/sources).","comment_cest_fait_en":"The data in this diagram is taken from the toflit18 database for the year 1789, using the filter \\"Best Guess customs region product x partner\\" to identify relevant flows (see https://toflit18.medialab.sciences-po. fr/#/exploration/sources).","inputs":[],"outputs":["fonctionnement-port-franc-complete.gexf","fonctionnement-port-franc-simplified.gexf"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données toflit18, année 1789, best_guess_region_prodxpart.<br/>Regroupement à partir de customs_region, partner_simplification, et 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secondary-page",children:[(0,dc.jsx)(ar,{children:(0,dc.jsx)("title",{children:vf(t,i)})}),(0,dc.jsx)("div",{className:"centered-contents",children:(0,dc.jsxs)(Xu.Provider,{value:{onRegisterVisualization:function(e){o({type:"MERGE",payload:{[e.callerId]:{...e}}})},onClickCallerScroll:()=>{},activeCallerId:void 0},children:[(0,dc.jsx)("h1",{children:t}),(0,dc.jsx)(e,{components:{Caller:({id:e})=>(0,dc.jsx)(XT,{id:e,lang:i}),Link:Ve}})]})})]})};function KT(e){const{Caller:t}=e.components||{};return t||function(){throw new Error("Expected component `Caller` to be defined: you likely forgot to import, pass, or provide it.")}(),(0,dc.jsxs)("div",{id:"part-1",children:[(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"intro",mode:"toflit18_world"})}),(0,dc.jsx)("p",{children:"À la veille de la Révolution française, malgré le développement de ses échanges extérieurs vers les espaces atlantique et asiatique, le commerce de Marseille reste profondément ancré en Méditerranée. La carte ci-contre, qui illustre la valeur des exportations et des importations marseillaises telles qu’elles furent enregistrées par le bureau de la balance du commerce, le montre. En 1789, ses deux partenaires privilégiés sont les Etats italiens (notamment le royaume de Naples) et le Levant. Le dynamisme Atlantique existe aussi: le volume des échanges avec les colonies françaises en Amérique (catégorie \"Amériques\" sur la carte) arrive presque au même niveau en 1789. Un autre partenaire important est l’Espagne: les liens de Marseille avec Cadix, nœud de communication obligé avec l'Amérique espagnole, sont anciens et importants. Le commerce avec l’Europe du Nord et la Baltique est plus modeste, et dominé par l'exportation de produits méditerranéens (huile d’olive, etc.). "}),(0,dc.jsx)("p",{children:"Durant la décennie 1780, alors que les échanges avec le Levant déclinent, les flux vers et en provenance des espaces atlantiques et asiatiques connaissent une croissance accélérée. D’une part, la hausse de la demande européenne et levantine en sucre, café, cacao et indigo dynamise les échanges de Marseille avec les colonies françaises des Caraïbes (Guadeloupe, Martinique, Saint-Domingue). D’autre part, l’ouverture du commerce avec les États-Unis, qui viennent d’obtenir leur indépendance en 1783, ont ouvert des marchés nouveaux pour les produits français. Enfin, la suppression du monopole de Lorient en 1769 a ouvert le marché des Indes orientales, (c’est-à-dire la Chine et les comptoirs français en Inde) aux négociants marseillais."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"intro",mode:"navigo_world"})}),(0,dc.jsxs)("p",{children:["Les données relatives aux arrivées de navires à Marseille confirment pour l’essentiel celles de la balance du commerce: elles montrent la part toujours dominante des trafics méditerranéens, en provenance de la péninsule italienne, du Levant et d’Espagne.",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"La navigation méditerranéenne de Marseille est d’ailleurs encore plus significative si on considère que la catégorie «Flandres et États de l’Empereur» comprend en réalité davantage des départs depuis Trieste et Fiume (Rijeka) que depuis Ostende.",children:"?"})," Les navires méditerranéens sont de tonnage moindre par rapport à ceux qui relient le port phocéen aux mondes atlantiques. La carte représente visuellement le tonnage moyen, qui repose sur nos estimations. Au niveau agrégé, les trafics de proximité courts mais fréquents, comme le cabotage en Méditerranée nord-occidentale, tout comme les voyages à plus large rayon dans la Méditerranée centrale et orientale, l’emportent largement sur la navigation océanique."]}),(0,dc.jsxs)("p",{children:["Le port de Marseille possède plusieurs spécificités géographiques et institutionnelles qu’il convient d’explorer pour mieux comprendre les logiques géographiques et économiques qui l’animent en 1789. Ici, il est utile de le mettre en regard du cas de Dunkerque auquel nous avons consacré une ",(0,dc.jsx)("a",{className:"c15",href:"https://medialab.github.io/portic-storymaps-2022/#/fr",rel:"noopener noreferrer",target:"_blank",children:"autre étude"})," dans le cadre du programme Portic",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Voir le site de ce programme ANR.",children:"?"}),". Comme Dunkerque, Marseille est un port franc - c’est-à-dire qu’il bénéficie de privilèges douaniers spécifiques - et sa position géographique lui donne un avantage de proximité avec certains des partenaires commerciaux de la France. Dunkerque a utilisé ses atouts pour devenir, à sa mesure, un port d’entrepôt pour l’Angleterre et l’Europe du Nord. Ses liens commerciaux – même frauduleux – avec le reste de la France forment une partie significative de son activité. En est-il de même pour Marseille ? "]}),(0,dc.jsx)("p",{children:"Pour le savoir, nous suivons trois pistes. Dans un premier temps, nous analyserons le commerce de Marseille sur le temps long, pour souligner qu’elles présentent des caractéristiques différentes de celles des autres ports français. Ensuite nous examinerons le marché du blé pour faire apparaître l’aire commerciale de Marseille qui remonte assez loin dans l’intérieur, notamment le long du Rhône et de la Saône. Finalement, l’examen du mouvement des navires et des marchandises permet de mesurer plus finement l’importance de Marseille pour le Sud-Est de la France. Marseille est intégré à son arrière-pays de manière beaucoup plus puissante que Dunkerque ou La Rochelle."}),(0,dc.jsx)("h2",{id:"h.9aefnfi0kgry",children:"1.A Marseille, un port international important"}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"intro",mode:"toflit18_france"})}),(0,dc.jsx)("p",{children:"La carte ci-contre montre la valeur du commerce de chaque direction des Fermes en 1789: Marseille est en deuxième position, juste derrière Bordeaux. Il lui est même légèrement supérieur en ce qui concerne les importations, mais Bordeaux le dépasse largement en ce qui concerne les exportations, composées pour une part importante de ré-exportations de produits coloniaux (sucre, café) vers l’Europe du Nord."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"intro",mode:"navigo_france"})}),(0,dc.jsxs)("p",{children:["L’activité maritime de Marseille est sans équivalent à la fin de l'Ancien Régime: le nombre de congés délivrés en 1787 à Marseille est plus du double qu’à Bordeaux.",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Le congé est un document légal que tout navire sortant d’un port français doit posséder. Il ne correspond pas exactement au nombre de sorties car, dans certains cas, le congé est valable pour une aller-retour, ou pour une période de quelques mois, voire d’une année (Marzagalli et Pfister, 2014). Si tout navire sortant d’un port français doit être pourvu d’un congé, leur nombre n’est pas parfaitement comparable entre un port et l’autre, dans la mesure où dans certains endroits il existe des congés valables pour une année, quel que soit le nombre d’allers-retours. Ce n’est toutefois pas le cas en Provence, où seuls les petits pêcheurs peuvent bénéficier d’un congé annuel.",children:"?"})," Cet indicateur est toutefois assez approximatif car il additionne des navires de taille très différente. Il est donc utile de comparer aussi les tonnages. Ceux-ci nous sont connus en 1787 pour la plupart des ports français grâce aux registres des congés, mais nous ne disposons, pour Marseille, que du tonnage des navires sortis du port. Nous avons donc procédé à une estimation des tonnages entrés à partir du type de navire, information consignée par le bureau de la Santé de Marseille aussi bien dans les registres des dépositions des capitaines que dans les cahiers du petit cabotage. Cette estimation nous permet d’évaluer le tonnage moyen des navires entrés pour pouvoir comparer approximativement les trafics maritimes de Marseille avec ceux des autres ports français. En raison du très grand nombre de bâtiments assurant une navigation de proximité, le tonnage moyen d’un navire sortant de Marseille est moitié moins élevé que celui d’un navire sortant de Bordeaux, et inférieur à celui des navires desservant Nantes ou Le Havre. Mais comme le nombre de sorties depuis Marseille est plus du double que dans ces autres grands ports, au total les trafics du port de Marseille dépassent en tonnage ceux de n’importe quel autre port métropolitain. "]}),(0,dc.jsxs)("p",{children:["Marseille est donc un des deux ports français les plus importants en 1789. Sa participation dans le système colonial est moindre que celle de Bordeaux; il est en revanche le premier port européen (et levantin) français. Il convient ensuite de se pencher sur l’évolution au cours du XVIIIe siècle. Nous n’avons malheureusement pas de sources aisément mobilisables pour mesurer ce dynamisme avec précision pour ce qui est de la navigation. Les données sur les sorties commencent en 1732, avec les comptes rendus de congés, qui ne fournissent que le nombre de navires par grandes catégories (Marzagalli & Pfister-Langanay, 2011). Pour les entrées, les dépositions des capitaines au bureau de la Santé existent depuis 1709, et précisent origine et cargaison navire par navire, mais ils ne comprennent pas toutes les arrivées",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"La navigation dite du petit cabotage - celle provenant d’une aire comprise entre la Catalogne et la Toscane, Corse incluse, ne transportant pas de passagers ou d’autres produits spécifiques (tels l’huile, le vin, etc.), et n’ayant pas fait de rencontres en mer avec des corsaires - est en effet enregistrée à part. Les cahiers du petit cabotage ne sont conservés qu’à partir de 1786, ce qui les rend inutilisables dans ce cadre.",children:"?"}),". Néanmoins, en dépit de ces inconvénients, la corrélation de deux courbes est très forte (taux de corrélation = 0.89) entre 1732 et 1780 ce qui nous assure que nos statistiques décrivent de manière fiable l’évolution des flux maritimes marseillais."]}),(0,dc.jsx)("p",{children:"Le nombre des congés délivrés à Marseille montre une nette croissance dans les années 1740 (et ce, en dépit de la guerre de succession d’Autriche) et une reprise au lendemain de la guerre de Sept Ans, sur des niveaux nettement plus élevés qu’avant ce conflit. La crise financière liée aux faillites en chaîne des courtiers en 1774, très sensible, est de courte durée. Le port accroît son commerce au XVIIIe siècle en élargissant sa géographie commerciale vers l’Atlantique et l’océan Indien, tout en gardant une position de force dans les marchés méditerranéens et notamment levantins. "}),(0,dc.jsx)("p",{children:"Ces données de navigation présentent néanmoins un défaut pour comprendre ce qui a pu faire la différence à Marseille : elles n’ont pas d’équivalent dans les autres ports français et ne permettent pas d’étude comparative. Nous nous sommes tournés donc vers les données commerciales."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"dynamique-du-commerce",kind:"exports",rows:"Marseille,Bordeaux"})}),(0,dc.jsx)("p",{children:"En 1740, Marseille assure près de 30% des exportations de la France, alors que Bordeaux en représente moins de 10%. Les exportations de textile à destination du Levant connaissant une certaine stagnation à partir des années 1750, puis une baisse sensible dans les années 1770. Toutefois, le trafic de Marseille continue de progresser, tiré par les exportations de denrées coloniales. La place relative de Marseille recule tout de même, au profit de Bordeaux. Alors que les exportations françaises croissent de 1,3% par an entre 1740 et 1789, celles de Marseille entre 1740 et 1780 n’augmentent que de 0,4% par an et celles de Bordeaux... de 3,2% par an."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"dynamique-du-commerce",kind:"exports",rows:"Marseille, Bordeaux, Rouen, Nantes, La Rochelle"})}),(0,dc.jsx)("p",{children:"L’analyse de la tendance de la croissance des exportations principales régions françaises vient renforcer l’idée que Marseille était un port important au début de la période et que sa position s’est légèrement dégradée au cours du siècle au bénéfice de Bordeaux. Certes, Marseille est devenu le deuxième port colonial en France, à parité avec Nantes, mais loin derrière Bordeaux. Le moindre dynamisme du port phocéen dans ce secteur spécifique qui soutient l’envol de Bordeaux, a plusieurs raisons. La distance aux Antilles est un peu plus importante que pour les ports Atlantiques, elle est surtout plus éloignée des principaux marchés de réexportation pour les produits coloniaux français, qui se trouvent dans le nord de l’Europe; enfin, Marseille ne pratique que le commerce en droiture puisque les négociants ont fait le choix de ne pas participer au commerce triangulaire."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"dynamique-du-commerce",kind:"imports",rows:"Marseille, Bordeaux, Rouen, Nantes, La Rochelle"})}),(0,dc.jsx)("p",{children:"Le succès de Marseille après 1815 ne s’inscrit donc pas dans la continuité de sa dynamique du XVIIIe siècle."}),(0,dc.jsx)("h2",{id:"h.s8r3lug8yvf9",children:"1.B Marseille, un hub méditerranéen du blé "}),(0,dc.jsx)("p",{children:"Puisque l’importance de Marseille semble plutôt liée à sa situation d’importateur, plutôt que sa connexion avec les marchés extérieurs en forte croissance que sont les colonies françaises, il est intéressant d’étudier de manière plus précise ces caractéristiques en analysant sa zone d’influence en France. Malheureusement, les sources pour mesurer les relations économiques à l’intérieur du Royaume sont plus rares que celles pour mesurer les relations économiques à l’extérieur. Une mesure traditionnelle de l’importance des relations bilatérales entre les différentes régions est la synchronicité des fluctuations des prix, notamment pour le produit le plus important des économies pré-industrielles : le blé."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{colorby:"community",id:"correlation-prix",layout:"network"})}),(0,dc.jsxs)("p",{children:["Nous disposons pour cette étude des données rassemblées par Federico, Schulze et Volckart (2021). Ils disposent de prix annuels du blé pour 129 villes en France entre 1209 et 1940, mais seules 108 sont incluses dans cette analyse car nous restreignons l’étude à la période 1716-1815. Nous calculons des corrélations entre le prix du blé dans chaque paire de villes puis utilisons cette valeur comme une mesure de proximité. Nous utilisons ensuite un algorithme pour déterminer des groupes de villes. Le résultat est affiché dans le réseau ci-contre. Les liens n’y sont représentés que si la corrélation entre deux villes est supérieure à 0,87 (0,87 = 3,5^0,5-1). Marseille se place dans un groupe qui se différencie de ceux dans lesquels sont placés Rouen, Nantes, Orléans, Issoire et Bordeaux.",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Les positions dans le réseau, décidées par l’algorithme, ne sont pas géographiques. Elles sont simplement le fruit de la proximité du comportement des prix du blé entre chaque ville. Ainsi, deux villes ayant presque les mêmes prix du blé seront voisines dans le réseau.",children:"?"})," "]}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{colorby:"bassin",id:"correlation-prix",layout:"geography"})}),(0,dc.jsx)("p",{children:"Pour comprendre ces corrélations, nous pouvons reporter les villes sur la carte des six principaux bassins versants français. Les villes de notre étude sont réparties sur tout le territoire et représentent tous les bassins versants. Dans la carte ci-contre, les villes sont colorées suivant leur appartenance à l’un ou à l’autre. "}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{colorby:"community",id:"correlation-prix",layout:"geography"})}),(0,dc.jsx)("p",{children:"Nous pouvons maintenant comparer les groupes issus de notre analyse du réseau des villes obtenu en utilisant la corrélation comme une mesure de proximité d’une part et des bassins versants d’autre part. C’est ce que fait la carte ci-contre. Les groupes de Rouen, Bordeaux, Nantes et Issoire sont assez cohérents et correspondent respectivement à la Normandie et la vallée de la Seine, le Sud-Ouest (bassin Adour-Garonne), la Bretagne et le sud de la Loire et l’Auvergne. Le groupe d’Orléans est moins géographiquement cohérent, et les bassins Rhin-Meuse et Artois-Picardie sont dispersés entre plusieurs groupes. "}),(0,dc.jsx)("p",{children:"Le groupe de Marseille correspond assez exactement à l’ensemble du vaste bassin Rhône-Méditerranée, hors Carcassonne et Narbonne (qui, en partie sans doute à cause du canal du Midi, regardent plus en direction de Bordeaux). Sa cohérence (il n’y a pas de discontinuité géographique contrairement au groupe d’Orléans) suggère que les flux des échanges commerciaux du port de Marseille irriguent une vaste zone économique dépendante de Marseille. "}),(0,dc.jsxs)("p",{children:["Il serait intéressant d’effectuer le même travail pour des produits moins pondéreux que le blé. Les sources manquent pour le faire sur l’ensemble du pays. Ce qu’il est possible, par contre, c’est de comparer l’évolution des valeurs unitaires des biens importés",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Les biens exportés sont trop différents entre chaque port pour que l’analyse soit intéressante.",children:"?"})," dans les cinq ports du Royaume pour lesquels nous avons des données sur une période assez longue: Nantes, Marseille, Bordeaux, Bayonne et La Rochelle. Ce travail a été fait par Daudin et Pingnède (2021). Ils montrent que les prix marseillais sont peu corrélés avec ceux des autres ports et que, surtout, cette corrélation décline au cours du temps, alors que les quatre ports de la façade atlantique voient augmenter toutes leurs corrélation bilatérales. "]}),(0,dc.jsx)("h2",{id:"h.o2phdo3p8par",children:"1.C Marseille, porte du Sud-Est de la France "}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"marseille-port-structurant"})}),(0,dc.jsx)("p",{children:"Nous venons de voir que la conjoncture commerciale de Marseille était assez différente de celle des autres ports français. Par ailleurs, l’étude de la structure des prix des blés en France suggère que Marseille domine économiquement un arrière-pays très vaste. Dans cette section, nous allons essayer de comprendre la manière dont Marseille s’insère dans des logiques économiques d’échelles variées au niveau national."}),(0,dc.jsxs)("p",{children:["La première échelle est celle du pourtour méditerranéen. Elle peut être analysée à partir de données collectées dans le cadre du programme Portic. Quelle est la part des navires partant des autres ports français en Méditerranée qui déclare Marseille comme destination ? La comparaison entre le nombre des congés délivrés dans chaque port du Sud-Est en 1789 (où par Sud-Est nous entendons les ports de Provence, Languedoc, du Roussillons et de la Corse) et le nombre des entrées à Marseille en provenance de chacun de ces ports démontre l’attractivité de Marseille. Il ne s’agit pas d’un port marginalisé dans sa propre région comme peut l’être celui de ",(0,dc.jsx)("a",{className:"c15",href:"https://medialab.github.io/portic-storymaps-2021/fr/",rel:"noopener noreferrer",target:"_blank",children:"La Rochelle"}),". Les ports de Provence (Toulon, Saint-Tropez, Arles, Fréjus, Bandol, Sanary-sur-Mer, Bormes et La Seyne) sont manifestement dans l’orbite de la cité phocéenne. Le cas de Cassis ou des Bormes, où tous les congés délivrés correspondent à des entrées à Marseille, sont les plus emblématiques. "]}),(0,dc.jsx)("p",{children:"En revanche, les trafics de Sète et Narbonne, tous deux situés en Languedoc, sont moins dépendants de Marseille - c’est également ce qui était ressorti de l’examen des corrélations du prix du blé. Les ports du Roussillon (Collioure, Port-Vendres et Saint-Laurent-de-la-Salanque) et la Corse sont encore moins liés à Marseille."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{colonies:"oui",id:"exportations-sud-est",inconnu:"oui"})}),(0,dc.jsxs)("p",{children:["La seconde source que nous pouvons utiliser fournit l’origine des produits exportés en 1789 par la Direction des Fermes de Marseille. Elle comprend aussi les bureaux d’Arles, La Ciotat, La Penne, Lambesc et Septèmes (voir Annexe), mais les exportations vers l’étranger de ces autres bureaux sont très faibles par rapport à l’origine des produits exportés de la France dans son ensemble. Les données de la Balance du Commerce confortent les données de navigation. Cependant, pour des raisons probablement liées au fonctionnement du port franc (voir ce ",(0,dc.jsx)("a",{className:"c15",href:"https://medialab.github.io/portic-storymaps-2023/#/fr/atlas/fonctionnement-port-franc",rel:"noopener noreferrer",target:"_blank",children:"graphique"}),' qui donne une idée de la multiplicité et de la complexité des sources), nous ne disposons de l’origine des produits exportés par Marseille que pour moins de la moitié de ses exportations. Sur 80 M. de lt d’exportations, 42 M. sont donc d’origine "inconnue", alors que 25 M. viennent des colonies. Les 15 M. restants sont dominés par les produits provençaux (9 M.) et lyonnais (1.5 M.). En raison de ces lacunes, il est donc nécessaire d’aller au-delà des sources pour pouvoir analyser le lien entre Marseille et son arrière-pays. ']}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"exportations-sud-est"})}),(0,dc.jsxs)("p",{children:["Pour aller plus loin, nous émettons deux hypothèses. D’une part, il n’y a pas de produits coloniaux parmi les produits d’origine inconnue. C’est plausible, car les ré-exportations coloniales sont tirées d’un document qui leur est propre. D’autre part, l’origine des produits d’origine inconnue se répartit suivant les mêmes proportions que l’origine des produits d’origine connue. Nous ne disposons pas de raisons de penser que ce n’est pas le cas.",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"À vrai dire, les origines inconnues ne sont pas dispersées aléatoirement dans les différents bureaux de Marseille. Marseille - Domaine d'Occident et Marseille, Poids et Casse n’en déclarent jamais (et il y en a une poignée dans les exportations de Marseille). Mais nous n’avons pas percé le mystère de la règle de répartition des différents flux d’exportation dans ces différentes sources.",children:"?"})," "]}),(0,dc.jsx)("p",{children:"Si on accepte ces deux hypothèses, il faut multiplier par 3,8 (57 M d’exportations d’origine non-coloniales / 15 M d’exportations connues) les montants des exportations connues. Marseille exporterait donc 34,2 M de produits venant de Provence (34,2=9×3,8). C’est plus que les exportations connues venant de Provence de toute la France (14.5 M), mais cet écart peut tout à fait être expliqué par les 61 M d’exportations françaises d’origine inconnue. Restent donc 5,5 M. de produits venant de Provence dont on sait qu’ils ne sont pas exportés par Marseille (5,5=14,5-9). AInsi 86% des produits provençaux exportés par la France (0,86=34,2/(34,2+14,5-9)) passeraient par Marseille."}),(0,dc.jsx)("p",{children:"Appliquons le même raisonnement pour le Lyonnais: Marseille exporterait 5,7 M de lt de produits originaires de cette région (5,7=1,5×3,8). La France exporte 24 M. de produits de cette région. Donc 20% des produits originaires du Lyonnais exportées (0,2=5,7/(24+5,7-1,5) passeraient par Marseille. Par le même raisonnement, elle exporte 2,85 M de lt de produits du Languedoc (2,85= 0,75×3,8), soit 19% des exportations totales (0,19=2,85/(12,7+2,85-0,75)). Elle exporte aussi 18% des produits originaires d’Île de France (0,18=0,5×3,8/(9+0,5×3,8-0,5)) et 25% des produits originaires du Dauphiné (0,25=0,15×3,8/(1,85+0,15×3,8-0,15)."}),(0,dc.jsx)("p",{children:"Marseille est manifestement le principal relais de son arrière-pays provençal vers l’étranger. Par contre, les provinces avec lesquelles elle a un marché des blés intégré (Languedoc, Lyonnais et Dauphiné) ne l’utilisent pas - du moins à la fin de l’Ancien Régime - comme port d’exportation majoritaire, peut-être parce qu’elles assurent elles-mêmes leur commerce vers les voisins espagnols, italiens et suisses. Elle est sans doute aussi la voie d’exportation des produits du bassin de l’Île de France vers la Méditerranée. "})]})}function QT(e){return(0,dc.jsxs)("div",{id:"part-1",children:[(0,dc.jsx)("p",{children:"Au vu de l’existence d’un port franc, est-ce que Marseille est intégré à l’économie français ou plutôt elle domine le marché du Sud-Est ? Est-ce que le fait que Marseille soit relativement autonome par rapport au marché français mais ait eu une forte emprise sur le Sud-Est est un facteur de force ? Plus grande autonomie par rapport aux dynamiques françaises. GD : Sans elle, notre question n’a pas de sens puisque Marseille serait trop lié à la France"}),(0,dc.jsx)("p",{children:"caractéristiques de Marseille: participent peu à dynamiques qui caractérisent les autres ports français"}),(0,dc.jsx)("p",{children:"présence des Provençaux dans la navigation de Marseille -> Marseille port méditerranéen"}),(0,dc.jsx)("h2",{id:"h.wwcfzm6r9k8n",children:"(Intro C passe ici et devient I.A) : Pas exceptionnel du côté de la croissance1.A Intégration de Marseille au reste du royaume vu par les prix (devient le 1B)"}),(0,dc.jsxs)("p",{children:["Est-ce que les prix de Marseille évoluent à court/moyen terme comme ceux du reste de la France ? Intégration de Marseille par rapport au reste de l’économie vue par les prix ?Une évolution des prix différente qu’ailleurs en France: La co-évolution des prix pour certains types de produits démontre l’intégration de Marseille dans le commerce du royaume ? (voir article ",(0,dc.jsx)("a",{className:"c20",href:"https://drive.google.com/file/d/1-X-be9zeDtCVx6S80eKV-6MaCQuwx039/view?usp%3Dshare_link",rel:"noopener noreferrer",target:"_blank",children:"Daudin"}),")"]}),(0,dc.jsx)("p",{children:"Paramètres (voir projet gephi sur le git) : "}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"liens créés avec : (corrélation + 1) au carré"}),(0,dc.jsx)("li",{children:"filtré les liens > 3.5 (max 4)"}),(0,dc.jsx)("li",{children:"couleur = modularité"}),(0,dc.jsx)("li",{children:"spatialisation ForceAtlas 2"})]}),(0,dc.jsx)("p",{children:"Nous avons ensuite annoté la visualisation avec les cours d’eau qui semblent prépondérants dans l’interprétation des corrélations de prix :"}),(0,dc.jsx)("p",{children:"Nous avons ensuite étudié le réseau des corrélations pour un ensemble réduits de ports français (1714-1789) : "}),(0,dc.jsx)("h2",{id:"h.o2phdo3p8par",children:"1.B Marseille, porte du sud-est de la France "}),(0,dc.jsx)("p",{children:"(sud-est = Provence, Languedoc, Lyonnais, Corse et Roussillon)"}),(0,dc.jsx)("p",{children:"NB: Expliquer fonctionnement de la Ferme/port franc"}),(0,dc.jsx)("p",{children:"montrer importance de l’hinterland (pour quels produits ?)"}),(0,dc.jsx)("p",{children:"montrer importance du petit cabotage"}),(0,dc.jsx)("p",{children:"montrer l’importance des transporteurs locaux"}),(0,dc.jsx)("p",{children:"NB: Dans cette partie il faudrait aussi expliquer le fonctionnement du port franc:"}),(0,dc.jsx)("p",{children:"Il y a un souci avec la compréhension du fonctionnement du port franc de Marseille. Voir les commentaires de Pierre et Guillaume:"}),(0,dc.jsx)("p",{children:"Expliquer le fonctionnement du port franc. Mystère des différents bureaux. déclarés par Toflit18 1789..:"}),(0,dc.jsx)("p",{children:"Hors 1789 & Importations : "}),(0,dc.jsx)("p",{children:'Toujours "Marseille"'}),(0,dc.jsx)("p",{children:"Exports de 1789, des bureau que nous avons rassemblés"}),(0,dc.jsx)("p",{children:'"Marseille" (2202 flux en 1789)'}),(0,dc.jsx)("p",{children:'MDO "Marseille - Domaine d\'Occident" (1359)'}),(0,dc.jsx)("p",{children:'MPC "Marseille – Poids et Casse" (203 flux)'}),(0,dc.jsx)("p",{children:'"Marseille" : utilisé seulement par F2B14 tableaux 5 et 20, pour les exportations vers l’Afrique, les Amériques et le Monde (ré-exportations de produits coloniaux")'}),(0,dc.jsx)("p",{children:'MPC "Marseille -- Poids et Casse" : 202 flux d’ exportations vers la France (AN F12 1666) + 1 exportation vers l’Asie (ANOM F2B14 tableau 28)'}),(0,dc.jsx)("p",{children:'Que vers "Marseille" et que des produits français'}),(0,dc.jsx)("p",{children:'MDO "Marseille – Domaine d’Occident" : le reste'}),(0,dc.jsx)("p",{children:"Dont 2 exportations vers l’Asie d’ANOM F2B14 tableau 28"}),(0,dc.jsx)("p",{children:"Ce fameux tableau 28 porte sur le commerce des particuliers vers l’Asie (y compris en fait des envois de la Compagnie ?)"}),(0,dc.jsx)("p",{children:"Et 120 exportations vers la France (aussi AN F12 1666)"}),(0,dc.jsx)("p",{children:'Les grandes catégories de produits sont présentes dans "MDO" et "MPC"'}),(0,dc.jsx)("p",{children:"Ne correspond pas à ce que dit Rambert : "}),(0,dc.jsx)("p",{children:"- MDO n’est d’après lui que du colonial"}),(0,dc.jsx)("p",{children:"- MPC est d’après lui le plus actif et porte sur tout ce qui est vendu à Marseille."}),(0,dc.jsx)("p",{children:"Mystère à éclairer."}),(0,dc.jsx)("p",{children:"Il faudrait comparer les exportations de MDO vers la France avec les flux miroirs, et peut-être celle de MPC avec les flux miroirs. Y a-t-il double compte ou régime douanier différent ?"}),(0,dc.jsx)("p",{children:'Rambert, tome IV, p. 225: "Les plus importants [bureaux, ndr] étaient au nombre de trois: le bureau du fameux droit de 20% perçu au profit de la Chambre de Commerce en même temps que le droit de Consulat; le bureau des fermes du domaine d\'Occident qui percevait un droit de 3% sur les marchandises d\'origine coloniale [je comprends = importations depuis les colonies, ndr], enfin le bureau du Poids et Casse, où 75 peseurs publics procédaient au pesage des marchandises vendues sur place et percevaient au profit du Roi un droit qui avait été doublé en 1669. Note 1: Colbert avait pris cette mesure pour donner au Roi une compensation aux pertes subies par l\'application de l\'édit du port franc. [Donc, j\'interprète: droit sur toutes les marchandises vendues à Marseille, ndr]. C\'était le bureau le plus actif; il délivrait les acquits-à-caution, recevait les manifestes des capitaines et faisait visiter les colis à leur débarquement, percevait les droits sur les marchandises étrangères envoyées directement de Marseille aux colonies françaises et plombait celles qui étaient expédiées en transit [Je ne sais pas si Rambert dit "le plus actif" pour dire "celui qui fait plus d\'opérations" ou pour dire "toutes les marchandises passent par là", comme il devrait être, vu qu\'il parle de "toutes les marchandises vendues à Marseille"]".'}),(0,dc.jsxs)("p",{children:["Pour ces informations, Rambert presque recopie ce qui avait écrit Julliany en 1812 : ",(0,dc.jsx)("a",{className:"c20",href:"https://books.google.sm/books?id%3DB43FQMyap0sC%26printsec%3Dfrontcover%26hl%3Dit%26source%3Dgbs_vpt_read#v%3Donepage%26q%26f%3Dfalse",rel:"noopener noreferrer",target:"_blank",children:"https://books.google.sm/books?id=B43FQMyap0sC&printsec=frontcover&hl=it&source=gbs_vpt_read#v=onepage&q&f=false"})]}),(0,dc.jsx)("p",{children:"Guillaume: D’après mon étude pour les escargots du datascape dunkerque, je n’ai pas l’impression qu’il y ait des doubles comptes. Voir Présentation Données Marseille dans Toflit18.pptx et Pour graphiques escargots.do et Pour graphiques escargots.log. Hypothèse: MPC représente des biens français qui ont été mis à l’entrepôt et en sortent pour la consommation locale de Marseille."}),(0,dc.jsx)("p",{children:"Regarder les stats pour 1789 (origine des exports)"}),(0,dc.jsx)("p",{children:"Ci-dessus : "}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"Liens roses = Marseille rapporteur"}),(0,dc.jsx)("li",{children:"Liens verts = France rapporteur"}),(0,dc.jsx)("li",{children:"network_bureaux_with_mirrors.png"})]}),(0,dc.jsx)("p",{children:"Ci-dessus : "}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"Liens roses = Marseille rapporteur"}),(0,dc.jsx)("li",{children:"Liens verts = France rapporteur"}),(0,dc.jsx)("li",{children:"network_bureaux_with_mirrors_simplified.png"})]}),(0,dc.jsx)("p",{children:"Titre: Nombre de congés des ports du Sud-Est et par province en 1789"}),(0,dc.jsx)("p",{children:"Titre: Ratios entre le nombre de navires arrivant à Marseille et le nombre total des congés de ports de la région en 1789. NB: les ports dont le ratio est > 101% ne figurent pas ici: Bormes et Cassis. "}),(0,dc.jsx)("p",{children:"Titre: Ratios entre le nombre de navires arrivant à Marseille et le nombre total des congés de ports de la région en 1789. "}),(0,dc.jsx)("p",{children:"La comparaison entre le nombre des congés de chaque port du Sud-Est en 1789 et le nombre des entrées à Marseille en provenance de chacun de ces ports démontre l’attractivité de Marseille. Les ports les plus polarisés par la cité phocéenne se situent en Provence (Toulon, Saint-Tropez, Arles, Fréjus, Bandol, Sanary-sur-Mer, Bormes et La Seyne) et en Corse. Le cas de Cassis, petit port très proche de Marseille, est le plus emblématique parmi les ports provençaux qui pouvaient sans doute bénéficier, comme c’est le cas en Normandie et en Bretagne, d’un congé annuel pour les trafics intérieurs à la province, ce qui permettait de nombreux allers-retours vers Marseille qui n’apparaissent qu’une seule fois parmi les congés. "}),(0,dc.jsx)("p",{children:"En revanche, Sète et Narbonne, tous deux situés en Languedoc, sont nettement moins polarisés par Marseille. Par conséquent, l’attractivité de Marseille pour le commerce des ports du Sud-Est semble plus forte dans sa propre province, la Provence, que dans la province voisine, le Languedoc. Les ports du Roussillon (Collioure, Port-Vendres et Saint-Laurent-de-la-Salanque) sont encore moins liés à Marseille. Ces données confortent celles de la balance du commerce quant à l’origine des produits exportés par Marseille en 1789."})]})}function JT(e){const{Caller:t}=e.components||{};return t||function(){throw new Error("Expected component `Caller` to be defined: you likely forgot to import, pass, or provide it.")}(),(0,dc.jsxs)("div",{id:"part-2",children:[(0,dc.jsx)("p",{children:"La diversification du commerce est une autre explication possible de la résilience de Marseille au XIXe siècle ? La diversification recouvre en réalité trois types de phénomènes. Elle peut renvoyer aux produits: une économie diversifiée est plus à même de résister à des chocs politiques et économiques majeurs. Elle peut renvoyer aux hommes, ici les acteurs du commerce. Enfin, elle peut désigner la diversité des types de navigation."}),(0,dc.jsx)("h2",{id:"h.ipbpmiriq4tr",children:"2.A Diversité des produits du commerce de Marseille"}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"diversite-produits-exportes"})}),(0,dc.jsx)("p",{children:"Pour étudier la diversité des exportations de Marseille, nous calculons des indices de Herfindahl : il s’agit de la somme des carrés de la part de chaque produit, suivant une classification unifiée en cent-cinquante produits au cours des années et des ports. Cet indice est égal à un si un seul produit constitue toutes les exportations, et est proche de zéro si tous les produits ont la même part de marché. De ce point de vue, Bordeaux est exceptionnel en 1750 : son indice est de 75% alors que les autres ports ont des indices entre 23% (Bayonne) et 40% (Nantes). Ceci est dû à la forte spécialisation de ses exportations sur un petit nombre de marchandises: le vin et les produits coloniaux (café, sucre)."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{annee:"1750",id:"diversite-produits-exportes"})}),(0,dc.jsx)("p",{children:"Cette hiérarchie évolue peu au cours du siècle. La Rochelle devient un port d’exportation très spécialisé (72% en 1789), dépassant même Bordeaux en cette année (qui descend exceptionnellement à 54%). Marseille devient le port le plus diversifié (entre 27 et 29% entre 1775 et 1789), alors que Bayonne perd de la diversification durant la guerre d’Indépendance américaine, Rouen passe au-dessus de 40% et Nantes fluctue autour de 40%. "}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{annee:"1789",id:"diversite-produits-exportes"})}),(0,dc.jsx)("p",{children:"Marseille est donc le moins concentré des ports d’exportation en 1789 et surtout c’est le port qui connaît une diversification grandissante au cours du siècle. Il contraste fortement avec Bordeaux et La Rochelle qui sont très spécialisés ou le deviennent au cours du siècle. Il faut toutefois noter que Marseille n’est pas beaucoup plus diversifiée que certains ports de l’Atlantique, notamment Bayonne, mais Marseille a un volume de commerce beaucoup plus important que ce dernier. "}),(0,dc.jsx)("h2",{id:"h.5xt17flpsq8c",children:"2.B Diversité des acteurs de la navigation de Marseille"}),(0,dc.jsx)("p",{children:"Est-ce que la particularité de Marseille, et un facteur de sa résilience, est à rechercher plutôt du côté d’une présence d’acteurs plus diversifiés qu’ailleurs dans son commerce maritime, et/ou à une participation directe plus importante des Provençaux dans sa navigation ? Ces facteurs interrogent la question des retombées de l’existence de ce grand port méditerranéen pour le Royaume. "}),(0,dc.jsxs)("p",{children:[(0,dc.jsx)(t,{id:"part-des-etrangers-dans-navigation"})," "]}),(0,dc.jsx)("p",{children:"Les navires étrangers sont présents de manière significative dans l’ensemble des premiers ports français (représentés ici par importance du tonnage total). Certes, les données de Marseille ne sont pas comparables avec celles des autres ports, car elles prennent en compte la seule source des déclarations des capitaines à l’arrivée (3290 entrées, sur un total connu de 4557 congés délivrés), alors que pour les autres ports, il s’agit des sorties; aussi et surtout, les tonnages marseillais sont issus d’estimations à partir du type de navires, alors que pour les autres ports, ils sont connus grâce aux registres des congés. Les ordres de grandeur sont toutefois vraisemblables: le pourcentage des congés étrangers délivrés à Marseille, connu grâce aux comptes rendus de l’ensemble des congés délivrés, est de 29,4% (1341 congés sur 4557), soit sensiblement le même pourcentage que l’on trouve via l’estimation des tonnages. "}),(0,dc.jsx)("p",{children:"Ces données comprennent toutes les destinations (ou, pour Marseille, les origines), y compris celles réservées par la législation aux transporteurs nationaux (cabotage, commerce colonial) et celles où les droits sur les étrangers deviennent de facto prohibitifs (Levant, pêche hauturière). En général, dans la France d’Ancien Régime, la navigation sur laquelle ce type de contraintes ne pèse pas - pour l’essentiel, les trafics internationaux avec l’Europe-, est largement tributaire des services de transport des flottes étrangères. Or, nous constatons que les navires français assurent à Marseille une partie des trafics bien plus importante que dans d’autres grands ports éloignés des frontières, comme Bordeaux ou Le Havre, où la moitié des tonnages est étrangère. "}),(0,dc.jsxs)("p",{children:[(0,dc.jsx)(t,{id:"part-des-francais-dans-provenance"})," "]}),(0,dc.jsx)("p",{children:"Cette caractéristique marseillaise se cumule avec une autre spécificité significative. Le port phocéen attire un nombre de pavillons étrangers différents plus élevé que partout ailleurs (20 nationalités en 1787). Le graphique permet de voir, pour les principaux marchés, la part de la navigation effectuée par les Français et le tonnage total estimé. Cette part demeure importante y compris sur des marchés extérieurs qui sont partout ailleurs dominés par les transporteurs étrangers. "}),(0,dc.jsx)("p",{children:"En se limitant à l’analyse des années de paix dont nous avons collecté les données représentées ici, on constate que les navires français gèrent une partie écrasante (plus de 90%) du trafic maritime entre Marseille et les autres ports de France - commerce certes réservé aux nationaux -, tout comme avec l’Empire ottoman, marché privilégié du port phocéen. Sous fond d’une importante croissance des volumes concernés par ces deux secteurs protégés (partie inférieure du graphique, qui indique les tonnages cumulés), la part du pavillon français ne change pas de manière significative au fil du temps: les armateurs français savent donc faire face à la hausse des besoins de services de transport. "}),(0,dc.jsx)("p",{children:"Pour ce qui est des liaisons avec les ports de la péninsule italienne et de l’Espagne, marchés primordiaux pour Marseille, les navires français réussissent à assurer un peu moins de la moitié des trajets environ, ce qui est remarquable, si on considère par exemple que les liaisons entre Bordeaux et les villes hanséatiques, essentielles à la prospérité bordelaise, sont presque exclusivement assurée par des navires nordiques (hollandais, hanséatiques, scandinaves pour l’essentiel). Si les Français perdent de parts sur les marchés ibériques et stagnent, ils parviennent à accroître le tonnage total, et à conserver leurs positions dans la péninsule italienne."}),(0,dc.jsx)("p",{children:'La navigation depuis les pays "Nordiques" (ici, nous avons mis en évidence les départs depuis des ports britanniques et néerlandais) est minime en valeur absolue, et elle est largement gérée par les étrangers: la présence des Français en provenance des ports sous souveraineté britannique est due aux navires qui reviennent de la pêche sédentaire à Terre-Neuve. Le commerce avec les Provinces-Unies - comme du reste avec toute l’Europe du Nord et la Baltique - échappe entièrement aux armateurs français. '}),(0,dc.jsx)("h2",{id:"h.agycgsyuh378",children:"2.C La coexistence de styles de navigation différents "}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"styles-navigation"})}),(0,dc.jsxs)("p",{children:["Il est possible que le principal élément de robustesse de Marseille vienne de la diversification de ses trafics maritimes, c’est-à-dire la coexistence de logiques de navigation différentes. Pour approfondir cet aspect, nous avons voulu interroger la navigation marseillaise de long cours à partir de ses caractéristiques, en se focalisant sur trois différents marchés : celui de la Méditerranée occidentale",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Nous y incluons aussi les voyages en provenance des ports italiens et autrichiens en Adriatique, ainsi que ceux de la façade atlantique de l’Espagne du du Maroc.",children:"?"}),", celui de l’Empire ottoman",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Y compris donc les régences d’Alger, Tunis, et Tripoli en Afrique du Nord et le Moyen-Orient, ainsi que les ports russes sur la mer Noire. Le fond de carte présente des erreurs, les frontières des régences étant celles de Etats contemporains, et le Moyen Orient ne s’affiche pas en vert.",children:"?"})," et celui du Ponant",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Tous les ports européens situés en Atlantique, mer du Nord et mer Baltique (Espagne exclue).",children:"?"}),". Ces marchés correspondent à des logiques de navigation différentes, que la visualisation ci-contre permet d’apprécier pour les années de paix dont nous avons collecté les données (1749, 1769, 1787, 1789). "]}),(0,dc.jsx)("p",{children:'Nous avons représenté le nombre de voyages total pour ces quatre années qui nous sont livrés par les registres des dépositions des capitaines auprès du Bureau de la Santé de Marseille. Le graphique permet d’apprécier la distribution des tonnages, estimés à partir du type d’embarcation, et le nombre d’étapes intermédiaires entre le port de départ et l’arrivée à Marseille. Il s’agit de mettre en avant la pluralité de manières de gérer le transport maritime, et de suggérer que celle-ci a pu contribuer à accroître la capacité de résilience du port phocéen: la variété d’embarcations, la large palette de styles de navigation, comprenant des escales parfois nombreux, que ce soit d’ordre technique ou pour "aller à la cueillette", c’est-à-dire, charger ou décharger une partie de la cargaison, ont pu finalement permettre à Marseille de pouvoir jouer sur plusieurs plans et plusieurs marchés, sans se rendre dépendante d’un seul marché ou d’une seule modalité d’effectuer le transport. Cette flexibilité pourrait expliquer aussi sa meilleure tenue en temps de guerre.'}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{categorie:"méditerranée",id:"styles-navigation"})}),(0,dc.jsx)("p",{children:"La navigation depuis les ports de la Méditerranée occidentale - notion étendue ici à l’Adriatique européenne - comprend un très grand nombre de données (plus de 7 600 arrivées à Marseille sur les quatre années, et encore une bonne partie des trafics de proximité entre la Toscane et la Catalogne nous échappe, car ils étaient inscrits sur les cahiers du petit cabotage). Cette masse de voyages, pour l’essentiel en provenance d’une multitude de ports situés entre le détroit de Gibraltar et le royaume de Naples, se caractérise par la prépondérance de bâtiments de faible portée (5-50 tonneaux) comme les bateaux, les chasse-marées, les felouques, les goélettes et surtout les tartanes qui naviguent principalement en droiture (c.à.d. sans escales), ou en effectuant une seule escale. Cette navigation ne requiert pas de compétences nautiques particulières, et n’a pas beaucoup attiré l’attention des historien.nes. Elle se révèle pourtant essentielle pour le ravitaillement quotidien et le commerce de redistribution du grand port de Marseille."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"styles-navigation",tonnage:"150"})}),(0,dc.jsx)("p",{children:"Les grands navires sont rares sur ces routes de proximité. Si on met en avant par exemple la navigation des brigantins, des navires ou des senaus, c.à.d. des bâtiments estimés à 150 tonneaux mis en évidence ci-contre, la géographie commerciale change radicalement, et l’Europe méditerranéenne disparaît au profit du commerce avec l’Empire ottoman et l’Europe atlantique."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{categorie:"empire",id:"styles-navigation"})}),(0,dc.jsx)("p",{children:"Le tonnage et le nombre d’escales intermédiaires sont bien plus importants depuis les grands nœuds du commerce français au Levant, qui emploient le plus souvent des navires de tonnage moyen (50-150 tonneaux) comme l’allège, le brick, le chebec, la pinque ou la queche. Parmi les « Échelles » ottomanes, Smyrne est le principal protagoniste du trafic français, et dépasse largement les départs depuis les autres grands ports de l’Empire (Salonique, Alexandrie d’Égypte et Constantinople). Alexandrette, Coron, Enos et La Canée ne viennent qu’au deuxième rang. En réalité, la navigation française fréquente de dizaines de ports au Levant tant en droiture que, surtout, dans le cadre de la caravane maritime (voir partie 3.C). S’ils n’apparaissent pas sur la carte, qui ne représente que le port de départ du voyage, on lit leur présence en filigrane par le nombre d’escales intermédiaires avant l’arrivée du navire à Marseille - le plus souvent, entre un et quatre, sans que la taille du navire n’affecte cette variable. "}),(0,dc.jsx)("p",{children:'Les ports du Maghreb (Tunis, Bonne, La Cale, Alger) rivalisent avec les principales Échelles ottomanes par le nombre des expéditions. Au cours du XVIIIe siècle ils se révèlent de plus en plus stratégiques pour le ravitaillement en céréales de Marseille et de son arrière-pays. Les arrivées en droiture, sans escales intermédiaires, depuis la catégorie agrégée "Empire ottoman" sont le plus souvent de leur fait.'}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{categorie:"ponant",id:"styles-navigation"})}),(0,dc.jsx)("p",{children:"Les ports européens situés au-delà du détroit de Gibraltar expédient un nombre de navires à Marseille comparables à ceux en provenance de l’Empire ottoman et de la mer Noire (1160 voyages contre 1230). Les navires de portée moyenne et forte (150-300 tonneaux) dominent. Il s’agit d’une navigation de long cours, où les navires se dirigent à Marseille, principal emporium méditerranéen, pour décharger leur cargaison et trouver un fret ou une cargaison de retour. L’écrasante majorité des bâtiments navigue en réalité en droiture, l’escale indiquée sur le graphique n’étant le plus souvent que le passage par le détroit de Gibraltar, dont les sources relatent la date. Les lieux de départ sont multiples, sans que l’importance de Londres et Amsterdam se dégage de manière écrasante. "}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"styles-navigation",steps:"3"})}),(0,dc.jsx)("p",{children:"La relation entre le nombre d’étapes, révélateur d’une logique de navigation qui ne vise pas à maximiser la durée du voyage, et la géographie commerciale mériterait d’être affinée, mais la visualisation ci-contre, qui met en évidence les voyages avec 3 étapes, montre qu’elle est pour l’essentiel le fait des navigations avec l’Empire ottoman."}),(0,dc.jsx)("p",{children:"Ce qui émerge cette analyse de ces trois grandes aires commerciales-maritimes, c’est la représentation de la coexistence (et la complémentarité?) de différents styles de navigation qui desservent un grand port européen à la fin de l’époque moderne. Marseille au XVIIIe siècle peut jouer sur plusieurs réseaux de navigation ayant des caractéristiques et fonctions différentes. Cabotage, caravane, long cours, navigation commerciale en droiture : chacun a sa part dans le fonctionnement et la résilience du port phocéen au XVIIIe siècle. "})]})}function eN(e){const t=Object.assign({code:"code"},e.components);return(0,dc.jsxs)("div",{id:"part-2",children:[(0,dc.jsx)("p",{children:"Diversification dans la variété des produits, dans les partenaires (et dans le croisement produits x partenaires : matrice), dans les acteurs de la navigation."}),(0,dc.jsx)("h2",{id:"h.ipbpmiriq4tr",children:"2.A Diversité des produits du commerce de Marseille"}),(0,dc.jsx)("p",{children:"Est-ce que Marseille est, en termes de produits, plus diversifié que les autres ports français ? + évolution dans le temps"}),(0,dc.jsx)("p",{children:"Notes sur la réponse à cette question:"}),(0,dc.jsx)("p",{children:"Pour certains bureaux et directions et bureaux, on a calculé l'indice Herfindhal en tout année dont les données sur les produits exportés étaient enregistrées en toflit18_all_flows."}),(0,dc.jsx)("p",{children:"Les six directions principales sélectionnées étaient : "}),(0,dc.jsxs)("ol",{children:[(0,dc.jsx)("li",{children:"Bordeaux"}),(0,dc.jsx)("li",{children:"Marseille"}),(0,dc.jsx)("li",{children:"Rouen"}),(0,dc.jsx)("li",{children:"Nantes"}),(0,dc.jsx)("li",{children:"La Rochelle"}),(0,dc.jsx)("li",{children:"Bayonne"})]}),(0,dc.jsx)("p",{children:"Les huit bureaux de ferme sélectionnées pour l'année 1789 étaient : "}),(0,dc.jsxs)("ol",{children:[(0,dc.jsx)("li",{children:"Bordeaux"}),(0,dc.jsx)("li",{children:"Marseille"}),(0,dc.jsx)("li",{children:"Rouen"}),(0,dc.jsx)("li",{children:"Nantes"}),(0,dc.jsx)("li",{children:"La Rochelle"}),(0,dc.jsx)("li",{children:"Bayonne"}),(0,dc.jsx)("li",{children:"Saint-Malo"}),(0,dc.jsx)("li",{children:"Le Havre"})]}),(0,dc.jsx)("p",{children:"Puisqu'il y a plus de données pour les directions que pour les bureaux, on a bouclé sur toute année enregistrée et on a calculé l'indice Herfindhal."}),(0,dc.jsx)("p",{children:"La calculation étaient fait selon les étapes suivantes : "}),(0,dc.jsxs)("ol",{children:[(0,dc.jsx)("li",{children:"calculer la somme de la valeur de tout produit exporté par la direction / le bureau ciblé → all_product_value"}),(0,dc.jsx)("li",{children:"agréger les exports par type et sommé leur valeur agrégée"}),(0,dc.jsx)("li",{children:"les agrégations étaient fait sur la colonne 'product_revolutionempire'"}),(0,dc.jsx)("li",{children:"GROUP BY product_revolutionempire → product_revolutionempire, SUM(value) AS sum_value"}),(0,dc.jsx)("li",{children:"calculer le ratio entre la totale en valeur d'un produit et la totale du bureau / direction et le multiplier par lui-même"}),(0,dc.jsx)("li",{children:"(sum_value/all_product_value)2 → carre_part_marche"}),(0,dc.jsx)("li",{children:"calculer la somme du ratio"})]}),(0,dc.jsx)("p",{children:"Lié à l’intersection de plusieurs espaces. "}),(0,dc.jsx)("h2",{id:"h.8lvwm85ep7f9",children:"2.B Une diversification des marchés plus forte qu’ailleurs ?"}),(0,dc.jsx)("p",{children:"Pour les catégories et/ou les produits les plus importants en valeur : Une diversification des marchés plus forte qu’ailleurs ? (voir si Marseille est moins dépendante que d’autres ports d’un seul marché pour ses produits principaux) + évolution dans le temps. Travail sur la matrice."}),(0,dc.jsxs)("p",{children:["analyse préliminaire pour blé et huile à Marseille (construit à partir des données dispos ",(0,dc.jsx)("a",{className:"c20",href:"https://github.com/medialab/portic-storymaps-2023/blob/main/datascripts/module_2B/partners.csv",rel:"noopener noreferrer",target:"_blank",children:"ici"})," en utilisant ‘python compute_data.py’ dans le dossier ",(0,dc.jsx)("a",{className:"c20",href:"https://github.com/medialab/portic-storymaps-2023/tree/main/datascripts/module_2B",rel:"noopener noreferrer",target:"_blank",children:"datascripts/module_2B"}),")"]}),(0,dc.jsx)("p",{children:"On crée un indice de variabilité des partenaires d’un port pour un type de produit (en import ou en export) comme la moyenne des variances des ratios d’un partenaire sur une année par rapport à l’ensemble des partenaires pour cette même année, on l’applique aux 10 principaux produits en import et 10 principaux en export pour les principaux grands ports (Marseille, Bordeaux, Nantes, Rouen, La Rochelle, Bayonne)."}),(0,dc.jsxs)("p",{children:["On produit les données avec ",(0,dc.jsx)(t.code,{children:"python compare_ports.py"})," dans le dossier ",(0,dc.jsx)("a",{className:"c20",href:"https://github.com/medialab/portic-storymaps-2023/tree/main/datascripts/module_2B",rel:"noopener noreferrer",target:"_blank",children:"datascripts/module_2B"})," ce qui produit les données ",(0,dc.jsx)("a",{className:"c20",href:"https://github.com/medialab/portic-storymaps-2023/blob/main/datascripts/module_2B/variances_ports_produits.csv",rel:"noopener noreferrer",target:"_blank",children:"suivantes"})," visualisées sous la forme de boxplot ou de violin plot ci-dessous (résultats contradictoires avec l’objectif initial)"]}),(0,dc.jsx)("p",{children:"Titre: Top 5 produits (imports et exports)"}),(0,dc.jsx)("h2",{id:"h.5xt17flpsq8c",children:"2.C . Diversité des acteurs de la navigation de Marseille "}),(0,dc.jsx)("p",{children:"Marseille attire plus de pavillons étrangers que tout autre port français. "}),(0,dc.jsx)("p",{children:"Titre: Nombre de pavillons étrangers différents en 1787 dans les 20 principaux ports français"}),(0,dc.jsx)("p",{children:"La navigation entre la France et les pays étrangers est largement tributaire des services de transport des flottes étrangères. Or, la présence française est plus élevée sur les marchés méditerranéens. "}),(0,dc.jsx)("p",{children:"Titre: Navigation de la France avec les pays étrangers en 1787. Nombre total des navires et pavillons"}),(0,dc.jsx)("p",{children:"Les étrangers assurent un trafic important, qui vient conforter la position de force du port phocéen, et ce d’autant plus que les données de Marseille prennent en compte la seule source des déclarations des capitaines (3290 entrées, sur un total connu de 4XXX congés), mise ici en comparaison avec le tonnage sortis des autres ports, connu grâce aux congés délivrés. "}),(0,dc.jsx)("p",{children:"Titre: Tonnage étranger dans les 20 principaux ports français en 1787 (en tonneaux)"}),(0,dc.jsx)("p",{children:"NB: congés pour tous les ports sauf Marseille = entrées (petit cabotage exclu)"}),(0,dc.jsx)("p",{children:"Les étrangers sont présents de manière significative dans l’ensemble des premiers ports français (par importance du tonnage total), sans que la position de Marseille se détache des autres."}),(0,dc.jsx)("p",{children:"Titre: Tonnage étranger versus tonnage total des 10 premiers ports français en 1787 (en tonneaux). NB: congés pour tous les ports sauf Marseille = entrées (petit cabotage exclu)"}),(0,dc.jsx)("p",{children:"Titre: Part du tonnage étranger dans les dix premiers ports de France en 1787 (en tonneaux)- Marseille = entrées; autres = congés"}),(0,dc.jsx)("p",{children:"Marseille est donc un port attractif pour le commerce et les frets. Il s’agit de voir la diversité et la part des différents acteurs sur les différents marchés en tant que facteur de force du commerce marseillais sur le long terme (car pas dépendante d’un seul pavillon) mais aussi de souligner (si c’est le cas) que la part de la navigation gérée par les Provençaux est plus importante qu’ailleurs (= sont plus autonomes)"}),(0,dc.jsx)("p",{children:"Parmi les principaux partenaires de Marseille (en tonnage), les navires français gèrent la plupart du trafic maritime entre Marseille et les autres ports de France, tout comme celui avec l’Empire ottoman, marché privilégié du port phocéen. La part du pavillon français ne change pas au fil du temps. Pour ce qui est des liaisons avec les ports de la péninsule italienne, marchés primordiaux pour Marseille, ce sont les étrangers à gérer la plupart du trafic. Depuis l’Espagne, la part des Français diminue au cours du temps."}),(0,dc.jsx)("p",{children:"Expliquer les données avec Grande-Bretagne"}),(0,dc.jsx)("p",{children:"Titre: Part de la navigation avec les principaux partenaires de Marseille (tonnage) assurée par les Français (années de paix)"}),(0,dc.jsx)("p",{children:"Titre: Tonnage assuré par les Français dans la navigation avec les principaux partenaires de Marseille (années de paix)"}),(0,dc.jsx)("p",{children:"Visus ex 4A"}),(0,dc.jsx)("p",{children:"Titre: Vitesse moyenne en miles par jour pour chaque décennie"}),(0,dc.jsx)("p",{children:"Titre: Vitesse moyenne pour chaque pavillon et chaque décennie"}),(0,dc.jsx)("p",{children:"Titre: Vitesse moyenne pour chaque pavillon et chaque décennie"}),(0,dc.jsx)("p",{children:"Titre: Nombre de trajet par pavillon et par types de bateau"}),(0,dc.jsx)("p",{children:"Titre: Durée moyenne par pavillon et par types de bateau "}),(0,dc.jsx)("p",{children:"Titre: Évolution des types de bateau en pourcentage, pour chaque décennie et chaque pavillon"}),(0,dc.jsx)("p",{children:"Possibilité de faire la même chose pour Marseille en 1787 (avec seulement les entrées) - > carte avec import (avec possibilité de sélectionner) et de comparer "}),(0,dc.jsxs)("ol",{children:[(0,dc.jsx)("li",{children:"Est-ce que les étrangers assurent le transport depuis les marchés les plus importants (hors colonies) ? projeter la part de la navigation française versus étrangère pour années Navigo (quels pavillons transportent les cargaisons de plus forte valeur) [ex: carte avec valeurs Toflit par pays import/export qui avance dans le temps] "}),(0,dc.jsx)("li",{children:'NB: étranger n’est pas synonyme de "Nordique"'})]}),(0,dc.jsx)("p",{children:"Hypothèse Silvia: diversifications entre marchés atlantiques et marchés méditerranéens en termes de pavillons (liées aussi à la taille des navires) qui permet aux ports avec des infrastructures importantes (lazarets, consulats etc.) d’être desservis par tout le monde, avec en parallèle des routes interstitielles réservés à d’autres acteurs (provençaux, méditerranéens) qui demeurent importantes -> Une géographie des acteurs plus ‘granulaire’ que chez Carrière qui ne croise pas pavillons et routes (hypothèse: les Nordiques ne sont présents que sur certains circuits / ports structurés; les Provençaux/Languedociens investissent la péninsule italienne, le Levant, la Barbarie, peut-être l’Espagne de manière significative)"})]})}function tN(e){const{Caller:t}=e.components||{};return t||function(){throw new Error("Expected component `Caller` to be defined: you likely forgot to import, pass, or provide it.")}(),(0,dc.jsxs)("div",{id:"part-3",children:[(0,dc.jsx)("p",{children:"Le commerce français est très affecté par les guerres maritime tout au long du XVIIIe siècle : Guerre de Succession d’Autriche (1744-1748), Guerre de Sept Ans (1756-1763 en Europe), Guerre d’Indépendance américaine (1778-1783), Guerres de la Révolution et de l’Empire (1793-1815, avec quelques mois de paix en 1801-1802 et 1814). La Méditerranée n’est pas neutralisée, loin de là : elle aussi est un champ de bataille. Cependant, elle est moins souvent sous l’emprise de la puissance navale britannique. Peut-être est-ce là un avantage pour Marseille, qui aurait moins souffert de la pression guerrière que les ports français de l’Atlantique ?"}),(0,dc.jsx)("h2",{id:"h.92qf38d5u0ri",children:"3.A Impact de la guerre sur le commerce de Marseille"}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{directions:"Marseille",id:"impact-guerre-sur-commerce-et-navigation",series:"total"})}),(0,dc.jsx)("p",{children:"Pour vérifier cela, nous utilisons une statistique élaborée dans une recherche en cours Guillaume Daudin et Elisa Tirindelli. Elle consiste à calculer l’écart moyen entre le commerce observé en temps de guerre et le commerce tel qu’il aurait été s’il avait suivi sa tendance durant la période de paix précédant la guerre. Ainsi, sur la visualisation ci-contre, on peut lire que le commerce total de Marseille diminue de 40% en temps de guerre. La comparaison des droites rouges (l’évolution hypothétique du commerce durant chaque guerre si la paix avait continué) et les lignes noires (le commerce effectivement observé) montre aussi que cette diminution est d’ampleur comparable pour les trois guerres maritimes."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{directions:"Marseille",id:"impact-guerre-sur-commerce-et-navigation","navigation-metric":"carrière",series:"navigation"})}),(0,dc.jsx)("p",{children:"La chute de la navigation est moins forte: 6% en moyenne si on n’utilise les données annuelles de Carrière."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{directions:"Marseille",id:"impact-guerre-sur-commerce-et-navigation","navigation-metric":"entrées",series:"navigation"})}),(0,dc.jsx)("p",{children:"Les données de Navigocorpus pour Marseille concernent les entrées des dépositions des capitaines auprès du bureau de la Santé, mais ne sont disponibles que tous les dix ans (1749-1799). Elles indiquent un effet plus important de la guerre que les données collectées par Charles Carrière à partir de la même source (-23%). Dans tous les cas, ce déclin est moins important que celui visible à partir des données de la valeur du commerce."}),(0,dc.jsx)("p",{children:"La différence s’explique en partie à cause d’une couverture temporelle différente. La série de données de Charles Carrière comprend la période de la guerre de Succession d’Autriche qui a un impact faible mais pas celle de la guerre d’Indépendance américaine ni de la décennie révolutionnaire, qui ont un impact important d'après les données sur la navigation collectées par Navigocorpus."}),(0,dc.jsx)("p",{children:"En tout état de cause, il n’est pas surprenant que la navigation soit moins affectée par la guerre que le commerce, car une partie importante se fait à courte distance ou sur des navires de petite taille. La valeur des marchandises transportées par ces deux flux, moins vulnérables aux désordres apportés par la guerre, est relativement faible."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{directions:"Marseille",id:"impact-guerre-sur-commerce-et-navigation","navigation-metric":"mileage",series:"navigation"})}),(0,dc.jsx)("p",{children:"Le nombre d’entrées à Marseille rend imparfaitement compte de l’impact des conflits sur la navigation marseillaise, qui apparaît davantage en prenant en compte les tonnages et le rétrécissement des aires de navigation, mesuré ici en milles maritimes agrégées. Ainsi, lorsqu’on observe ces deux variables (graphique ci-contre), les pertes liées à la guerre sont beaucoup plus importantes (44% et 66% respectivement): la guerre n’est donc pas anodine, même pour la navigation."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{directions:"Marseille, Bordeaux, Rouen, Nantes, La Rochelle, Bayonne",id:"impact-guerre-sur-commerce-et-navigation"})}),(0,dc.jsx)("p",{children:"Pour savoir si ces réactions à la guerre sont malgré tout un facteur potentiel de la résilience marseillaise, il faut comparer le comportement du commerce de Marseille à celui des autres ports français. Comme le montre le graphique ci-contre, Nantes est plus vulnérable que Marseille (-55%). Mais c’est le seul port à l’être : la réduction du commerce de Bordeaux, Rouen (y compris le Havre) et La Rochelle varie entre 15 et 25%. Bayonne bénéficie même des guerres (pour un commerce, il est vrai, plus faible). La comparaison n’est pas parfaite, car les mêmes années ne sont pas disponibles pour chaque port. Mais en tous les cas, il n’y a pas de signe évident d’une particulière résilience de Marseille à la guerre."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"impact-guerre-sur-commerce-et-navigation","navigation-metric":"entrées",series:"total, imports, exports"})}),(0,dc.jsx)("p",{children:"Le graphique ci-contre élargit l’analyse en considérant les exportations et les importations, il confirme les résultats présentés ci-dessus. De même si on étudie le problème en regardant de manière plus spécifique le commerce colonial, notre constat initial en sort renforcé: il n’existe pas d’éléments statistiques probants qui permettent d’affirmer que le commerce maritime de Marseille est moins affecté par les guerres que celui des autres ports français."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"impact-guerre-sur-commerce-et-navigation","navigation-metric":"entrées",series:"total_no_colonial_trade, imports_no_colonial_trade, exports_no_colonial_trade"})}),(0,dc.jsx)("p",{children:"Même constatation si l’on exclut le commerce colonial, sinon que dans ce cas, la vulnérabilité de La Rochelle et de Nantes sont comparables à celles de Marseille."}),(0,dc.jsx)("h2",{id:"h.wwo855isgynu",children:"3.B Qui assure la navigation en temps de guerre ?"}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"guerre-et-navigation"})}),(0,dc.jsx)("p",{children:"Une approche différente, mais complémentaire, pour comprendre l’impact des conflits sur le commerce consiste à étudier les changements affectant les acteurs du transport maritime. Plus précisément, il s’agit de questionner la permanence de la navigation française - et donc l’éventuelle perte des marchés du transport maritime - et le jeu des pavillons neutres. La guerre affecte profondément les logiques des trafics maritimes et les vitesses de navigation (que ce soit en raison de l’introduction des convois depuis le Levant, ou d’une navigation plus proche des côtes, avec des escales plus fréquentes, pour échapper aux corsaires ennemis). Faute de données permettant une comparaison avec les autres ports français, cette étude a été menée sur le seul cas marseillais. "}),(0,dc.jsx)("p",{children:"L’analyse s’est concentrée sur le changement des pavillons qui desservent Marseille dans une année de guerre étudiée (1759, 1779, 1799) par rapport à l’année de paix dix ans plus tôt. Les pavillons ont été répartis en cinq catégories, représentant le statut diplomatique envers la France du pays respectif dans l’année de guerre (allié, ennemi, neutre) et, pour le pavillon français, en distinguant ceux de la façade méditerranéenne et ceux du Ponant (façade atlantique et Manche). Nous avons introduit cette distinction car les navires des ports français au-delà du détroit de Gibraltar doivent prendre des risques bien plus importants lors de leur trajet jusqu’à Marseille, en raison de la présence britannique sur mer dans la Manche et en Atlantique."}),(0,dc.jsx)("p",{children:"Les pavillons qui desservent Marseille présentent une dynamique similaire tant pendant la guerre des Sept Ans que pendant celle de l’Indépendance américaine. Les grands gagnants lors de la guerre de Sept Ans et de celle d'Indépendance américaine sont les pavillons neutres, qui passent de 20-25 % du trafic à 50-60%. La part de la navigation française du Ponant diminue fortement, alors que celle du Levant se maintient nettement mieux. Sans grande surprise, la navigation des pavillons ennemis de la France disparaît pendant les deux conflits, la seule différence entre les deux guerres étant que leur part en 1749 (19 %) - l’année de paix précédente qui sert de référence - est considérablement supérieure à leur part en 1769 (5 %). "}),(0,dc.jsx)("p",{children:"La part de la navigation assurée par les alliés de la France dans la navigation marseillaise demeure négligeable aussi bien pendant la guerre de Sept Ans que pendant celle d’Indépendance américaine. Cela change fortement en 1799, lorsque la France révolutionnaire a su, par ses conquêtes militaires, mettre sous son contrôle aussi bien les Provinces-Unies qu’une bonne partie de la péninsule italienne pendant plusieurs mois de l’année. La position de force de la France sur le continent en 1799 explique en grande partie l’effondrement du rôle de la navigation neutre à Marseille en 1799 par rapport aux conflits précédents. Mais ce n’est pas pour autant un signe d’une meilleure position de la France sur mer. Exprimée en pourcentage, cette répartition des pavillons masque un changement radical: le nombre de gros bâtiments s’effondre: brigantins, polacres, senaus et navires - soit de types de navires de 150 tonneaux ou plus en moyenne (Sofia, 2024) - passent de plus de 800 en 1789 à moins de 200 en 1799, contre une diminution d’un tiers seulement entre 1769 et 1779. Ce n’est donc plus que le cabotage par de petites unités qui se maintient car elles échappent plus facilement à la vigilance britannique sur mer."}),(0,dc.jsx)("p",{children:"La compréhension des effets de compensation entre pavillons et des changements de fond dans les marchés et la navigation requiert de prendre en compte simultanément les différentes variables. Nous allons le faire pour le commerce du Levant, dont on a déjà souligné l’importance centrale pour Marseille. Il nous a semblé plus intéressant de suivre ce cas, plutôt que celui du commerce colonial, dont l’importance est moindre pour Marseille. "}),(0,dc.jsx)("h2",{id:"h.8uq6vxnsuzpw",children:"3.C Zoom sur le Levant"}),(0,dc.jsx)("p",{children:"Comme nous avons vu plus haut, le Levant représente un ensemble important de ports de départ pour les arrivées à Marseille :"}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"levant-navigation"})}),(0,dc.jsxs)("p",{children:["La présence française est en effet capillaire, ce dont témoigne aussi l’effort majeur, par la monarchie française, d’étoffer le réseau consulaire et le nombre de vice-consuls afin d’assister les capitaines. Outre le commerce direct, les Provençaux se sont spécialisés aussi dans le commerce dit de caravane (Panzac 2004; Buti 2010)",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Le terme de caravane désigne des contrats de transport individuels, enregistrés auprès des chancelleries des consulats européens, entre un marchand généralement turc ou arabe, un capitaine chrétien et un intermédiaire souvent issu des minorités religieuses du monde ottoman (Grecs, Arméniens ou Juifs), en qui les deux parties ont confiance dans la mesure où il n’appartient pas à la communauté de l’autre contractant. Les campagnes, d’une durée théorique de deux ans maximum d’après le législateur français, sont assez fréquemment plus longues.",children:"?"}),". Les capitaines partent depuis la France vers le Levant, et associent au fil de leurs escales commerce et services de transport, naviguant donc de port et port au gré des contrats d'affrètement. Les Provençaux ne sont pas les seuls à s’adonner à ces trafics profitables, car les Vénitiens et Ragusains sont aussi actifs, et leur ravissent des parts de marché quand les Français sont en guerre. Ces trois groupes d’acteurs méditerranéens assurent 95% de la navigation sous pavillon européen à Alexandrie dans les années 1785-1789. "]}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"effets-guerre-sur-commerce-levant"})}),(0,dc.jsx)("p",{children:"Au regard du graphique ci-contre, on peut constater que l’impact des guerres avec l'Angleterre est significatif en ce qui concerne le commerce avec le Levant. Cet impact est visible aussi bien à partir des données de la balance du commerce que de celles de la navigation. En effet, il est le commerce le plus affecté après celui des colonies françaises, alors que ses conséquences sur le commerce avec les pays méditerranéens plus proches (l’Italie et l’Espagne) sont plus bénins. Seule la guerre d'indépendance américaine fait un peu exception. Comme le rapport entre les flottes de guerre françaises et ses alliés contre celle de l’Angleterre est bien plus favorable que pendant les trois autres guerres et que le principal théâtre d’opération se situe dans l’Atlantique Nord, les risques de pertes pour les marchands à destination du Levant étaient beaucoup moins grands. L’utilisation des données de navigation permet d'affiner ce constat: la perte de commerce vers le Levant est moins grande que ne le laisse imaginer les flux bilatéraux car une partie de celui-ci est pris en charge par les navires neutres, italiens en particulier. C’est ce qui explique que, pendant les guerres de succession d’Autriche et de Sept Ans, le commerce vers l’Espagne et le Portugal connaisse une certaine croissance: ces relais- l’Italie en particulier - sont en fait des étapes depuis ou vers des destinations plus éloignées et trop risquées en temps de guerre."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"levant-navigation-guerre"})}),(0,dc.jsx)("p",{children:'Pour ce qui est de la navigation, on constate que les Provençaux (les "Français du Levant" sont essentiellement des Provençaux, la participation des Languedociens étant limitée) parviennent à garder le contrôle sur la navigation en provenance du Levant tant pendant la guerre de Sept Ans que, encore plus, pendant celle d’Indépendance américaine (où quatre convois par an sont organisés pour escorter les navires français depuis Smyrne et Malte, et quatre autres depuis les régences barbaresques). En revanche, ils sont définitivement évincés des activités de tramping lors des guerres révolutionnaires: en 1799, seulement un navire sur quatre en provenance du Levant qui parvient à Marseille navigue sous pavillon français. Ces changements, exprimés en pourcentage de tonnages agrégés, nécessitent d’être éclairés par les chiffres absolus: le nombre de départs depuis l’Empire ottoman (régences barbaresques comprises) vers Marseille se contracte aussi bien pendant la guerre de Sept Ans que lors de celle d’Indépendance américaine, et se situe autour de 45% du nombre des entrées dix ans plus tôt. En revanche, en 1799 ce commerce disparaît presque entièrement, car on passe de 192 arrivées de l’Empire ottoman en 1789 à 8 seulement en 1799 ! '}),(0,dc.jsx)("p",{children:"Dans la décennie révolutionnaire, la France perd en effet définitivement ses positions de force au Levant, et abandonne également le commerce de caravane qui permettait à l’armement français des profits substantiels (Panzac, 2004). Lorsque la paix revient, en 1815, le contexte méditerranéen a profondément changé: la fin du corso, activité prédatrice qui affecte lourdement au XVIIIe siècle la sécurité des navires ottomans et des pays de chrétienté qui n’avaient pas de traités de paix avec les régences barbaresques, permet désormais à tout et chacun de naviguer librement en Méditerranée, alors que la suppression des privilèges qui favorisent le commerce de Marseille avec l’Empire ottoman (droit de 20%) ouvre la voie à la concurrence. Un demi siècle plus tard, quand la navigation à vapeur et le chemin de fer auront changé en profondeur les modalités des échanges en Méditerranée et en Europe, Marseille trouvera de nouvelles possibilités de s’insérer dans ce monde qui change."})]})}function nN(e){return(0,dc.jsxs)("div",{id:"part-3",children:[(0,dc.jsx)("p",{children:"on pose la question de l’impact et on montre que finalement ce n’est pas un facteur essentiel de la résilience de Marseille"}),(0,dc.jsx)("h3",{id:"h.92qf38d5u0ri",children:"3.A Impact de la guerre sur le commerce de Marseille"}),(0,dc.jsx)("p",{children:"Un impact de la guerre moins important qu’ailleurs? Voir si les guerres ont toutes un moindre impact (quelques doutes pour celle de Sept Ans)"}),(0,dc.jsxs)("ol",{children:[(0,dc.jsx)("li",{children:"Regarder les évolutions du commerce de Marseille pendant les guerres 1740-1748, 1756-1763 et 1776-1783 comparé au commerce français total."}),(0,dc.jsx)("li",{children:"Quels marchés à Marseille sont les plus affectés par la guerre? Est-ce que certains marchés accroissent leur part ? "})]}),(0,dc.jsx)("p",{children:"On distingue trois périodes de guerre : "}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"1744-1748 : succession Autriche"}),(0,dc.jsx)("li",{children:"1756-1763: sept ans"}),(0,dc.jsx)("li",{children:"1776-1783: indépendance américaine"})]}),(0,dc.jsx)("p",{children:"Pour ces trois périodes on calcule une prédiction du commerce en appliquant une régression linéaire sur les données de commerce des années précédent la guerre."}),(0,dc.jsx)("p",{children:"On teste deux manières de considérer les périodes de paix pré-guerre: "}),(0,dc.jsxs)("ol",{children:[(0,dc.jsx)("li",{children:"avec mémoire: on considère toutes les périodes de paix précédentes"}),(0,dc.jsx)("li",{children:"sans mémoire: on ne considère que la dernière période de paix précédente"})]}),(0,dc.jsx)("p",{children:"Sur les représentations ci-dessous, les régressions en rouge sont celles calculées avec mémoire, en orange sans mémoire (sur la première période de guerre, les deux régressions sont identiques)."}),(0,dc.jsx)("p",{children:"On calcule ensuite un taux de perte en comparant les valeurs attendues par régression aux valeurs constatées dans les stats de commerce. Ce taux de perte est exprimé comme suit : (effectif - prédit) / prédit"}),(0,dc.jsx)("p",{children:"On agrège ensuite les taux de perte annuels en faisant une moyenne."}),(0,dc.jsx)("p",{children:"Ces taux sont indiqués dans les coins hauts gauche et droites des visualisations."}),(0,dc.jsx)("p",{children:"On calcule les mêmes indicateurs de perte sur les indicateurs de navigation:"}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"entrées suivant Carrière"}),(0,dc.jsx)("li",{children:"entrées suivant Navigo"}),(0,dc.jsx)("li",{children:"distances parcourues suivant Navigo"}),(0,dc.jsx)("li",{children:"tonnage suivant Navigo"})]}),(0,dc.jsx)("p",{children:"On observe une différence importante entre les taux de pertes des séries navigo comparées à Carrière. La série de donnée Carrière contient la période de la guerre de succession qui a un impact faible mais ne contient pas la période de la guere d’indépendance qui semble très impactante d’arès navigo. La série Carrière est donc globalement moins impactée. "}),(0,dc.jsx)("p",{children:"Les données navigo nous permettent de constater que si les entrées sont les moins influencées par les guerres, la taille et la distance parcourue par les navires subissent elles une diminution importante."}),(0,dc.jsxs)("p",{children:["Explication après exploration Toflit18 :",(0,dc.jsx)("a",{className:"c20",href:"http://toflit18.medialab.sciences-po.fr/#/exploration/indicators?lines=%5B%7B%22color%22%3A%22#504342%22%2C%22partnerClassification%22%3A%22partner_grouping%22%2C%22partner%22%3A%5B%7B%22id%22%3A%22Italie%7Epartner_grouping%22%2C%22name%22%3A%22Italie%22%7D%2C%7B%22id%22%3A%22Espagne%7Epartner_grouping%22%2C%22name%22%3A%22Espagne%22%7D%5D%2C%22region%22%3A%22Marseille%22%2C%22kind%22%3A%22import%22%2C%22sourceType%22%3A%22Best%20Guess%20customs%20region%20product%20x%20partner%22%7D%2C%7B%22color%22%3A%22#A563B7%22%2C%22partnerClassification%22%3A%22partner_grouping%22%2C%22partner%22%3A%5B%7B%22id%22%3A%22Levant_et_Barbarie%7Epartner_grouping%22%2C%22name%22%3A%22Levant%20et%20Barbarie%22%7D%5D%2C%22region%22%3A%22Marseille%22%2C%22kind%22%3A%22import%22%2C%22sourceType%22%3A%22Best%20Guess%20customs%20region%20product%20x%20partner%22%7D%2C%7B%22color%22%3A%22#85C85B%22%2C%22partnerClassification%22%3A%22partner_grouping%22%2C%22partner%22%3A%5B%7B%22id%22%3A%22Angleterre%7Epartner_grouping%22%2C%22name%22%3A%22Angleterre%22%7D%2C%7B%22id%22%3A%22Am%E9riques%7Epartner_grouping%22%2C%22name%22%3A%22Am%E9riques%22%7D%5D%2C%22region%22%3A%22Marseille%22%2C%22kind%22%3A%22import%22%2C%22sourceType%22%3A%22Best%20Guess%20customs%20region%20product%20x%20partner%22%7D%2C%7B%22color%22%3A%22#C14F4C%22%2C%22partnerClassification%22%3A%22partner_grouping%22%2C%22partner%22%3A%5B%7B%22id%22%3A%22Nord%7Epartner_grouping%22%2C%22name%22%3A%22Nord%22%7D%2C%7B%22id%22%3A%22Hollande%7Epartner_grouping%22%2C%22name%22%3A%22Hollande%22%7D%2C%7B%22id%22%3A%22Flandre_et_autres_%E9tats_de_l%27Empereur%7Epartner_grouping%22%2C%22name%22%3A%22Flandre%20et%20autres%20%E9tats%20de%20l%27Empereur%22%7D%5D%2C%22region%22%3A%22Marseille%22%2C%22kind%22%3A%22import%22%2C%22sourceType%22%3A%22Best%20Guess%20customs%20region%20product%20x%20partner%22%7D%5D",rel:"noopener noreferrer",target:"_blank",children:" le commerce du Levant est fortement réduit en temps de guerre. Faire une viz avec les part Toflit."})]}),(0,dc.jsx)("p",{children:"En 1748, baisse Italie (il y a une guerre là-bas je crois)."}),(0,dc.jsx)("h3",{id:"h.ts1t7dr716s7",children:"3.B Stratégies de maintien de la navigation à Marseille face à la guerre "}),(0,dc.jsx)("p",{children:"Le nombre d’entrées à Marseille rend imparfaitement compte de l’impact des conflits sur la navigation marseillaise, qui apparaît davantage en prenant en compte le rétrécissement des aires de navigation, mesuré ici en milles maritimes agrégées."}),(0,dc.jsx)("p",{children:"Titre: Tonnages estimés totaux passant par Marseille chaque année considérée"}),(0,dc.jsx)("p",{children:"Titre: Stage_length total agrégé pour tous et pour le pavillon FR"}),(0,dc.jsx)("p",{children:"Titre: Stage_length moyen par bateau pour tous et pour le pavillon FR"}),(0,dc.jsx)("p",{children:"Titre: répartition du tonnage total par pavillons"}),(0,dc.jsx)("p",{children:"Titre: répartition du nombre de bateaux par pavillons"}),(0,dc.jsx)("p",{children:"Titre: Répartition du ratio de tonnage par statut en guerre"}),(0,dc.jsx)("p",{children:"Titre: Répartition du ratio de bateaux par statut en guerre"}),(0,dc.jsx)("p",{children:"Hypothèse à vérifier: 1799 forte diminution de l’arrivée de gros bateaux"}),(0,dc.jsx)("p",{children:"Visus ex 4A"}),(0,dc.jsx)("p",{children:"Titre: Nombre total de miles parcourus pour chaque pavillon et chaque décennie"}),(0,dc.jsx)("p",{children:"Titre: Nombre moyen d’étapes pour chaque pavillon et chaque décennie"}),(0,dc.jsx)("p",{children:"La guerre questionne ainsi la permanence de la navigation française et le jeu des pavillons neutres. Elle affecte toutefois aussi les vitesses de navigation, que ce soit en raison de l’introduction des convois depuis le Levant, ou d’une navigation plus proche des côtes, avec des escales plus fréquentes, pour échapper aux corsaires ennemis."}),(0,dc.jsx)("p",{children:"Titre: Nombre de pavillons par décennies"}),(0,dc.jsx)("p",{children:"Titre: Vitesse moyenne pour chaque pavillon (années de guerre versus années de paix)"}),(0,dc.jsx)("p",{children:"Titre: Nombre de trajets total pour chaque pavillon (années de guerre versus années de paix)"}),(0,dc.jsx)("p",{children:"Titre: Nombre de trajets du pavillon français et des pavillons étrangers (années de guerre versus années de paix)"}),(0,dc.jsx)("p",{children:"Une tenue de la navigation française et/ou provençale ? (Convois, Navigation de concert)"}),(0,dc.jsxs)("ol",{children:[(0,dc.jsx)("li",{children:"Les neutres au service de Marseille: Effets de substitution dans le transport maritime "}),(0,dc.jsx)("li",{children:"Montrer la part du commerce qui passe aux neutres dans les années de guerre à partir des tonnages estimés des navires présents dans Navigo en projetant valeurs importations de Marseille par pays"}),(0,dc.jsx)("li",{children:"Sur quels marchés la présence neutre devient fondamentale?"})]})]})}function rN(e){return(0,dc.jsx)("div",{id:"part-4",children:(0,dc.jsx)("p",{children:"Finalement, la force de Marseille n’est pas sa participation à la croissance du commerce Atlantique français tirée par le système colonial. Elle ne repose pas non plus sur un dynamisme exceptionnel de son économie. Elle s’appuie sur sa situation de port méditerranéen dominant. Cette domination s'assoit sur la géographie. Idéalement placée à l’embouchure d’un axe fluvial majeur qui ouvre sur la deuxième métropole française, Lyon, Marseille est d’abord un emporium qui permet la rencontre entre les produits de son arrière pays (draps du Languedoc en particulier) destinés principalement aux marchés méditerranéens (Italie, Levant et dans une moindre mesure l’Espagne) et les produits du pourtour méditerranéen qui nourrissent le Sud-est français et son économie (Blé, cochenille, cotonnades ottomanes). Aussi, même si la Méditerranée est un espace en déclin relatif, elle constitue une base extrêmement solide pour le fonctionnement d’une économie portuaire dynamique tout au long de l’époque moderne et au XIXe siècle. Ces avantages s’inscrivent dans la longue durée, ils persistent après la fin de l’Ancien Régime et seront même renouvelés avec la conquête d’une partie de l’Afrique du Nord sous la restauration, puis l’ouverture du canal de Suez. Aujourd'hui encore, Marseille est un des deux principaux ports internationaux français."})})}function iN(e){return(0,dc.jsx)("div",{id:"part-4",children:(0,dc.jsx)("p",{children:"Finalement, la force de Marseille n’est pas sa participation à la croissance française du xviiie siècle tirée par le système colonial. Il n’est pas non plus dû à un dynamisme exceptionnel. C’est le fait que c’est un port méditerranéen important depuis très longtemps, pour des raisons géographiques persistantes. Même si la Méditerranée est un espace en déclin relatif, l’importance de son commerce est telle qu’elle forme une base pour le fonctionnement d’une économie portuaire dynamique tout au long de l’époque moderne et au xixe siècle. Le 2e empire français donne un nouveau sursi à Marseille. À force de sursis, le condamné enterre ses juges et ses concurrents. "})})}function aN(e){const{Caller:t}=e.components||{};return t||function(){throw new Error("Expected component `Caller` to be defined: you likely forgot to import, pass, or provide it.")}(),(0,dc.jsxs)("div",{id:"part-5",children:[(0,dc.jsx)("h2",{id:"h.glt45mz12av1",children:"Élucider le fonctionnement du port franc"}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"fonctionnement-port-franc",mode:"complete"})}),(0,dc.jsx)("p",{children:"Marseille bénéficie depuis au moins 1669 de privilèges commerciaux exceptionnels pour son commerce avec le Levant. À partir de 1703, une barrière douanière sépare la ville du reste du royaume, consacrant la franchise du port de Marseille. Le statut de port franc de Marseille a ensuite été étendu au commerce colonial par les lettres patentes de 1779 qui lui octroient la liberté du commerce avec les colonies françaises, sous condition d’accepter le régime d’entrepôt. Le fonctionnement du port franc n’apparaît pas très clairement dans les sources portant sur son commerce en 1789 (c’est-à-dire les références F12/1666 et 1667 aux Archives Nationales et F2/B14 aux Archives Nationales d’Outre-Mer, désormais ANOM). En 1789, trois bureaux proprement marseillais sont mentionnés par celles-ci, en plus des bureaux non-marseillais de la Direction des fermes de Marseille."}),(0,dc.jsx)("p",{children:"Mentionnons tout d’abord ces derniers, qui ne posent pas de difficultés particulières : il s’agit des bureaux de Arles, La Ciotat, Lambesc, La Penne et Septeme."}),(0,dc.jsx)("p",{children:"Arles et la Ciotat sont bien connus. Lambesc est entre Aix-en-Provence et Salon-de-Provence. La Penne est sans doute La Penne-sur-Huveaune, aujourd’hui dans la banlieue Est de Marseille. Sur la carte de Cassini, La Penne est très clairement au croisement du grand chemin menant de Marseille à Toulon et sur une frontière indiquée en pointillés. Julliany mentionne d’ailleurs le bureau de la Penne comme lieu d’expédition en direction de la Basse Provence (Juilliany, 1842, tome I, p. 129). Septeme désigne sans doute Septèmes-les-Vallons, au Nord de Marseille sur la route d’Aix-en-Provence, qui était le lieu de passage principal du commerce terrestre de Marseille avec le reste de la France (Julliany, 1842, tome I, p. 129). D’ailleurs, Septèmes et La Penne sont mentionnés parmi les bureaux placés au pourtour de la zone franche suite à un bornage de 1728 (Legay, 2023). Les autres bureaux du pourtour (La Gavotte, La Bourdonnière, Allauch, Aubagne et Cassis) ne sont pas mentionnés par les sources que nous examinons ici."}),(0,dc.jsx)("p",{children:'La Ciotat ne rapporte que des importations coloniales (dans ANOM Col F2/B14, tableau 3). D’ailleurs, cette source (qui provient de la Marine ou de l’Amirauté plutôt que de la Ferme) ne liste que des "Ports de France", sans utiliser les termes "bureau" ni "direction". C’est nous qui par cohérence avec les autres sources avons supposé que La Ciotat était un bureau de la direction de Marseille. Lambesc ne rapporte que des exportations vers Marseille. Arles, La Penne et Septèmes des importations et des exportations surtout avec Marseille, mais aussi avec l’Europe (pas les Colonies ni le Levant). On peut supposer qu’ils regroupaient de lieux périphériques de la direction de Marseille commerçant essentiellement avec le port franc et avec quelques partenaires étrangers.'}),(0,dc.jsxs)("p",{children:["Par ailleurs, Marseille est mentionné comme partenaire commercial par des rapporteurs",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Un «rapporteur» dans ce contexte est un bureau des fermes (ou un port pour les sources issues de l’Amirauté) signalant un flux commercial, que cela soit une exportation ou une importation.",children:"?"}),' français se trouvant hors de la direction de Marseille, y compris dans le Ponant (eg. Saint-Malo, Nantes, Rouen, mais aussi Amiens, Charleville...). Ces rapporteurs français n’indiquent jamais autre chose que "Marseille" (ou "port de Marseille") pour leur commerce avec la direction de Marseille.']}),(0,dc.jsx)("p",{children:'Voyons maintenant le commerce rapporté par Marseille en tant que telle. Pas de difficulté du côté des importations rapportées par Marseille : elles sont toujours déclarées par le bureau de "Marseille".'}),(0,dc.jsx)("p",{children:'Les choses sont plus compliquées pour les exportations. Elles sont rapportées par trois bureaux différents : "Marseille" tout court (2202 flux en 1789), "Marseille - Domaine d\'Occident" (1359 flux) et "Marseille - Poids et Casse" (203 flux, où un flux représente l’enregistrement de l’importation ou de l’exportation d’un produit particulier entre un rapporteur et un partenaire). '}),(0,dc.jsx)("p",{children:'Rambert (1954, t. VI, p. 225), dans son Histoire du Commerce de Marseille, tome IV (consacré à la période de 1660 à 1789) donne les explications suivantes, essentiellement reprises de Jules Julliany (1842, tome 1, p. 86-87, 231 et 292) : "Les plus importants [bureaux] étaient au nombre de trois: le bureau du fameux droit de 20% perçu au profit de la Chambre de Commerce en même temps que le droit de Consulat; le bureau des fermes du domaine d\'Occident qui percevait un droit de 3% sur les marchandises d\'origine coloniale [nous comprenons "importations depuis les colonies"], enfin le bureau du Poids et Casse, où 75 peseurs publics procédaient au pesage des marchandises vendues sur place et percevaient au profit du Roi un droit qui avait été doublé en 1669". Et en note : "Colbert avait pris cette mesure pour donner au Roi une compensation aux pertes subies par l\'application de l\'édit du port franc. [nous comprenons "droit sur toutes les marchandises vendues à Marseille"]. C\'était le bureau le plus actif; il délivrait les acquits-à-caution, recevait les manifestes des capitaines et faisait visiter les colis à leur débarquement, percevait les droits sur les marchandises étrangères envoyées directement de Marseille aux colonies françaises et plombait celles qui étaient expédiées en transit". Nous ne savons pas si Rambert dit "le plus actif" pour dire "celui qui fait plus d\'opérations" ou pour signifier que "toutes les marchandises passent par là", comme il devrait être, vu qu\'il parle de "toutes les marchandises vendues à Marseille". '}),(0,dc.jsx)("p",{children:"Ces textes ne mentionnent que les importations de Marseille : pourtant dans les sources, ces bureaux ne rapportent que des exportations."}),(0,dc.jsxs)("p",{children:["Pour le bureau des Poids et Casse (203 flux), 202 flux (25 M de lt) sont en direction de Marseille. Il ne s’agit que de produits français. Il est donc plausible qu’il s’agisse d’exportations de la France vers le port franc de Marseille pour sa propre consommation, comme suggéré par Julliany et Rambert. Se pose la question d’un double compte éventuel avec les flux d’exportation des autres bureaux français vers Marseille (c. 17 M de lt",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Ce chiffre se décompose sur le graphique en 6,8 M venant des bureaux de France hors direction de Marseille ; 0,3 M venant d’Arles ; 2,8 M venant de La Penne ; 0,4 M venant de Lambesc et 6,6 M venant de Septèmes.",children:"?"}),") : les chiffres sont bien du même ordre de grandeur, mais il ne serait pas logique que l’ensemble des importations de Marseille depuis la France soit plus faible que les importations pour la sa propre consommation. Il nous semble donc plus plausible de penser que les 25 M de lt d’importations pour la consommation de Marseille s’ajoutent aux 16,5 M de lt importés dans le port franc pour ré-exportation. "]}),(0,dc.jsxs)("p",{children:['Le dernier flux issu du bureau des Poids et Casse est en direction des "Etats de l’Inde" (ANOM Col F2/B14, tableau 28) : 0,7 M de livres tournois. Le tableau précise "Marseille, Poids et Casse, Sous Pavillon Étranger" : il s’agit sans doute des envois du commerce privé de Marseille pour contourner le monopole de la Compagnie des Indes re-crée en 1785. Le tableau mentionne le reste du commerce (à la fois privé et par la Compagnie',(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"D’après Conan (1939, note 1 p. 164), il n’y a que deux expéditions de la Compagnie des Indes de 1785 durant toute son existence portà partir de Marseille.",children:"?"}),") lorsqu’il liste 0,8 M de lt d’exportations vers l’Isle de France et de Bourbon",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Soit, respectivement, l’actuelle île Maurice et l’actuelle île de la Réunion.",children:"?"}),', et 0,1 M de lt vers les "Etats de l’Inde issus de "Marseille, domaine d’Occident" (voir Carrière (1973, p. 345) et Dermigny (1959-1960, tome I, p. 155). Les produits ne sont précisés pour aucun de ces flux.']}),(0,dc.jsx)("p",{children:'Laissons de côté le commerce vers l’Asie. Il serait naturel que les exportations du bureau "Marseille, domaine d’Occident" soient formées des produits coloniaux en entrepôt. Les flux recouvrent en fait toutes les catégories de produits, et seulement 37 flux (sur 1 389) sont des produits coloniaux, exportés soit vers la France (hors Marseille) soit vers le Monde (hors colonies). Ces produits coloniaux ne sont que d’une valeur limitée (0,5 M de lt) et semblent ne pas provenir des colonies françaises de l’Amérique (la liste exhaustive en est : Café du Levant, Chocolat, Cannelle, Girofle, Poivre, Sucre candi et Thé). Il pourrait donc s’agir de produits coloniaux issus du commerce non-colonial ou asiatique (en petite quantité). À part les deux flux vers l’Asie déjà mentionnés, tous les flux viennent de la source AN F12 1666, qui est issue du travail de la Ferme.'}),(0,dc.jsx)("p",{children:'Les exportations de "Marseille" (930 flux) sont toutes soit des ré-exportations de produits coloniaux (9 flux et 25 M de lt), soit des exportations vers les colonies françaises de l’Amérique, le Sénégal ou la Guinée (921 flux et 15 M de lt). Ce sont ces flux qu’on s’attendrait à voir attribués au bureau "Marseille, domaine d’Occident". La source pour tous ces flux est ANOM Col F2/B14 (tableaux 5 et 20), qui est probablement issue du travail de l’Amirauté et de la Marine. '}),(0,dc.jsx)("p",{children:'Notre hypothèse est donc que la distinction entre le bureau exportateur "Marseille" et "Marseille, domaine d’Occident" (hors du commerce avec l’Asie) n’est qu’un effet de source. En tous les cas, nous ne trouvons pas d’explication logique à la distinction des deux bureaux. Par contre, le bureau exportateur "Marseille, Poids et Casse" ne porte que sur la consommation propre de la ville de Marseille. C’est surprenant car, d’après Leguay (2023), c’est plutôt le bureau des Poids et Casse qui s’occupait de l’établissement de la balance du commerce.'})]})}function oN(e){return(0,dc.jsx)("div",{id:"part-5",children:(0,dc.jsx)("p",{children:"Coucou"})})}function sN(e){const{Caller:t}=e.components||{};return t||function(){throw new Error("Expected component `Caller` to be defined: you likely forgot to import, pass, or provide it.")}(),(0,dc.jsxs)("div",{id:"part-6",children:[(0,dc.jsxs)("p",{children:["Le présent site a été réalisé dans le cadre du ",(0,dc.jsx)("a",{className:"c15",href:"https://anr.portic.fr/",rel:"noopener noreferrer",target:"_blank",children:"programme de recherche ANR PORTIC"}),". Ce programme porte sur les dynamiques de navigation et du commerce extérieur au dix-huitième siècle, un commerce qui s’effectue largement par voie maritime. Outre la meilleure compréhension de ces dynamiques par le croisement de deux jeux de données, un enjeu fondamental du programme est de chercher des méthodes de qualification et d’appréhension de l’incertitude des données historiques, en expérimentant des modes de visualisation et d’écriture appropriés."]}),(0,dc.jsxs)("p",{children:["Dans ce cadre, le Working Package n°5 de ce programme de recherche consiste à effectuer une série d’études de cas tirant parti de deux corpus existants de sources historiques numérisées : ",(0,dc.jsx)("a",{className:"c15",href:"http://navigocorpus.org/",rel:"noopener noreferrer",target:"_blank",children:"Navigocorpus"}),", une base de données portant sur l’histoire de la navigation pilotée par Silvia Marzagalli et Christine Plumejeaud ; et ",(0,dc.jsx)("a",{className:"c15",href:"http://toflit18.medialab.sciences-po.fr/#/home",rel:"noopener noreferrer",target:"_blank",children:"Toflit18"}),", une base de données portant sur le commerce extérieur de la France, pilotée par Loïc Charles et Guillaume Daudin. À ce titre, cette étude de cas s’inscrit dans un triptyque composé avec deux autres enquêtes publiées au format web : "]}),(0,dc.jsxs)("ul",{children:[(0,dc.jsxs)("li",{children:[(0,dc.jsx)("a",{className:"c15",href:"https://medialab.github.io/portic-storymaps-2021",rel:"noopener noreferrer",target:"_blank",children:"Commerce multi-échelles autour du port de La Rochelle au XVIII"}),(0,dc.jsx)("a",{className:"c15",href:"https://medialab.github.io/portic-storymaps-2021",rel:"noopener noreferrer",target:"_blank",children:"e"}),(0,dc.jsx)("a",{className:"c15",href:"https://medialab.github.io/portic-storymaps-2021",rel:"noopener noreferrer",target:"_blank",children:" siècle"})]}),(0,dc.jsxs)("li",{children:[(0,dc.jsx)("a",{className:"c15",href:"https://medialab.github.io/portic-storymaps-2022",rel:"noopener noreferrer",target:"_blank",children:"Commerce, contrebande et ports francs : le cas de Dunkerque au XVIII"}),(0,dc.jsx)("a",{className:"c15",href:"https://medialab.github.io/portic-storymaps-2022",rel:"noopener noreferrer",target:"_blank",children:"e"}),(0,dc.jsx)("a",{className:"c15",href:"https://medialab.github.io/portic-storymaps-2022",rel:"noopener noreferrer",target:"_blank",children:" siècle"})]})]}),(0,dc.jsx)("p",{children:"Ces réalisations visent à valoriser le travail déjà accompli lors de premières entreprises de numérisation pour chacune des deux bases (navigocorpus et toflit18), via l’étude approfondie de sous-ensembles signifiants dans les données. Ces études éclairent des questions disciplinaires existantes sous un nouveau jour grâce aux nouveaux matériaux et méthodes offerts par les bases de données mobilisées par le programme. Les questions soulevées par une telle initiative sont multiples :"}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"Comment mobiliser ensemble deux sources dont certaines dimensions sont incommensurables ou difficiles à mettre en équivalence ? Comment croiser les données numérisées des deux bases avec des connaissances plus denses et qualitatives sur les phénomènes étudiés, apportées par des historiens spécialistes de la région étudiée ? "}),(0,dc.jsx)("li",{children:"Comment prendre en compte, au moment de l’enquête et du raisonnement, l’importante stratification de transformations, de réductions et de décisions interprétatives constituant la chaîne d’opérations documentaires qui relie les sources initiales avec les données qui en ont été tirées ? "}),(0,dc.jsx)("li",{children:"Comment prendre en compte l’incertitude ou l’incomplétude des données tout en proposant une analyse scientifiquement solide des phénomènes étudiés ? "}),(0,dc.jsx)("li",{children:"Comment faire dialoguer les formes classiques de l’écriture historique - le récit déployé phrase après phrase, l’argument déroulé paragraphe par paragraphe - avec les formes d’écriture diagrammatique et computationnelle qu’implique la composition d’un site web ? "}),(0,dc.jsx)("li",{children:"Comment gérer la collaboration interdisciplinaire et la partition d’expertises qu’implique une telle écriture multimodale ?"})]}),(0,dc.jsx)("p",{children:"Toutes ces questions ont été travaillées lors du processus de collaboration qui a mené à l’élaboration de ce site, dont voici un bref récit à des fins de documentation et de modeste retour d’expérience pratique et méthodologique pour d’autres recherches similaires."}),(0,dc.jsx)("h2",{id:"h.dru36nbx6gy9",children:"D’une série de questionnements à une semaine d’enquête"}),(0,dc.jsxs)("p",{children:["L’étude de cas dont ce site est l’aboutissement a été articulée autour d’un format de collaboration intensive que nous appelons datasprint",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":'Venturini, Tommaso, Anders Munk, and Axel Meunier. "Data-sprinting: A public approach to digital research." Routledge handbook of interdisciplinary research methods. Routledge, 2018. 158-163.',children:"?"})," et qui consiste à faire travailler ensemble des expert.e.s de plusieurs disciplines sur un temps court et avec des questions de recherche déterminées à l’avance, sur la base d’un ou plusieurs jeux de données préparés pour l’occasion."]}),(0,dc.jsx)("p",{children:"En amont du datasprint, nous avons conduit pendant plusieurs mois un double travail de préparation des données, et de préparation des questions de recherche. "}),(0,dc.jsx)("p",{children:"Sur le plan des données, les équipes de Navigocorpus et de Toflit18 ont pu bénéficier de l’important travail de nettoyage et d’affinement concernant les espaces et les périodes étudiées déjà réalisé dans le cadre du datasprint sur la région de La Rochelle et de celui sur Dunkerque. Pour celui-ci, les données navigocorpus relatives à Marseille ont notamment fait l’objet d’une attention particulière et d’un important travail de curation et de vérification par Silvia Marzagalli, Christine Plumejeaud et Pierre Niccolo’ Sofia, chercheur post-doctoral ayant rejoint le programme pour sa dernière année. Différentes sources complémentaires aux deux bases principales ont également été explorées et parfois transcrites en vue de la semaine de travail."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{className:"is-invalid",id:"schemas-generaux"})}),(0,dc.jsx)("p",{children:"Sur le plan de la préparation des questions de recherche, nous avons conduit une série de réunions préliminaires reliées par des documents en ligne rédigés collaborativement, qui nous ont aidé à identifier des questions pertinentes en regard de l’histoire de Marseille et de la littérature existante, mais aussi compatibles avec ce que les données nous permettaient - ou pas - d’explorer et de visualiser. Ce travail d’ajustement et de mise en correspondance entre les questions et les données a ainsi couru sur plusieurs mois et a notamment profité d’un très important travail d’état de l’art bibliographique effectué par Pierre Niccolo’ Sofia. Il nous a permis à la fois d’identifier les activités d’exploration les plus pertinentes à proposer aux participants durant l’atelier, et d’éviter les chausses-trappes qui nous auraient conduit dans des questionnements impossibles à résoudre."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{className:"is-invalid",id:"modules-screencast"})}),(0,dc.jsxs)("p",{children:["La semaine de collaboration intensive a ainsi été préparée pour être structurée autour de modules ou pistes d’enquête, associant pour chacune : les questions historiques et économiques à explorer, la bibliographie pertinente pour ces questions, un balisage technique sur les données à considérer dans les bases de données, et des prémices de questions opérationnalisables à travers l’analyse et la visualisation des données, à développer ensuite avec les ingénieurs et designers mobilisés pour l’atelier. La vidéo ci-dessus présente un aperçu rapide du format de ces documents préparatoires. Contrairement aux années précédentes où les modules se voulaient des pistes d’exploration à réarticuler avec un plan argumentatif à la suite des enquêtes, nous avons fait le choix, pour cette dernière étude de cas, d’établir un plan argumentatif en amont et d’y indexer les différents modules de travail, afin de s’assurer de pouvoir couvrir l’ensemble du travail préparatoire nécessaire à établir la publication finale dans le cadre de la semaine de datasprint. Ce choix, informé par les difficultés rencontrées pour la deuxième étude de cas sur Dunkerque, dues à un trop grand travail exploratoire reporté à l’après-datasprint",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Voir l’étude de cas Commerce, contrebande et ports francs : le cas de Dunkerque au XVIIIe siècle",children:"?"}),", a ancré la semaine de datasprint dans une perspective beaucoup plus opérationnelle que les précédentes, favorisant une plus grande efficacité, mais amoindrissant la dimension exploratoire et expérimentale qui fait d’habitude souvent le plaisir de la participation à un datasprint."]}),(0,dc.jsx)("p",{children:"La semaine de datasprint s’est déroulée en février 2023 au CAES du CNRS La Ville Perrotine, sur l’île d’Oléron. Littéralement isolés, dans un bâtiment de travail situé sur une île au milieu du complexe CNRS lui-même, nous avons passé une semaine en circuit fermé dans un bâtiment nous offrant trois salles de travail nous permettant d’alterner phases de plénières et sessions de travail en petits groupes."}),(0,dc.jsx)("p",{children:'La semaine de travail a été organisée autour d’une infrastructure à la fois spatiale et numérique articulée autour des modules d’enquêtes élaborés pour la préparation de la semaine de travail. Sur le plan spatial, le lieu de travail a été agencé en fonction d’un grand espace d’affichage commun, placé sur l’un des murs de la salle principale, que nous avons utilisé pour nous répartir les tâches à effectuer et pour partager de manière passive les résultats en train d’être produits. Chaque espace du mur s’est vu dédié à l’un des "modules d’enquête" définis avant le datasprint, et les personnes qui ont travaillé à chacun de ces modules y ont progressivement accolé visualisations, post-its d’analyse ou d’avertissement sur des points d’attention relatifs aux données, croquis de visualisations à effectuer, etc. Autour de cette surface d’affichage partagé, différents groupes constitués de 2 à 5 personnes, et toujours mixtes du point de vue des compétences apportées, se sont formés et répartis sur l’ensemble des salles et espaces disponibles dans les locaux du médialab à Sciences Po.'}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{className:"is-invalid",id:"photos-datasprint"})}),(0,dc.jsx)("p",{children:"Sur le plan numérique, le collectif d’enquête a été structuré autour de l’utilisation d’un dossier google drive partagé, organisé en dossiers correspondant aux modules d’enquêtes, et d’un répertoire de code source sur la plateforme github, utilisé par toutes les personnes sachant programmer pour partager des scripts et des fichiers de données utiles."}),(0,dc.jsx)("p",{children:"Le datasprint s’est terminé sous la forme d’une plénière durant laquelle l’ensemble des résultats ont été présentés et discutés, ainsi que d’une discussion générale sur l’expérience des datasprints et des études de cas PORTIC. L’atelier a abouti à la rédaction d’un premier document de rédaction martyre partiellement rédigé, intégrant dans un fil argumentatif déjà très abouti l’ensemble des productions réalisées durant la semaine sous la forme de copies d’écran ou de croquis. Nous avons collectivement convenu que cette expérience, comparée aux deux précédentes, avait été la plus efficace et productive, peut-être du fait du contexte social et géographique de la semaine de travail en vase clos, ou encore de la préparation très dense des modules de travail et de leur articulation a priori à un plan de publication ; mais qu’elle avait également été la plus intense et la plus fatigante, du fait du rythme de production extrêmement soutenu qui a été adopté par les ingénieur·es pour la réalisation des dizaines de visualisations ayant émergé de la semaine, et pour les économistes et historien·nes pour l’élaboration d’un argument commun dans un temps très contraint. "}),(0,dc.jsx)("h2",{id:"h.fxih2baprl8o",children:"La fabrication d’un site web comme pivot pour une collaboration interdisciplinaire"}),(0,dc.jsx)("p",{children:"À la suite du datasprint, nous avons convenu d’une méthodologie de travail consistant à laisser les designers du projet reprendre la main sur la structuration de la publication en se faisant force de proposition pour des visualisations de communication à même d’orienter la rédaction des textes finaux. Pour ce faire, un tandem composé de Paul Girard et Robin de Mourat a effectué pendant plusieurs jours un travail de conception et de synthèse graphique visant à proposer une série de quelques visualisations significatives et à même de porter la structure argumentative esquissée collectivement durant la semaine de travail."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{className:"is-invalid",id:"maquettes-visualisations"})}),(0,dc.jsx)("p",{children:"Ces dernières propositions ont été discutées et amendées avec les personnes en charge de la rédaction des textes, puis intégrées dans un brouillon de site mis à jour quotidiennement qui a permis aux historiennes et économistes de se projeter et construire un texte directement connecté aux visualisations."}),(0,dc.jsx)("p",{children:'Afin d’élaborer un document propre à être publié et à transmettre un récit et des arguments à partir des données des deux bases, nous avons donc, comme pour les deux études précédentes, tenté d’utiliser la perspective de la fabrication d’un site pour articuler trois types "d’écriture" : la confection de nouveaux fichiers de données correspondant aux enquêtes soulevées par les activités de la semaine (écriture computationnelle) ; la confection de visualisations d’informations (écriture diagrammatique) ; enfin, bien sûr, la mise en récit et en argument historique de l’étude de cas (écriture en prose).'}),(0,dc.jsx)("p",{children:'Dans ce cadre, nous avons mis en place une infrastructure de travail visant à développer progressivement le présent site web alors même que ses "contenus" textuels et graphiques étaient encore en cours d’élaboration. Le site web en construction a ainsi tout autant servi d’objectif que de moyen de rencontre entre les différentes activités qui ont suivi la semaine d’atelier datasprint.'}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{className:"is-invalid",id:"processus-maj"})}),(0,dc.jsxs)("p",{children:["La fabrication du site présenté au public a été articulée autour d’un protocole automatisé qui a permis de mettre le site à jour quotidiennement pendant sa phase d’écriture et de développement, et ainsi de faire progresser conjointement sa structure, son aspect graphique et les divers contenus qui le peuplent (voir son ",(0,dc.jsx)("a",{className:"c15",href:"https://github.com/medialab/portic-storymaps-2022",rel:"noopener noreferrer",target:"_blank",children:"répertoire github"})," pour plus d’informations). Plus précisément, ce protocole automatisé consistait à récupérer les contenus écrits dans un google documents écrit par les historien.ne.s, les données des bases Navigocorpus et Toflit18 sur leurs espaces numériques respectifs, et enfin à produire un ensemble de données optimisées pour le web avant de refabriquer le site."]}),(0,dc.jsx)("p",{children:'Cette méthode de travail sur mesure nous a permis de multiplier les itérations sur les données, les visualisations et les textes, afin de développer progressivement un document ajusté et cohérent pour la lecture. Elle nous a également permis d’échapper à une approche qui voudrait formater la production du site de manière trop séquentielle, c’est-à-dire faisant suivre un premier temps de "conception" puis un deuxième temps "d’exécution", pour plutôt faire place à la découverte et au dialogue avec les différents matériaux en train de se développer. Elle a permis de travailler de manière progressive les rapports entre les différents types d’écriture, en testant par exemple les rapports entre textes et images au moyen de croquis papier directement intégrés dans le site pour permettre aux historiennes et économistes de se projeter dans le résultat final pendant que les visualisations finalisées étaient élaborées.'}),(0,dc.jsx)("p",{children:"Ainsi, la méthode de travail et de montage du site adoptée ici, outre la dimension d’optimisation qu’implique l’automatisation de certaines tâches, a été envisagée comme le moyen de favoriser un dialogue plus organique entre les différentes écritures en jeu dans ce document : en réalisant simultanément le design du site, celui des visualisations, et les textes qui les accompagnent, nous avons tenté de faire profiter chacune de ces activités l’une de l’autre, comme des sources d’invention ou de solidification mutuelle, plutôt que de les considérer comme des tâches spécialisées et/ou articulées selon un régime de subordination (de l’histoire à la technique, ou du visuel au textuel, ou de l’argument à son illustration, etc.). "}),(0,dc.jsx)("h2",{id:"h.ub5q8dkj8ap1",children:"Un document destiné à tisser des liens avec d’autres activités et d’autres publics"}),(0,dc.jsx)("p",{children:'Ce document web est pensé comme un objet autonome déroulant le récit scientifique de l’histoire de Marseille au dix-huitième siècle, mais aussi comme le point de départ d’assemblages scientifiques et didactiques encore à venir. Afin de qualifier le registre d’écriture et le degré de complexité que nous nous autoriserions, nous avons convenu de le fabriquer avec l’idée de l’adresser à un public "intermédiaire" (ni celui d’un "grand public" toujours insaisissable, ni celui de "pairs" avec lesquels nous interagissons via d’autres types de documents), c’est-à-dire un public constitué d’étudiant.e.s en histoire, de professeur.e.s d’histoire du secondaire, ou d’amateur.ice.s avancés passionnés par le commerce et la navigation d’Ancien Régime ou la question de la contrebande. Cependant, le site est également pensé pour pouvoir s’articuler avec deux publics complémentaires :'}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"les personnes spécialisées dans la médiation et/ou la vulgarisation, qui pourront utiliser certaines des visualisations ici présentes pour des initiatives destinées à un plus grand public;"}),(0,dc.jsx)("li",{children:"les historien.ne.s spécialisés, qui pourront citer ces visualisations dans des publications conventionnelles en revues ou monographies et ainsi s’appuyer sur ces dernières pour continuer nos enquêtes ou les faire travailler de manière plus avancée"})]}),(0,dc.jsx)("p",{children:'Pour ce faire, nous avons notamment rendu chacune des visualisations "détachable" du récit proposé via la page Atlas - et plus techniquement en dotant chacune des visualisations d‘une adresse URL propre.'}),(0,dc.jsxs)("p",{children:["Par ailleurs, le ",(0,dc.jsx)("a",{className:"c15",href:"https://github.com/medialab/portic-storymaps-2023",rel:"noopener noreferrer",target:"_blank",children:"code source du site"}),", partagé sous licence libre, a été construit et documenté de manière à pouvoir être dérivé - en tout ou partie - pour d’autres projets à venir. Il est enfin à noter que toutes les données utilisées - et les scripts qui les génèrent à partir des données complètes de Toflit18 et Navigocorpus, accessibles toutes les deux librement - sont également inclus dans le code source du site, rendant nos visualisations et résultats entièrement reproductibles."]}),(0,dc.jsx)("h2",{id:"h.jhdiwhxrxrb0",children:"Coda : un travail de documentation réflexive sur les pratiques de recherche interdisciplinaire en humanités numériques à travers le cas du programme PORTIC"}),(0,dc.jsx)("p",{children:"En parallèle et en complément du travail relatif à l’étude de cas ici présente, nous avons également profité de la dernière année du programme PORTIC pour engager un travail de documentation et de réflexion épistémologique et méthodologique sur l’ensemble de l’expérience qu’ont constitué les nombreuses années sur lesquelles s’est écoulé le programme PORTIC."}),(0,dc.jsxs)("p",{children:["PORTIC",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Ports et Technologies de l’Information et de la Communication. Site du programme : https://anr.portic.fr/",children:"?"})," est un programme de recherche typique des humanités numériques et de l’histoire quantitative contemporaine : il s’inscrit dans la suite de très longues opérations de numérisation de sources historiques conduites sur plusieurs années, pour maintenant, dans un second temps, tenter de les valoriser sur les plans scientifique et social. Après des années passées dans l’ombre des archives et dans l’enfer des bases de données, des arguments commencent à être produits, des outils d’exploration développés, des visualisations réalisées. Ce deuxième souffle du tournant numérique de la recherche historique est également un deuxième souffle de l’interdisciplinarité et de la collaboration. En effet, il demande, pour réfléchir, écrire et publier à partir de ces sources numérisées, d’inventer de nouvelles formes de mise en commun et de dialogue entre des disciplines aussi variées que l’histoire, l’économie, la géomatique et le design."]}),(0,dc.jsx)("p",{children:"Dans ce cadre, le recours à la production de graphiques et à la fabrication de statistiques, bien qu’indispensable pour élaborer des connaissances pertinentes à propos de sources numérisées impliquant des données quantitatives, peut être problématique : il a tendance à donner une impression d’immédiateté et d’évidence à des arguments qui sont pourtant le fruit d’une longue et hétérogène chaîne de pratiques, et l’objet de nombreuses incertitudes avec lesquelles les collectifs de recherche doivent constamment se frotter et composer pour élaborer leur pensée. "}),(0,dc.jsx)("p",{children:"Nous sommes face à un double défi : d’une part, il s’agit de situer davantage les nombres et les images que produisent nos recherches dans la généalogie des pratiques qui leur ont donné naissance, afin de mieux les comprendre, les discuter et se les approprier ; mais il s’agit aussi de déjouer la tendance des formats conventionnels de communication scientifique à occulter la richesse intellectuelle du processus de collaboration interdisciplinaire lui-même. Ces derniers formats conventionnels (articles, communications dans colloques, monographies) se concentrent en effet souvent sur les résultats disciplinaires au détriment des petites découvertes, des avancées faites en cours de route, des déboires et épreuves instructives, etc. "}),(0,dc.jsx)("p",{children:"Dans ce cadre, nous avons essayé de décrire, de qualifier et de valoriser ce que la collaboration interdisciplinaire fait aux disciplines et aux métiers qu’elle met en relation, ainsi que les pratiques et situations multiples - et parfois insolites - par lesquelles se font les découvertes dans ces contextes. Il s’agit aussi de situer et de qualifier épistémologiquement les productions non-discursives (nombres, images, interfaces, ...) générées par PORTIC vis-à-vis de la généalogie des pratiques et procédures qui les ont produites. Il est enfin nécessaire de trouver un mode de mise en discussion du programme PORTIC adapté à ses problématiques centrales : la gestion fine de l’incertitude historique, et la place de la matérialité (numérique) et de la visualité dans l’étude de l’histoire économique et maritime du XVIIIème siècle."}),(0,dc.jsx)("p",{children:'Plutôt que de produire un discours et des images bien lissées, nous voulons donc conclure la série des trois études de cas du programme de recherche PORTIC par un document ouvrant la porte de la "cuisine" de notre recherche en humanités numériques. Il s’agit de produire une description fidèle et ouverte de la collaboration interdisciplinaire dans toute sa complexité et son hétérogénéité, sans préjuger des dimensions ou opérations les plus décisives dans la conduite d’une telle aventure.'}),(0,dc.jsx)("p",{children:'Nous souhaitons donc proposer une restitution des études de cas du programme du point de vue de leur méthodologie et de leur déroulement pratique, sous la forme d’un "making of scientifique" audiovisuel de la dernière étude de cas de PORTIC, portant sur le commerce et la navigation de Marseille au dix-huitième siècle. Il s’agit de donner à voir comment peut se conduire une recherche interdisciplinaire en humanités numériques, depuis les premières réunions de préparation jusqu’à la longue traîne de la finition d’une publication, en passant par les moments décisifs de collaboration face à face.'}),(0,dc.jsx)("h3",{id:"h.roq1lak7f6o",children:'"S’entendre. L’interdisciplinarité en pratique" : un documentaire sur l’étude de cas réalisé par Fabien Luszezyszyn et Aymeric Poidevin'}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{className:"is-invalid",id:"documentaire-s-entendre"})}),(0,dc.jsxs)("p",{children:['Le document résultant de notre démarche s’intitule "S’entendre. L’interdisciplinarité en pratique." Il a été réalisé par Fabien Luszezyszyn et Aymeric Poidevin (',(0,dc.jsx)("a",{className:"c15",href:"https://lascopdessalesgosses.com/",rel:"noopener noreferrer",target:"_blank",children:"scop des sales gosses"}),") à la demande de l'équipe de l'ANR PORTIC, qui nous ont suivi et filmé durant l’entièreté de la semaine du datasprint, du 27 février au 3 mars 2023. "]}),(0,dc.jsx)("p",{children:"Ce documentaire permet d’appréhender les motifs et les enjeux de l'engagement de chacun au service du projet commun, la diversité des langages et des pratiques impliquées dans l’enquête collective, l'intensité des échanges qui continuent au-delà des horaires pourtant très intenses des journées de travail, sans masquer les tensions, la fatigue, les frustrations suscitées par la collaboration. Finalement, loin des discours prophétiques, réducteurs ou généralisants à propos de la collaboration entre les disciplines dans des cadres impliquant le travail des données numériques, nous avons voulu partager une description située et réaliste de la fabrique de l'interdisciplinarité."}),(0,dc.jsx)("p",{children:"Ce document a avant tout un objectif scientifique : celui de décrire une trajectoire de collaboration interdisciplinaire à l’œuvre (et peut-être la comparer avec les modèles produits par les écrits positionnels et les demandes de financement en humanités numériques). À partir de ce dernier, que nous allons nous employer à valoriser dans des contextes multiples à venir, nous entendons nourrir une discussion sincère et fructueuse à propos des multiples enjeux qui sous-tendent la collaboration interdisciplinaire, et donner l’envie de prolonger cette expérience réflexive par de nouvelles initiatives."}),(0,dc.jsx)("h3",{id:"h.lnpq3tkc5k0l",children:"Faire l’histoire de PORTIC : vers une archive multimodale d’une rare richesse pour la compréhension des enjeux et dynamiques de collaboration interdisciplinaire"}),(0,dc.jsxs)("p",{children:["En parallèle de la réalisation du documentaire, nous avons engagé un travail (encore) plus ambitieux d’archivage ayant vocation à constituer un fonds numérique multimodal et hétérogène regroupant l’ensemble des traces dont nous disposons pour rendre compte de la conduite de la troisième étude de cas de PORTIC ici présentée. Pour ce faire, nous avons enregistré la plupart des réunions préliminaires au datasprint",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Réalisées pour la plupart via la plateforme Zoom.",children:"?"}),", sauvegardé l’ensemble des documents et codes produits, et envisageons également de faire un travail de sélection et de préparation dans nos échanges mails pertinents pour la compréhension des dynamiques de collaboration en jeu. À partir de ce travail, nous entendons constituer une archive d’une richesse rare qui permettra à des collègues intéressés différents aspects de notre expérience d’y porter un regard et une analyse nouvelle. Cette archive, qui devrait être mise en ligne d’ici l’année 2025, sera limitée en accès mais décrite en détail afin de permettre de nouvelles collaborations impliquant des personnes tierces et des anciens membres du programme PORTIC dans l’analyse commune de ce matériau."]}),(0,dc.jsx)("p",{children:"Les réflexions individuelles et premières discussions nous ont permis d’esquisser une série de questionnements qui permettraient d’interroger le matériau que nous sommes en train d’archiver. En voici quelques uns en guise d’exemple :"}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:'habitus disciplinaires et trajectoires (parfois chaotiques) de coordination : tactiques de traduction et de clarification depuis un jargon disciplinaire vers un autre, rétablissement de situations d’anomie/confusion, "sauts disciplinaires" à négocier pendant les discussions collectives et les phases de travail individuelles de chacun - comment se parle-t-on dans un processus interdisciplinaire ?'}),(0,dc.jsx)("li",{children:"conditions de travail, contexte institutionnel et inscription socio-professionnelle du projet : question des rythmes du travail sur projet/calendrier/milestones, de la multi-activité des personnels (entre plusieurs projets, entre recherche et enseignement, ...), des rapports de domination (disciplinaires, statutaires), des processus de délégation"}),(0,dc.jsx)("li",{children:'interdisciplinarité et spécialisation : dynamiques d’apprentissage (mutuel) ou au contraire de délimitation de frontières ("ce n’est pas de mon ressort") dans le cours des situations - place de la spécialisation/technicité dans ces processus - faut-il essayer de construire un langage commun ou apprendre à devenir l’autre ?'}),(0,dc.jsx)("li",{children:"relation entre sémiologie et épistémologie : processus de traduction hétérogènes depuis les sources jusqu’aux documents produits - comment la circulation générative des hypothèses à travers différents langages et systèmes de signes (texte, code, tableaux, images) produit-elle des arguments et des hypothèses ? et comment la qualifier ? "}),(0,dc.jsx)("li",{children:'place de la matérialité dans le processus de recherche : quel est le rôle de l’espace, de la scénographie, des objets dans ces projets à dominante "numérique" ?'}),(0,dc.jsx)("li",{children:"incertitude et négociation : comment gère-t-on la dimension d’incertitude très forte de notre recherche dans les discussions et les processus de prise de décision à l’intérieur du collectif ?"}),(0,dc.jsx)("li",{children:'intérieur et extérieur - rapport entre écriture (collective) et publication : comment la constitution d’un "nous" au fil du processus du projet et d’un "eux" destinataire de la publication structure-t-elle la formulation des arguments et le choix de ce qui doit être mis en coulisse ou sur le devant de la scène ?'})]}),(0,dc.jsx)("p",{children:"Ces pistes de réflexion sont appelées à évoluer et se préciser au fil du développement de ce projet, mais aussi et surtout par le contact avec des partenaires extérieurs aptes à collaborer avec nous pour tirer le plus d’apprentissages possibles de notre expérience de collaboration. Nous accueillons en ce sens avec le plus vif intérêt d’éventuelles manifestations d’intérêt de la part de personnes versées dans l’anthropologie des sciences et des pratiques savantes, dans l’anthropologie filmique, dans le champ des réflexions méthodologiques et épistémologiques à propos des humanités numériques, ou encore dans le champ de la recherche en design. En parallèle de cet appel et du travail d’archivage susmentionné qui suit son cours, nous envisageons également l’écriture d’un texte à plusieurs voix développant des pistes d’analyse de ce matériau archivistique à partir de nos points de vue de parties prenantes aux sensibilités variées."}),(0,dc.jsx)("h2",{id:"h.bm38bbekxtmz",children:"Une écriture collective : remerciements"}),(0,dc.jsx)("p",{children:"Ce site est le résultat d’un processus d’enquête et d’écriture collective qui a mobilisé des personnes issues de plusieurs disciplines : histoire, économie, informatique, géomatique, design. "}),(0,dc.jsxs)("p",{children:["Les textes de cette publication ont été écrits par ",(0,dc.jsx)("a",{className:"c15",href:"https://cmmc-nice.fr/membres-du-cmmc/silvia-marzagalli/",rel:"noopener noreferrer",target:"_blank",children:"Silvia Marzagalli"})," (professeur d’histoire moderne, Université Côte d’Azur - CMMC, coordinatrice et co-responsable scientifique du programme PORTIC), ",(0,dc.jsx)("a",{className:"c15",href:"https://www.ined.fr/fr/recherche/chercheurs/Charles%252BLo%2525C3%2525AFc",rel:"noopener noreferrer",target:"_blank",children:"Loïc Charles"})," (professeur d’économie, INED, Université Paris 8 Vincennes - LED), ",(0,dc.jsx)("a",{className:"c15",href:"https://leda.dauphine.fr/fr/membre/detail-cv/profile/guillaume-daudin.html",rel:"noopener noreferrer",target:"_blank",children:"Guillaume Daudin"})," (professeur d’économie, Université Paris-Dauphine - LEDa-DIAL), ",(0,dc.jsx)("a",{className:"c15",href:"https://criham.labo.univ-poitiers.fr/membres/thierry-sauzeau/",rel:"noopener noreferrer",target:"_blank",children:"Thierry Sauzeau"})," (professeur d’histoire moderne, Université de Poitiers - Criham) et ",(0,dc.jsx)("a",{className:"c15",href:"https://www.cairn.info/publications-de-Pierre-Niccol%25C3%25B2-Sofia--794286.htm",rel:"noopener noreferrer",target:"_blank",children:"Pierre Niccolo’ Sofia"})," (chercheur post-doctoral du programme PORTIC, Université Côte d’Azur - CMMC)."]}),(0,dc.jsxs)("p",{children:["L’ensemble du processus de médiation et d’articulation technique de la collaboration a été conduit par ",(0,dc.jsx)("a",{className:"c15",href:"https://medialab.sciencespo.fr/equipe/robin-de-mourat/",rel:"noopener noreferrer",target:"_blank",children:"Robin de Mourat"})," (designer de recherche permanent, médialab Sciences Po - co-responsable scientifique du programme PORTIC en charge des études de cas), appuyé par ",(0,dc.jsx)("a",{className:"c15",href:"https://fr.linkedin.com/in/paul-girard-57822118",rel:"noopener noreferrer",target:"_blank",children:"Paul Girard"})," (ingénieur expert en humanités numériques - entreprise ",(0,dc.jsx)("a",{className:"c15",href:"https://www.ouestware.com/",rel:"noopener noreferrer",target:"_blank",children:"Ouestware"}),")."]}),(0,dc.jsxs)("p",{children:["Les visualisations ont été conçues et développées par ",(0,dc.jsx)("a",{className:"c15",href:"https://medialab.sciencespo.fr/equipe/robin-de-mourat/",rel:"noopener noreferrer",target:"_blank",children:"Robin de Mourat"})," et ",(0,dc.jsx)("a",{className:"c15",href:"https://fr.linkedin.com/in/paul-girard-57822118",rel:"noopener noreferrer",target:"_blank",children:"Paul Girard"}),"."]}),(0,dc.jsxs)("p",{children:["Les fonds de carte d’époque ont été constitués par ",(0,dc.jsx)("a",{className:"c15",href:"https://lienss.univ-larochelle.fr/Plumejeaud-Christine-954",rel:"noopener noreferrer",target:"_blank",children:"Christine Plumejeaud"}),"."]}),(0,dc.jsxs)("p",{children:["La préparation et la vérification des données a été effectuée par les équipes de Navigocorpus (",(0,dc.jsx)("a",{className:"c15",href:"https://cmmc-nice.fr/membres-du-cmmc/silvia-marzagalli/",rel:"noopener noreferrer",target:"_blank",children:"Silvia Marzagalli"}),", ",(0,dc.jsx)("a",{className:"c15",href:"https://lienss.univ-larochelle.fr/Plumejeaud-Christine-954",rel:"noopener noreferrer",target:"_blank",children:"Christine Plumejeaud"}),", ",(0,dc.jsx)("a",{className:"c15",href:"https://www.cairn.info/publications-de-Pierre-Niccol%25C3%25B2-Sofia--794286.htm",rel:"noopener noreferrer",target:"_blank",children:"Pierre Niccolo’ Sofia"}),") et de Toflit18 (",(0,dc.jsx)("a",{className:"c15",href:"https://leda.dauphine.fr/fr/membre/detail-cv/profile/guillaume-daudin.html",rel:"noopener noreferrer",target:"_blank",children:"Guillaume Daudin"}),", ",(0,dc.jsx)("a",{className:"c15",href:"https://www.ined.fr/fr/recherche/chercheurs/Charles%2BLo%25C3%25AFc",rel:"noopener noreferrer",target:"_blank",children:"Loïc Charles"}),")."]}),(0,dc.jsxs)("p",{children:["Le site a été développé par ",(0,dc.jsx)("a",{className:"c15",href:"https://medialab.sciencespo.fr/equipe/robin-de-mourat/",rel:"noopener noreferrer",target:"_blank",children:"Robin de Mourat"}),", sur la base technique des deux précédentes expérimentations qui avaient été développées avec ",(0,dc.jsx)("a",{className:"c15",href:"https://fr.linkedin.com/in/c%2525C3%2525A9cile-asselin-3659541b7",rel:"noopener noreferrer",target:"_blank",children:"Cécile Asselin"})," en 2021 puis avec ",(0,dc.jsx)("a",{className:"c15",href:"http://www.myllaume.fr/",rel:"noopener noreferrer",target:"_blank",children:"Guillaume Brioudes"})," en 2022."]}),(0,dc.jsxs)("p",{children:["À ces personnes s’ajoutent celles ayant participé au datasprint qui a conduit à cette publication, sans qui cette étude de cas n’aurait pas été possible, et que nous remercions très chaleureusement : les ingénieurs en méthodes numériques du laboratoire médialab de Sciences Po ",(0,dc.jsx)("a",{className:"c15",href:"https://medialab.sciencespo.fr/equipe/diego-antolinos-basso/",rel:"noopener noreferrer",target:"_blank",children:"Diégo Antolinos-Basso"}),", ",(0,dc.jsx)("a",{className:"c15",href:"https://medialab.sciencespo.fr/equipe/ines-girard/",rel:"noopener noreferrer",target:"_blank",children:"Inès Girard"}),", ",(0,dc.jsx)("a",{className:"c15",href:"https://medialab.sciencespo.fr/equipe/kelly-christensen/",rel:"noopener noreferrer",target:"_blank",children:"Kelly Christensen"}),", ",(0,dc.jsx)("a",{className:"c15",href:"https://bmaz.github.io/",rel:"noopener noreferrer",target:"_blank",children:"Béatrice Mazoyer"})," et ",(0,dc.jsx)("a",{className:"c15",href:"https://medialab.sciencespo.fr/equipe/benjamin-ooghe-tabanou/",rel:"noopener noreferrer",target:"_blank",children:"Benjamin Ooghe-Tabanou"}),"."]})]})}function lN(e){return(0,dc.jsx)("div",{id:"part-6",children:(0,dc.jsx)("p",{children:"."})})}function uN(e){return(0,dc.jsxs)("div",{id:"part-7",children:[(0,dc.jsx)("h2",{id:"h.cbk6c4v18uxg",children:"Sources"}),(0,dc.jsxs)("p",{children:["Base de données Navigocorpus - Portic: voir ",(0,dc.jsx)("a",{className:"c15",href:"https://anr.portic.fr/",rel:"noopener noreferrer",target:"_blank",children:"https://anr.portic.fr/"})," "]}),(0,dc.jsxs)("p",{children:["Toflit18: voir ",(0,dc.jsx)("a",{className:"c15",href:"https://toflit18.medialab.sciences-po.fr/#/home",rel:"noopener noreferrer",target:"_blank",children:"https://toflit18.medialab.sciences-po.fr/#/home"})," "]}),(0,dc.jsx)("p",{children:"Baehrel René, Une croissance : la Basse-Provence rurale de la fin du seizième siècle à 1789 essai d'économie historique statistique, Paris, éditions de l’EHESS, 2 vols, 1988 (1ère édition, 1959)."}),(0,dc.jsx)("p",{children:"Carrière Charles, Négociants marseillais au XVIIIe siècle. Contribution à l'étude des économies maritimes, Marseille, Institut historique de Provence, 1973, 2 tomes."}),(0,dc.jsx)("p",{children:"Carrière Charles et Coudurié Marcel, « L’espace commercial marseillais aux XVIIe et XVIIIe siècles », dans Pierre Léon (dir.), Aires et structures du commerce français au XVIIIe siècle. Colloque national de l’AFHE, Paris, CNRS, 4-6 octobre 1973, Lyon, Centre d'histoire économique et sociale de la région lyonnaise, 1975, p. 75-106."}),(0,dc.jsx)("p",{children:'Federico, G., Schulze, M. S., & Volckart, O. (2021). "European goods market integration in the very long run: from the Black Death to the First World War." The Journal of Economic History, 81(1), 276-308.'}),(0,dc.jsx)("p",{children:"Romano Ruggiero, Commerce et prix du blé à Marseille au XVIIIe siècle, Paris, Armand Colin, 1956."}),(0,dc.jsx)("p",{children:"Les sources archivistiques ont été indiquées directement dans le corps du texte et dans l’annexe."}),(0,dc.jsx)("h2",{id:"h.bxam7tthku9i",children:"Références bibliographiques"}),(0,dc.jsx)("p",{children:"ABÉNON, Lucien-René, « Marseille et les îles au XVIIIe siècle », dans Jean-René Gaborit, Circulation des matières premières en Méditerranée : transferts de savoirs et de techniques. Actes du 128e Congrès national des sociétés historiques et scientifiques, « Relations, échanges et coopération en Méditerranée », Bastia, 2003, Paris, Editions du CTHS, 2009, p. 7-15."}),(0,dc.jsx)("p",{children:"ANDERSEN, Dan, The Danish Flag in the Mediterranean. Shipping and Trade, 1747-1807, Ph.D. thesis, University of Copenhagen, 2000."}),(0,dc.jsx)("p",{children:"BAEHREL, René, Une croissance : la Basse-Provence rurale de la fin du seizième siècle à 1789 essai d'économie historique statistique, Paris, éditions de l’EHESS, 2 vols, 1988 (1ère édition, 1959). "}),(0,dc.jsx)("p",{children:"BOUBAKER, Sadok, La régence de Tunis au XVIIe siècle ses relations commerciales avec les ports de l'Europe méditerranéenne, Marseille et Livourne, Zaghouan, Ceroma, 1987."}),(0,dc.jsx)("p",{children:"BOULANGER, Patrick, « Le commerce maritime des huiles durant les guerres de la seconde moitié du XVIIIe siècle », dans Michel Vergé-Franceschi (dir.), Guerre et commerce en Méditerranée IXe-XXe siècles, Paris, Éditions Veyrier, 1991, p. 235-253."}),(0,dc.jsx)("p",{children:"BOULANGER, Patrick, Marseille, marché international de l'huile d'olive, Marseille, Institut historique de Provence, 1996."}),(0,dc.jsx)("p",{children:"BUTEL, Paul, « France, the Antilles, and Europe in the seventeenth and eighteenth centuries : renewals of foreign trade », dans James D. Tracy (dir.), The Rise of Merchant Empires. Long-Distance Trade in the Early Modern World, 1350-1750, New York, Cambridge University Press, 1990, p. 153-173."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, « Aller en caravane : le cabotage lointain en Méditerranée, XVIIe et XVIIIe siècle », Revue d’histoire moderne et contemporaine, n°52-1, 2005, p. 7-38."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, « Marseille, port négrier au XVIIIe siècle », Cahiers des Anneaux de la Mémoire, n°11, 2007, p. 163-178."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, « Expédier à la côte et aller à la cueillette : le cabotage en Méditerranée aux XVIIe et XVIIIe siècles », Revue d’Histoire maritime, n°8, 2008, p.67-108."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, « Commerce honteux pour négociants vertueux à Marseille au xviiie siècle ? », dans Éric Saunier (dir.), Cahiers de l’histoire et des mémoires de la traite négrière, de l’esclavage et de leurs abolitions, n° 1, 2008, p. 199-219."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert. Les chemins de la mer : Saint-Tropez : petit port méditerranéen (XVIIe-XVIIIe siècles), Rennes, PUR, 2010."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, « Marseille, la péninsule ibérique et les empires américains (1659-1793) : ‘Le soleil des profits se lève aussi à l’Ouest’ », Revue d’Histoire maritime, n° 13, 2011, p. 211-232."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, « Négociants d’expression allemande à Marseille (1750-1793) », Cahiers de la Méditerranée, n°84, 2012, p. 49-64."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, JANIN-THIVOS, Michèle, RAVEUX, Olivier (dir.). Langues et langages du commerce en Méditerranée et en Europe à l’époque moderne, Aix-en-Provence, Presses universitaires de Provence, 2013."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, « Une maison de négoce à Marseille au xviiie siècle : les Roux frères », Patrimoines du Sud (en ligne), n°13, 2021."}),(0,dc.jsx)("p",{children:"CALCAGNO, Paolo, « Uno dei ‘Tirreni’ di Braudel : scambi commerciali nell’area marittima ligure-provenzale tra XVII e XVIII secolo », Mediterranea-ricerche storiche, n°33, avril 2015, p. 79-106."}),(0,dc.jsx)("p",{children:"CARASSALE, Alessandro, LO BASSO, Luca, Sanremo, giardino di limoni. Produzione e commercio degli agrumi dell’estremo Ponente ligure (secoli XII-XIX), Rome, Carocci, 2008."}),(0,dc.jsx)("p",{children:"CARRIÈRE Charles, Négociants marseillais au XVIIIe siècle. Contribution à l'étude des économies maritimes, Marseille, Institut historique de Provence, 1973, 2 tomes."}),(0,dc.jsx)("p",{children:"CARRIÈRE, Charles, COURDURIÉ, Marcel « L’espace commercial marseillais aux XVIIe et XVIIIe siècles », dans Pierre Leon (dir.), Aires et structures du commerce français au XVIIIe siècle. Colloque national de l’AFHE, Paris, CNRS, 4-6 octobre 1973, Lyon, Centre d'histoire économique et sociale de la région lyonnaise, 1975, p. 75-106."}),(0,dc.jsx)("p",{children:"CARRIÈRE, Charles, Richesse du passé marseillais. Le port mondial au XVIIIe siècle, Marseille, C.C.I.M., 1979."}),(0,dc.jsx)("p",{children:"CARRIÈRE, Charles, COURDURIÉ, Marcel, « Un sophisme économique : Marseille s'enrichit en achetant plus qu'elle ne vend. (Réflexions sur les mécanismes commerciaux levantins au XVIIIème siècle) », Histoire, Économie et Société, vol. 3, 1er trimestre 1984, p. 7-51."}),(0,dc.jsx)("p",{children:"COLLETTA, Teresa (dir.), Città portuali del Mediterraneo. Luoghi dello scambio commerciale e colonie di mercanti stranieri tra Medioevo e età moderna, Milano, Franco Angeli, 2012."}),(0,dc.jsx)("p",{children:'CONAN, J. "La dernière compagnie française des Indes: La compagnie dans l’Inde (suite), Revue d’Histoire Économie et Sociale, 25 n°2, 1939. p. 159–85'}),(0,dc.jsx)("p",{children:'DAUDIN, Guillaume et PIGNEDE, Edouard, "Le commerce de la France au XVIIIe : inflation et révolution", Dialogue, n°62, 2021.'}),(0,dc.jsx)("p",{children:'DERMIGNY, Louis, Cargaisons Indiennes Soliers et Cie, 1781-1793, Série "Affaires et Gens d’Affaires XV", Paris, S.E.V.P.E.N, 1959-1960, 2 tomes'}),(0,dc.jsx)("p",{children:"DUMOND, Lionel, DURAND, Stéphane, THOMAS, Jérôme (dir), Les ports dans l’Europe méditerranéenne : Trafics et circulation, Images et représentations (XVIe-XXe siècle), Actes du colloque tenu à Montpellier les 19 et 20 mars 2004 en hommage à Louis Dermigny (1916-1974), Presses Universitaires de la Méditerranée, Montpellier, 2007."}),(0,dc.jsx)("p",{children:"ELDEM, Edhem, « French Trade and Commercial Policy in the Levant in the Eighteenth-Century », Oriente Moderno, Nuova serie, n°79, 1999, p. 27-47."}),(0,dc.jsx)("p",{children:"ELDEM, Edhem, « Capitulations and Western trade », dans Suraiya Faroqhi (dir.), The Cambridge History of Turkey: The Later Ottoman Empire, 1603-1839, Cambridge, Cambridge University Press, 2006, p. 283-335."}),(0,dc.jsx)("p",{children:"EMMANUELLI, François-Xavier, La Crise marseillaise de 1774 et la chute des courtiers. Contribution à l'histoire du commerce du Levant et de la banque, Marseille, Éditions du Centre national de la recherche scientifique, 1979."}),(0,dc.jsx)("p",{children:"FARGANEL, Jean-Pierre, « Les échelles du Levant dans la tourmente des conflits méditerranéens au XVIIIe siècle : la défense des intérêts français au fil du temps », Cahiers de la Méditerranée, n°70, 2005, p. 61-83."}),(0,dc.jsx)("p",{children:'FEDERICO, G., SCHULZE, M. S., & VOLCKART, O., "European goods market integration in the very long run: from the Black Death to the First World War", The Journal of Economic History, 81(1), 2021, p. 276-308.'}),(0,dc.jsx)("p",{children:"FIGEAC-MONTHUS, Marguerite, LASTÉCOUÈRES, Christophe (dir.), Territoires de l'illicite: ports et îles. De la fraude au contrôle (XVIe-XXe s.), Paris, Armand Colin, 2012."}),(0,dc.jsx)("p",{children:"FILIPPINI, Jean-Pierre, et alii (dir.), Dossier sur le commerce français dans la Méditerranée orientale au XVIIIe siècle, Paris, Presses Universitaires de France, 1976."}),(0,dc.jsx)("p",{children:"FÖLSCH, François Philippe, L'oeil de Stockholm : la correspondance du consul François Philippe Fölsch à Marseille (1780-1807), Pari, Classiques Garnier, 2021, ed. par BEAUREPAIRE, Pierre-Yves, MARZAGALLI, Silvia, THOMASSON, Thomasson."}),(0,dc.jsx)("p",{children:"FRANGAKIS-SYRETT, Elena, The Commerce of Smyrna in the Eighteenth Century (1700-1820), Athens, Center for Asia Minor Studies, 1992."}),(0,dc.jsx)("p",{children:"FUKASAWA, Katsumi, Toilerie et commerce du Levant, d’Alep à Marseille, Paris, Editions du CNRS, 1985."}),(0,dc.jsx)("p",{children:"GALANI, Katerina, British Shipping and Trade in the Mediterranean in the Age of War, 1770-1815, Phd thesis, University of Oxford, 2010."}),(0,dc.jsx)("p",{children:"GODECHOT, Jacques, « La France et les problèmes de l’Atlantique à la veille de la Révolution », Revue du Nord, n°142, 1954, p. 231-244."}),(0,dc.jsx)("p",{children:"HILDESHEIMER, Françoise, Le Bureau de la santé de Marseille sous l'Ancien régime. Le renfermement de la contagion, Marseille, Fédération historique de Provence, 1980."}),(0,dc.jsx)("p",{children:"HORN, Jeff, « Marseille et la Question du mercantilisme : privilège, liberté et économie politique en France, 1650-1750 », Histoire, économie & société, 30e année, 2012, p. 95-111."}),(0,dc.jsx)("p",{children:"JUILLIANY, Essai sur le Commerce de Marseille, 2e édition, 1842,"}),(0,dc.jsx)("p",{children:"LARGUIER, Gilbert (dir.), Les hommes et le littoral autour du golfe du Lion (XVIe-XVIIIe siècle), Presses Universitaires de Perpignan, Perpignan, 2012."}),(0,dc.jsx)("p",{children:"LE BOUËDEC, Gérard, « L’État et le cabotage en France et en Europe aux XVIIe-XVIIIe siècles » dans Le Bouëdec Gérard, Chappé François, Cérino Christophe (dir.), Pouvoirs et littoraux du XVe au XXe siècle, Rennes, PUR, 2000, p. 383-394."}),(0,dc.jsx)("p",{children:"LE GOUIC, Olivier. Lyon et la mer au XVIIIe siècle: Connexions atlantiques et commerce colonial, Rennes, Presses universitaires de Rennes, 2011."}),(0,dc.jsxs)("p",{children:["LEGAY, Marie-Laure, « Marseille » (2023) dans Legay Marie-Laure, Boullu Thomas (dir.), Dictionnaire Numérique de la Ferme générale, ",(0,dc.jsx)("a",{className:"c15",href:"https://fermege.meshs.fr",rel:"noopener noreferrer",target:"_blank",children:"https://fermege.meshs.fr"})]}),(0,dc.jsx)("p",{children:"LOPEZ, Olivier, S'établir et travailler chez l’autre. La Compagnie royale d’Afrique et ses hommes, Paris, Classiques Garnier, 2019."}),(0,dc.jsx)("p",{children:"LO BASSO, Luca, « Il Sud dei Genovesi. Traffici marittimi e pratiche mercantili tra l’Italia meridionale, Genova e Marsiglia nel Settecento », dans Biagio Salvemini (dir.), Lo spazio tirrenico nella « Grande Trasformazione ». Merci, uomini e istituzioni nel Settecento e nel primo Ottocento, Bari, Edipuglia, 2009, p. 239-263."}),(0,dc.jsxs)("p",{children:["MARZAGALLI, Silvia, PFISTER-LANGANAY, Christian, « L",(0,dc.jsx)("a",{className:"c15",href:"https://journals.openedition.org/cdlm/6284?lang%3Dfr",rel:"noopener noreferrer",target:"_blank",children:"a navigation des ports français en"})," Méditerranée au XVIIIe siècle : premiers aperçus à partir d’une source inexploitée », Cahiers de la Méditerranée, n°83, 2011, p. 273-295."]}),(0,dc.jsx)("p",{children:"MARZAGALLI, Silvia, « L’apport des cahiers du petit cabotage à la connaissance du commerce et de la navigation de Marseille à la fin du XVIIIe siècle »,  Cahiers de la Méditerranée, n° 108, juin 2024, p. 33-50. "}),(0,dc.jsx)("p",{children:"MEYER, Jean, « La France maritime au XVIIIe siècle. Aspects chronologiques », dans Jean Bérenger, Jean Meyer (dir.), La France dans le monde au XVIIIe siècle, Paris, Sedes, 1993, p. 269-288."}),(0,dc.jsx)("p",{children:"MIÈGE, Jean-Louis (dir.), Les céréales en Méditerranée, Histoire, Anthropologie, Économie, Paris, CNRS Éditions, 1994."}),(0,dc.jsx)("p",{children:"PANZAC, Daniel, La caravane maritime : marins européens et marchands ottomans en Méditerranée (1680-1830), Paris, CNRS Éditions, 2004"}),(0,dc.jsx)("p",{children:"PARIS, Robert, Histoire du commerce de Marseille. Tome V. De 1660 à 1789. Le Levant, Paris, Plon, 1957."}),(0,dc.jsx)("p",{children:"PAYN-ECHALIER, Patricia, « Entre Rhône et Méditerranée : la marine d’Arles au service d’un petit cabotage polyvalent (XVIe-XVIIIe siècles) », Rives méditerranéennes, n°13, 2003, p. 59-73."}),(0,dc.jsx)("p",{children:"PAYN-ECHALIER, Patricia, « Entre fleuve et mer, le port d’Arles et le delta du Rhône (XVIe-XVIIIe siècle) », Rives méditerranéennes, n°35, 2010, p. 29-44."}),(0,dc.jsx)("p",{children:"RAMBERT, Gaston, Histoire du commerce de Marseille, tomes IV, VI-VII, Paris, Plon, 1954-1966."}),(0,dc.jsx)("p",{children:"ROMANO, Ruggiero, Commerce et prix du blé à Marseille au XVIIIe siècle, Paris, A. Colin, 1956."}),(0,dc.jsx)("p",{children:"SALVEMINI, Biagio (dir.), Lo spazio tirrenico nella ‘grande trasformazione’. Merci, uomini e istituzioni nel Settecento e nel primo Ottocento, Atti del Convegno Internazionale di Bari, 17-18 novembre 2006, Bari, Edipuglia, 2009."}),(0,dc.jsx)("p",{children:'SOFIA, Pierre Niccolò, "C’est toute une question de jauge. Méthode, défis, incertitudes et résultats de l’estimation de la portée des navires du commerce marseillais au xviiie siècle", Cahiers de la Méditerranée, 106, 2024, p. 13-31.'}),(0,dc.jsx)("p",{children:"TAKEDA, Junko Thérése, Between crown and commerce Marseille and the early modern Mediterranean, Baltimore, Johns Hopkins University Press, 2011."}),(0,dc.jsx)("p",{children:"UNGER, Richard W. 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Si la résilience de l’estuaire de la Seine s’explique d’abord par l’importance et le dynamisme du bassin économique et démographique parisien, dans le cas de Marseille les causes sont plus complexes. Charles Carrière, auteur il y a cinquante ans d’une étude incontournable sur le négoce de Marseille au XVIIIe siècle (Carrière, 1973), associait la croissance économique et la force du port à son intégration progressive à l’économie de l’Atlantique. Après la guerre de Succession d’Espagne (1701-1713/14), les ports de la façade atlantique (Bordeaux, La Rochelle et Nantes notamment) connaissent une forte croissance liée au premier empire colonial français. Mais cette croissance est fragile car elle dépend principalement du commerce colonial et de la traite des esclaves. La perte de Saint-Domingue (devenue indépendante sous le nom d'Haïti en 1804) et l’interdiction de la traite Atlantique par le Parlement anglais en 1807 détruisent les bases du commerce colonial antillais. Les ports qui en tiraient leur dynamisme et en particulier le premier d’entre eux, Bordeaux, seront cantonnés au XIXe siècle à un rôle secondaire. À l’inverse, Marseille survit au choc des guerres révolutionnaires et napoléoniennes et à leurs conséquences. Cette résilience repose sur des caractéristiques qui lui sont spécifiques et qui s’inscrivent dans le temps long."}),(0,dc.jsxs)("p",{children:["Port marchand par tradition, Marseille est la première ville française à accueillir une chambre de commerce en 1599. Elle connaît une expansion commerciale régulière à partir de la seconde moitié du XVIIe siècle. Cette expansion se nourrit de l'intensification de ses échanges avec ses partenaires méditerranéens, notamment le Levant",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Le terme désigne alors l’Empire ottoman, en particulier sa partie orientale qui comprend la péninsule des Balkans, la Turquie actuelle, le Proche Orient, ainsi que l’Egypte et la Libye. Le Maghreb actuel qui est également sous le contrôle de l’Empire ottoman au XVIIIe siècle est souvent désigné par le terme de «Barbarie».",children:"?"}),". Le privilège obtenu par le port au début du règne personnel de Louis XIV va la renforcer. En effet, l’édit de mars 1669 supprime la plupart des taxes portant sur le commerce marseillais avec le Levant et établit simultanément un droit unique de 20% sur les marchandises du Levant apportées à Marseille par des étrangers. En 1685, le port phocéen obtient une franchise totale, alors que les marchandises levantines débarquées dans tous les autres ports français doivent payer un droit de 20%. Le privilège est ensuite confirmé en 1703 et se maintient jusqu’à la Révolution. Le port phocéen obtient ainsi le monopole de facto sur le commerce français avec le Levant. À partir de 1703, une barrière douanière sépare la ville du reste du royaume, consacrant la franchise du port de Marseille. Malgré le coup d’arrêt de la peste de 1720, il est le premier port français dans la première moitié du XVIIIe siècle. Le statut de port franc de Marseille a ensuite été étendu au commerce colonial par les lettres patentes de 1779 qui lui octroient la liberté du commerce avec les colonies françaises, sous condition d’accepter le régime d’entrepôt. Marseille bénéficie donc tout au long du XVIIIe siècle d’importants privilèges commerciaux qui soutiennent son expansion."]}),(0,dc.jsx)("p",{children:"La situation géographique de Marseille s’est avérée particulièrement avantageuse au XVIIIe siècle. Située à mi-chemin entre Cadix, la côte Atlantique et le Levant, la ville est un centre majeur de transit pour les textiles du Languedoc, ainsi que pour la cochenille et les piastres en provenance de l’Empire espagnol (via Cadix) vers l’Empire ottoman. Vers l’Ouest, le port est un centre de tout premier rang pour l’exportation des produits méditerranéens (huile d’olive, savon, etc.) vers les colonies atlantiques et vers l’Europe du Nord. De plus, Marseille a pu exploiter sa situation à l’embouchure du Rhône, qui en fait le point d’accès non seulement vers la Provence, mais aussi vers la région lyonnaise au Nord et le Languedoc à l’ouest. C’est ainsi que Marseille, importateur structurel de blé pour alimenter son hinterland, est devenu dès les années 1730 le hub céréalier de toute la Méditerranée, symétrique d’Amsterdam pour l’Europe du Nord-Ouest. De manière plus générale, le poids démographique de l’hinterland de Marseille n’a d’équivalent que celui de Rouen-Le Havre, ce dernier étant toutefois plus dynamique dans la seconde moitié du XVIIIe siècle. Outre ces avantages géographiques structurants, d’autres éléments ont pu contribuer à solidifier la place de Marseille dans le temps:"}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"Le statut de port franc et la domination commerciale de Marseille sur l’espace méditerranéen ont favorisé la constitution de communautés marchandes (Arméniens, Suisses, Italiens, etc.) ou la présence des commissionnaires étrangers. "}),(0,dc.jsx)("li",{children:"La plus grande diversité des acteurs (mesurée dans cette étude à partir des pavillons des navires) a pu compenser en partie au moins une conjoncture défavorable."}),(0,dc.jsx)("li",{children:"De même, une plus grande diversité des marchés nationaux et internationaux qui va de pair avec une gamme plus large de productions a pu contribuer à la résilience marseillaise. Ainsi, la non-participation au commerce de la traite a paradoxalement contribué à protéger l’économie marseillaise des effets de sa disparition en 1793. "}),(0,dc.jsx)("li",{children:"Une plus grande résilience aux guerres liée au plus faible contrôle de la Méditerranée par les Anglais et la présence de transporteurs neutres italiens, si elle était avérée, pourrait également être un facteur de continuité de l’activité marchande sur la longue période (voir partie III de cette étude)."}),(0,dc.jsx)("li",{children:"Enfin, la co-présence/superposition des trafics et des logiques différentes (spatiales et temporelles) ont pu donner une plus grande souplesse à l’ensemble."})]})]})}const wN=function(e={}){const{wrapper:t}=e.components||{};return t?(0,dc.jsx)(t,Object.assign({},e,{children:(0,dc.jsx)(xN,e)})):xN()};function _N(e){return(0,dc.jsxs)("div",{id:"part-0",children:[(0,dc.jsx)("p",{children:'Deux ports français qui survivent au XIXe : Marseille et l’ensemble Rouen-Le Havre. La dynamisme de l’estuaire de la Seine s’explique facilement par l’industrialisation et la proximité de Paris. Quelle est l’explication de la force de Marseille ? Vient-elle, comme l’affirme Carrière, de la force de la croissance du XVIIIe tirée par l’intégration à l’économie Atlantique ? (Réponse : non. "Marseille, port traditionnel et méditerranéen).'}),(0,dc.jsx)("h2",{id:"h.o25rt55n14tq",children:"A. Marseille en 1789, un port international"}),(0,dc.jsx)("p",{children:"Marseille en 1789: Les échanges de Marseille en 1789 restent principalement tournés vers l’espace méditerranéen - ses deux partenaires privilégiés étant l’Italie et le Levant (l’empire Ottoman). Toutefois, à la veille de la Révolution, Marseille a développé des liens économiques et commerciaux avec des espaces lointains, les colonies antillaises et, dans une moindre mesure, le Nord de l’Europe, l’océan indien et les Etats-Unis. Le port de Marseille est un port international que les avantages en termes de localisation, ont permis à son personnel négociant et à ses capitalistes de développer leurs activités à l’interconnexion de son espace commercial traditionnel - la Méditerranée - et de la zone la plus dynamique - l’espace Atlantique."}),(0,dc.jsx)("p",{children:"Titre : (carte de Paul&co) Carte de la valeur des importations et des exportations de Marseille en 1789. Légende: La taille du cercle est proportionnelle à la valeur, la couleur indique si la balance commerciale est favorable (vert) ou défavorable (rouge) à Marseille."}),(0,dc.jsx)("p",{children:"Les données relatives aux arrivées de navires confirment pour l’essentiel les données de la balance du commerce: elles montrent la part toujours dominante du trafic méditerranéen issu d’Italie, du Levant et d’Espagne pour Marseille. "}),(0,dc.jsx)("p",{children:"Données Navigo, code : moduleA_navigo_1789 "}),(0,dc.jsx)("p",{children:"Titre : Arrivées de navires à Marseille en 1789 (santé + cabotages, en excluant les doublons Q) "}),(0,dc.jsx)("h2",{id:"h.qb9ge46p8sqw",children:"B. Marseille premier (ou presque) port de France"}),(0,dc.jsx)("p",{children:"En 1789, Marseille est le deuxième port français en termes de valeur de commerce derrière Bordeaux. Il lui est même légèrement supérieur en ce qui concerne les importations, mais Bordeaux le dépasse largement en ce qui concerne les exportations. "}),(0,dc.jsx)("p",{children:"Toutefois, la supériorité de Bordeaux est fragile puisqu’elle dépend largement de sa spécialisation dans le commerce colonial et la traite des esclaves; ce qui apparaît lorsqu’on considère la balance à l’exclusion de ces deux commerces (voir graphiques ci-dessous). De ce fait, la fermeture de ces deux commerces à partir de de 1793 sera une véritable catastrophe pour Bordeaux, alors que Marseille fait partie des rares ports français à survivre au choc révolutionnaire. "}),(0,dc.jsx)("p",{children:"En nombre de congés, c’est-à-dire des autorisations obligatoires de sortie de tout port français (parfois valables pour une année quelque soit le nombre d’allers-retours), Marseille vient largement en tête en 1789. "}),(0,dc.jsx)("p",{children:"Le nombre des congés étant un indicateur très approximatif car il additionne des navires de portée très différente, il serait souhaitable de comparer les tonnages. Or, ceux-ci sont connus en 1787 dans la plupart des ports français grâce aux congés. Nous ne disposons en revanche pas de l’indication des tonnages sortis de Marseille. Nous avons donc procédé à une estimation des tonnages entrés à partir du type de navire signalés par les registres des dépositions des capitaines et des cahiers du petit cabotage en 1787, afin de pouvoir la comparer avec les tonnages agrégés des autres ports français. Comme le nombre d’entrées à Marseille est supérieur de 17.6% au nombre des congés, une fois ôtés les navires en relâche, nous avons déflaté le tonnage estimé de ce même facteur, puis refait le calcul en supposant que les navires dépourvus de congés soient ceux qui effectuent du cabotage de port en port au sein de la Provence [voir Chardon]. La comparaison entre les tonnages estimés supposés entrés à Marseille montre encore une fois la primauté de la navigation de ce port."}),(0,dc.jsx)("p",{children:"Si on se penche sur la valeur du commerce, Marseille vient en tête. "}),(0,dc.jsx)("p",{children:"Marseille est donc un des deux ports les plus importants en 1789. Sa participation dans le système colonial est moins forte que celle de Bordeaux : il est le premier port européen (et levantin) français."}),(0,dc.jsx)("h2",{id:"h.9aefnfi0kgry",children:"C. La croissance marseillaise (À déplacer I.A )"}),(0,dc.jsx)("p",{children:"Objectif : Montrer l'évolution au XVIIIe siècle, voir quels sont les points de flexion par rapport aux autres grands ports. "}),(0,dc.jsx)("p",{children:"Carrière affirme que cette importance de Marseille en 1789 vient d’une croissance soutenue durant le siècle. Nous montrons ici que cette croissance n’est pas exceptionnelle : Marseille est important en 1789 parcequ’il était déjà important en 1740."}),(0,dc.jsx)("p",{children:"La situation de Marseille à l’aube de la révolution française s’inscrit dans une tendance de long-terme. Ville marchande par tradition, elle est la première à accueillir une chambre de commerce, dès 1599, elle connaît une expansion commerciale régulière à partir de la fin du XVIIe siècle. Elle se nourrit, dans un premier temps, de l'approfondissement de ses échanges avec la Méditerranée, notamment le Levant pour lequel elle obtient un privilège en 1700. Marseille devient, malgré le coup d’arrêt de la peste de 1720, le premier port français dans la première moitié du XVIIIe siècle. Les exportations de textile à destination du Levant connaissant une certaine stagnation à partir des années 1750, puis une baisse sensible dans les années 1770, la place relative de Marseille recule au profit de Bordeaux. Toutefois, le trafic de Marseille continue de progresser, tiré par les exportations coloniales. On remarque que la baisse relative de Marseille est plus marquée pour les exportations que pour les importations - Marseille approvisionnant un hinterland important (la Provence, la Vallée du Rhône et le sud-est)."}),(0,dc.jsx)("p",{children:"Titre: Comparaison du commerce total par direction de ferme pour les années dispos dans TOFLIT18."}),(0,dc.jsx)("p",{children:"Titre: Comparaison du montant des importations par direction de ferme "}),(0,dc.jsx)("p",{children:"comparaison des exports"}),(0,dc.jsx)("p",{children:"L’analyse de la tendance de la croissance des principales régions française vient renforcer l’idée que Marseille était un port important au début de la période et que sa position s’est légèrement dégradée au cours du siècle au bénéfice de Bordeaux."}),(0,dc.jsx)("p",{children:"Nous ne disposons pas de l’indication des tonnages sortis de Marseille. Nous avons donc procédé à une estimation des tonnages entrés à partir du type de navire signalés par les registres des dépositions des capitaines et des cahiers du petit cabotage en 1787, afin de pouvoir la comparer avec les tonnages agrégés des autres ports français. Comme le nombre d’entrées à Marseille est supérieur de 17.6% au nombre des congés, une fois ôtés les navires en relâche, nous avons déflaté le tonnage estimé de ce même facteur, puis refait le calcul en supposant que les navires dépourvus de congés soient ceux qui effectuent du cabotage de port en port au sein de la Provence [voir enquête Chardon]. La comparaison entre les tonnages estimés supposés entrés à Marseille montre encore une fois la primauté de la navigation de ce port."}),(0,dc.jsx)("p",{children:"Les données de la navigation reposent sur deux sources de nature différente: pour ce qui est de sorties, nous disposons du nombre des congés délivrés. Pour les entrées, il s’agit des dépositions des capitaines au bureau de la Santé qui ne comprennent pas toutes les entrées. La navigation dite du petit cabotage - celle provenant d’une aire comprise entre la Catalogne et la Toscane, Corse incluse, ne transportant pas de passagers ou d’autres produits spécifiques, et n’ayant pas fait de rencontres en mer avec des corsaires - est en effet enregistrée à part. En dépit de ces différences, la corrélation de deux courbes est la même (taux de corrélation = 0.89) entre 1732 et 1780."}),(0,dc.jsx)("p",{children:"Le nombre des congés délivrés à Marseille montre une nette croissance dans les années 1740 (et ce, en dépit de la guerre de succession d’Autriche) et une reprise au lendemain de la guerre de Sept Ans sur des niveaux nettement plus élevés qu’avant ce conflit. La crise financière liée aux faillites en chaîne des courtiers en 1774, très visible, est de courte durée. "}),(0,dc.jsx)("p",{children:"Le port accroît son commerce au XVIIIe siècle en élargissant sa géographie commerciale vers l’Atlantique et l’océan Indien, tout en gardant une position de force dans les marchés méditerranéens et notamment levantins. "}),(0,dc.jsx)("p",{children:"Ce succès marseillais a été traditionnellement attribué soit à une série de privilèges octroyés au port depuis le règne de Louis XIV, soit au dynamisme de son négoce. Marseille a en effet obtenu le statut de port franc (expliquer). "}),(0,dc.jsx)("p",{children:"Nous explorons ici les hypothèses suivantes : "}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"des avantages institutionnels (monopole sur le Levant) qui se combinent avec des avantages géographiques (présence des textiles du Languedoc, liens avec Cadix- cochenille, argent) ? "}),(0,dc.jsx)("li",{children:"des avantages économiques liés à son hinterland: importateur structurel de blé, Lyon/Rhone (marché bancaire/monétaire pour l’argent espagnol/capitaux marseillais-Cadix, soieries et dentelles du Puy, textiles du Languedoc, industrie pharmaceutique, produits méditerranéens) "}),(0,dc.jsx)("li",{children:"une plus grande diversité des marchés nationaux et internationaux qui va de pair avec une gamme plus large de productions ?"}),(0,dc.jsx)("li",{children:"une plus grande participation d’acteurs (pavillons) différents occupant des secteurs du marché différenciés en compensant ainsi des conjonctures défavorables (crises productives, guerre)."}),(0,dc.jsx)("li",{children:"une plus grande résilience aux guerres liée au manque de contrôle de la Méditerranée par les anglais et la présence de neutres italiens ? définir résilience"}),(0,dc.jsx)("li",{children:"une co-présence/superposition des trafics et des logiques différentes (spatiales et temporelles) qui donnent in fine une plus grande souplesse à l’ensemble"})]}),(0,dc.jsx)("p",{children:"Conclusion de l’introduction."})]})}const MN=function(e={}){const{wrapper:t}=e.components||{};return t?(0,dc.jsx)(t,Object.assign({},e,{children:(0,dc.jsx)(_N,e)})):_N()},VN=JSON.parse('{"fr":{"title":"Prospérité et résilience du port de Marseille au XVIIIe siècle"},"en":{"title":"Case study Marseille - document de rédaction en anglais"}}');var kN=i(7902),jN={};jN.styleTagTransform=_v(),jN.setAttributes=yv(),jN.insert=gv().bind(null,"head"),jN.domAPI=Cv(),jN.insertStyleElement=xv(),fv()(kN.A,jN),kN.A&&kN.A.locals&&kN.A.locals;const HN=({width:e,height:t,hourOfTime:n,hourDuration:r})=>{const i=.7*e,a=.05*e,o=ln().domain([0,12]).range(["darkgrey","black"])(Math.abs(12-n)),{fill:s}=Im({to:{fill:o},config:{duration:r}});return(0,dc.jsx)(ig.path,{className:"hull",style:{fill:s},d:`M 0 0 L ${e/3} 0 L ${e/3} ${t/4} L ${.6*e} ${t/4} L ${.6*e} 0 L ${e} 0 L ${i} ${t} L ${a} ${t} 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LC(d,u),f=(0,r.useRef)();dC((()=>(f.current=p,Uf(u,(e=>Wh(e,p))),()=>{f.current&&(Uf(f.current.deps,(e=>Gh(e,f.current))),Mf.cancel(f.current.update))}))),(0,r.useEffect)(d,[]),hC((()=>()=>{const e=f.current;Uf(e.deps,(t=>Gh(t,e)))}));const h=t.getComponentProps(l.getValue());return r.createElement(e,{...h,ref:s})}))},LC=class{constructor(e,t){this.update=e,this.deps=t}eventObserved(e){"change"==e.type&&Mf.write(this.update)}},SC=Symbol.for("AnimatedComponent"),PC=e=>Bf.str(e)?e:e&&Bf.str(e.displayName)?e.displayName:Bf.fun(e)&&e.name||null;function AC(e,...t){return Bf.fun(e)?e(...t):e}var TC=(e,t)=>!0===e||!!(t&&e&&(Bf.fun(e)?e(t):Gf(e).includes(t))),NC=(e,t)=>Bf.obj(e)?t&&e[t]:e,OC=(e,t)=>!0===e.default?e[t]:e.default?e.default[t]:void 0,qC=e=>e,IC=(e,t=qC)=>{let n=RC;e.default&&!0!==e.default&&(e=e.default,n=Object.keys(e));const r={};for(const i of n){const n=t(e[i],i);Bf.und(n)||(r[i]=n)}return 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WC={tension:170,friction:26,mass:1,damping:1,easing:Ih.linear,clamp:!1},GC=class{constructor(){this.velocity=0,Object.assign(this,WC)}};function XC(e,t){if(Bf.und(t.decay)){const n=!Bf.und(t.tension)||!Bf.und(t.friction);!n&&Bf.und(t.frequency)&&Bf.und(t.damping)&&Bf.und(t.mass)||(e.duration=void 0,e.decay=void 0),n&&(e.frequency=void 0)}else e.duration=void 0}var YC=[],KC=class{constructor(){this.changed=!1,this.values=YC,this.toValues=null,this.fromValues=YC,this.config=new GC,this.immediate=!1}};function QC(e,{key:t,props:n,defaultProps:r,state:i,actions:a}){return new Promise(((o,s)=>{let l,u,c=TC(n.cancel??r?.cancel,t);if(c)f();else{Bf.und(n.pause)||(i.paused=TC(n.pause,t));let e=r?.pause;!0!==e&&(e=i.paused||TC(e,t)),l=AC(n.delay||0,t),e?(i.resumeQueue.add(p),a.pause()):(a.resume(),p())}function d(){i.resumeQueue.add(p),i.timeouts.delete(u),u.cancel(),l=u.time-Mf.now()}function p(){l>0&&!Df.skipAnimation?(i.delayed=!0,u=Mf.setTimeout(f,l),i.pauseQueue.add(d),i.timeouts.add(u)):f()}function f(){i.delayed&&(i.delayed=!1),i.pauseQueue.delete(d),i.timeouts.delete(u),e<=(i.cancelId||0)&&(c=!0);try{a.start({...n,callId:e,cancel:c},o)}catch(e){s(e)}}}))}var JC=(e,t)=>1==t.length?t[0]:t.some((e=>e.cancelled))?nm(e.get()):t.every((e=>e.noop))?em(e.get()):tm(e.get(),t.every((e=>e.finished))),em=e=>({value:e,noop:!0,finished:!0,cancelled:!1}),tm=(e,t,n=!1)=>({value:e,finished:t,cancelled:n}),nm=e=>({value:e,cancelled:!0,finished:!1});function rm(e,t,n,r){const{callId:i,parentId:a,onRest:o}=t,{asyncTo:s,promise:l}=n;return a||e!==s||t.reset?n.promise=(async()=>{n.asyncId=i,n.asyncTo=e;const u=IC(t,((e,t)=>"onRest"===t?void 0:e));let c,d;const p=new Promise(((e,t)=>(c=e,d=t))),f=e=>{const t=i<=(n.cancelId||0)&&nm(r)||i!==n.asyncId&&tm(r,!1);if(t)throw e.result=t,d(e),e},h=(e,t)=>{const a=new am,o=new om;return(async()=>{if(Df.skipAnimation)throw im(n),o.result=tm(r,!1),d(o),o;f(a);const s=Bf.obj(e)?{...e}:{...t,to:e};s.parentId=i,Wf(u,((e,t)=>{Bf.und(s[t])&&(s[t]=e)}));const l=await r.start(s);return f(a),n.paused&&await new Promise((e=>{n.resumeQueue.add(e)})),l})()};let C;if(Df.skipAnimation)return im(n),tm(r,!1);try{let t;t=Bf.arr(e)?(async e=>{for(const t of e)await h(t)})(e):Promise.resolve(e(h,r.stop.bind(r))),await Promise.all([t.then(c),p]),C=tm(r.get(),!0,!1)}catch(e){if(e instanceof am)C=e.result;else{if(!(e instanceof om))throw e;C=e.result}}finally{i==n.asyncId&&(n.asyncId=a,n.asyncTo=a?s:void 0,n.promise=a?l:void 0)}return Bf.fun(o)&&Mf.batchedUpdates((()=>{o(C,r,r.item)})),C})():l}function im(e,t){Xf(e.timeouts,(e=>e.cancel())),e.pauseQueue.clear(),e.resumeQueue.clear(),e.asyncId=e.asyncTo=e.promise=void 0,t&&(e.cancelId=t)}var am=class extends Error{constructor(){super("An async animation has been interrupted. You see this error because you forgot to use `await` or `.catch(...)` on its returned promise.")}},om=class extends Error{constructor(){super("SkipAnimationSignal")}},sm=e=>e instanceof um,lm=1,um=class extends $h{constructor(){super(...arguments),this.id=lm++,this._priority=0}get priority(){return this._priority}set priority(e){this._priority!=e&&(this._priority=e,this._onPriorityChange(e))}get(){const e=vC(this);return e&&e.getValue()}to(...e){return Df.to(this,e)}interpolate(...e){return lC(`${oC}The "interpolate" function is deprecated in v9 (use "to" instead)`),Df.to(this,e)}toJSON(){return this.get()}observerAdded(e){1==e&&this._attach()}observerRemoved(e){0==e&&this._detach()}_attach(){}_detach(){}_onChange(e,t=!1){Bh(this,{type:"change",parent:this,value:e,idle:t})}_onPriorityChange(e){this.idle||lh.sort(this),Bh(this,{type:"priority",parent:this,priority:e})}},cm=Symbol.for("SpringPhase"),dm=e=>(1&e[cm])>0,pm=e=>(2&e[cm])>0,fm=e=>(4&e[cm])>0,hm=(e,t)=>t?e[cm]|=3:e[cm]&=-3,Cm=(e,t)=>t?e[cm]|=4:e[cm]&=-5,mm=class extends um{constructor(e,t){if(super(),this.animation=new KC,this.defaultProps={},this._state={paused:!1,delayed:!1,pauseQueue:new Set,resumeQueue:new Set,timeouts:new Set},this._pendingCalls=new Set,this._lastCallId=0,this._lastToId=0,this._memoizedDuration=0,!Bf.und(e)||!Bf.und(t)){const n=Bf.obj(e)?{...e}:{...t,from:e};Bf.und(n.default)&&(n.default=!0),this.start(n)}}get idle(){return!(pm(this)||this._state.asyncTo)||fm(this)}get goal(){return Dh(this.animation.to)}get velocity(){const e=vC(this);return e instanceof wC?e.lastVelocity||0:e.getPayload().map((e=>e.lastVelocity||0))}get hasAnimated(){return dm(this)}get isAnimating(){return pm(this)}get isPaused(){return fm(this)}get isDelayed(){return this._state.delayed}advance(e){let t=!0,n=!1;const r=this.animation;let{toValues:i}=r;const{config:a}=r,o=bC(r.to);!o&&Fh(r.to)&&(i=Gf(Dh(r.to))),r.values.forEach(((s,l)=>{if(s.done)return;const u=s.constructor==_C?1:o?o[l].lastPosition:i[l];let c=r.immediate,d=u;if(!c){if(d=s.lastPosition,a.tension<=0)return void(s.done=!0);let t=s.elapsedTime+=e;const n=r.fromValues[l],i=null!=s.v0?s.v0:s.v0=Bf.arr(a.velocity)?a.velocity[l]:a.velocity;let o;const p=a.precision||(n==u?.005:Math.min(1,.001*Math.abs(u-n)));if(Bf.und(a.duration))if(a.decay){const e=!0===a.decay?.998:a.decay,r=Math.exp(-(1-e)*t);d=n+i/(1-e)*(1-r),c=Math.abs(s.lastPosition-d)<=p,o=i*r}else{o=null==s.lastVelocity?i:s.lastVelocity;const t=a.restVelocity||p/10,r=a.clamp?0:a.bounce,l=!Bf.und(r),f=n==u?s.v0>0:n<u;let h,C=!1;const m=1,g=Math.ceil(e/m);for(let e=0;e<g&&(h=Math.abs(o)>t,h||(c=Math.abs(u-d)<=p,!c));++e)l&&(C=d==u||d>u==f,C&&(o=-o*r,d=u)),o+=(1e-6*-a.tension*(d-u)+.001*-a.friction*o)/a.mass*m,d+=o*m}else{let r=1;a.duration>0&&(this._memoizedDuration!==a.duration&&(this._memoizedDuration=a.duration,s.durationProgress>0&&(s.elapsedTime=a.duration*s.durationProgress,t=s.elapsedTime+=e)),r=(a.progress||0)+t/this._memoizedDuration,r=r>1?1:r<0?0:r,s.durationProgress=r),d=n+a.easing(r)*(u-n),o=(d-s.lastPosition)/e,c=1==r}s.lastVelocity=o,Number.isNaN(d)&&(console.warn("Got NaN while animating:",this),c=!0)}o&&!o[l].done&&(c=!1),c?s.done=!0:t=!1,s.setValue(d,a.round)&&(n=!0)}));const s=vC(this),l=s.getValue();if(t){const e=Dh(r.to);l===e&&!n||a.decay?n&&a.decay&&this._onChange(l):(s.setValue(e),this._onChange(e)),this._stop()}else n&&this._onChange(l)}set(e){return Mf.batchedUpdates((()=>{this._stop(),this._focus(e),this._set(e)})),this}pause(){this._update({pause:!0})}resume(){this._update({pause:!1})}finish(){if(pm(this)){const{to:e,config:t}=this.animation;Mf.batchedUpdates((()=>{this._onStart(),t.decay||this._set(e,!1),this._stop()}))}return this}update(e){return(this.queue||(this.queue=[])).push(e),this}start(e,t){let n;return Bf.und(e)?(n=this.queue||[],this.queue=[]):n=[Bf.obj(e)?e:{...t,to:e}],Promise.all(n.map((e=>this._update(e)))).then((e=>JC(this,e)))}stop(e){const{to:t}=this.animation;return this._focus(this.get()),im(this._state,e&&this._lastCallId),Mf.batchedUpdates((()=>this._stop(t,e))),this}reset(){this._update({reset:!0})}eventObserved(e){"change"==e.type?this._start():"priority"==e.type&&(this.priority=e.priority+1)}_prepareNode(e){const t=this.key||"";let{to:n,from:r}=e;n=Bf.obj(n)?n[t]:n,(null==n||BC(n))&&(n=void 0),r=Bf.obj(r)?r[t]:r,null==r&&(r=void 0);const i={to:n,from:r};return dm(this)||(e.reverse&&([n,r]=[r,n]),r=Dh(r),Bf.und(r)?vC(this)||this._set(n):this._set(r)),i}_update({...e},t){const{key:n,defaultProps:r}=this;e.default&&Object.assign(r,IC(e,((e,t)=>/^on/.test(t)?NC(e,n):e))),_m(this,e,"onProps"),Mm(this,"onProps",e,this);const i=this._prepareNode(e);if(Object.isFrozen(this))throw Error("Cannot animate a `SpringValue` object that is frozen. Did you forget to pass your component to `animated(...)` before animating its props?");const a=this._state;return QC(++this._lastCallId,{key:n,props:e,defaultProps:r,state:a,actions:{pause:()=>{fm(this)||(Cm(this,!0),Qf(a.pauseQueue),Mm(this,"onPause",tm(this,gm(this,this.animation.to)),this))},resume:()=>{fm(this)&&(Cm(this,!1),pm(this)&&this._resume(),Qf(a.resumeQueue),Mm(this,"onResume",tm(this,gm(this,this.animation.to)),this))},start:this._merge.bind(this,i)}}).then((n=>{if(e.loop&&n.finished&&(!t||!n.noop)){const t=vm(e);if(t)return this._update(t,!0)}return n}))}_merge(e,t,n){if(t.cancel)return this.stop(!0),n(nm(this));const r=!Bf.und(e.to),i=!Bf.und(e.from);if(r||i){if(!(t.callId>this._lastToId))return n(nm(this));this._lastToId=t.callId}const{key:a,defaultProps:o,animation:s}=this,{to:l,from:u}=s;let{to:c=l,from:d=u}=e;!i||r||t.default&&!Bf.und(c)||(c=d),t.reverse&&([c,d]=[d,c]);const p=!$f(d,u);p&&(s.from=d),d=Dh(d);const f=!$f(c,l);f&&this._focus(c);const h=BC(t.to),{config:C}=s,{decay:m,velocity:g}=C;(r||i)&&(C.velocity=0),t.config&&!h&&function(e,t,n){n&&(XC(n={...n},t),t={...n,...t}),XC(e,t),Object.assign(e,t);for(const t in WC)null==e[t]&&(e[t]=WC[t]);let{frequency:r,damping:i}=e;const{mass:a}=e;Bf.und(r)||(r<.01&&(r=.01),i<0&&(i=0),e.tension=Math.pow(2*Math.PI/r,2)*a,e.friction=4*Math.PI*i*a/r)}(C,AC(t.config,a),t.config!==o.config?AC(o.config,a):void 0);let v=vC(this);if(!v||Bf.und(c))return n(tm(this,!0));const y=Bf.und(t.reset)?i&&!t.default:!Bf.und(d)&&TC(t.reset,a),b=y?d:this.get(),x=DC(c),w=Bf.num(x)||Bf.arr(x)||cC(x),_=!h&&(!w||TC(o.immediate||t.immediate,a));if(f){const e=HC(c);if(e!==v.constructor){if(!_)throw Error(`Cannot animate between ${v.constructor.name} and ${e.name}, as the "to" prop suggests`);v=this._set(x)}}const M=v.constructor;let V=Fh(c),k=!1;if(!V){const e=y||!dm(this)&&p;(f||e)&&(k=$f(DC(b),x),V=!k),($f(s.immediate,_)||_)&&$f(C.decay,m)&&$f(C.velocity,g)||(V=!0)}if(k&&pm(this)&&(s.changed&&!y?V=!0:V||this._stop(l)),!h&&((V||Fh(l))&&(s.values=v.getPayload(),s.toValues=Fh(c)?null:M==_C?[1]:Gf(x)),s.immediate!=_&&(s.immediate=_,_||y||this._set(l)),V)){const{onRest:e}=s;Uf(wm,(e=>_m(this,t,e)));const r=tm(this,gm(this,l));Qf(this._pendingCalls,r),this._pendingCalls.add(n),s.changed&&Mf.batchedUpdates((()=>{s.changed=!y,e?.(r,this),y?AC(o.onRest,r):s.onStart?.(r,this)}))}y&&this._set(b),h?n(rm(t.to,t,this._state,this)):V?this._start():pm(this)&&!f?this._pendingCalls.add(n):n(em(b))}_focus(e){const t=this.animation;e!==t.to&&(Zh(this)&&this._detach(),t.to=e,Zh(this)&&this._attach())}_attach(){let e=0;const{to:t}=this.animation;Fh(t)&&(Wh(t,this),sm(t)&&(e=t.priority+1)),this.priority=e}_detach(){const{to:e}=this.animation;Fh(e)&&Gh(e,this)}_set(e,t=!0){const n=Dh(e);if(!Bf.und(n)){const e=vC(this);if(!e||!$f(n,e.getValue())){const r=HC(n);e&&e.constructor==r?e.setValue(n):yC(this,r.create(n)),e&&Mf.batchedUpdates((()=>{this._onChange(n,t)}))}}return vC(this)}_onStart(){const e=this.animation;e.changed||(e.changed=!0,Mm(this,"onStart",tm(this,gm(this,e.to)),this))}_onChange(e,t){t||(this._onStart(),AC(this.animation.onChange,e,this)),AC(this.defaultProps.onChange,e,this),super._onChange(e,t)}_start(){const e=this.animation;vC(this).reset(Dh(e.to)),e.immediate||(e.fromValues=e.values.map((e=>e.lastPosition))),pm(this)||(hm(this,!0),fm(this)||this._resume())}_resume(){Df.skipAnimation?this.finish():lh.start(this)}_stop(e,t){if(pm(this)){hm(this,!1);const n=this.animation;Uf(n.values,(e=>{e.done=!0})),n.toValues&&(n.onChange=n.onPause=n.onResume=void 0),Bh(this,{type:"idle",parent:this});const r=t?nm(this.get()):tm(this.get(),gm(this,e??n.to));Qf(this._pendingCalls,r),n.changed&&(n.changed=!1,Mm(this,"onRest",r,this))}}};function gm(e,t){const n=DC(t);return $f(DC(e.get()),n)}function vm(e,t=e.loop,n=e.to){const r=AC(t);if(r){const i=!0!==r&&FC(r),a=(i||e).reverse,o=!i||i.reset;return ym({...e,loop:t,default:!1,pause:void 0,to:!a||BC(n)?n:void 0,from:o?e.from:void 0,reset:o,...i})}}function ym(e){const{to:t,from:n}=e=FC(e),r=new Set;return Bf.obj(t)&&xm(t,r),Bf.obj(n)&&xm(n,r),e.keys=r.size?Array.from(r):null,e}function bm(e){const t=ym(e);return Bf.und(t.default)&&(t.default=IC(t)),t}function xm(e,t){Wf(e,((e,n)=>null!=e&&t.add(n)))}var wm=["onStart","onRest","onChange","onPause","onResume"];function _m(e,t,n){e.animation[n]=t[n]!==OC(t,n)?NC(t[n],e.key):void 0}function Mm(e,t,...n){e.animation[t]?.(...n),e.defaultProps[t]?.(...n)}var Vm=["onStart","onChange","onRest"],km=1,jm=class{constructor(e,t){this.id=km++,this.springs={},this.queue=[],this._lastAsyncId=0,this._active=new Set,this._changed=new Set,this._started=!1,this._state={paused:!1,pauseQueue:new Set,resumeQueue:new Set,timeouts:new Set},this._events={onStart:new Map,onChange:new Map,onRest:new Map},this._onFrame=this._onFrame.bind(this),t&&(this._flush=t),e&&this.start({default:!0,...e})}get idle(){return!this._state.asyncTo&&Object.values(this.springs).every((e=>e.idle&&!e.isDelayed&&!e.isPaused))}get item(){return this._item}set item(e){this._item=e}get(){const e={};return this.each(((t,n)=>e[n]=t.get())),e}set(e){for(const t in e){const n=e[t];Bf.und(n)||this.springs[t].set(n)}}update(e){return e&&this.queue.push(ym(e)),this}start(e){let{queue:t}=this;return e?t=Gf(e).map(ym):this.queue=[],this._flush?this._flush(this,t):(Tm(this,t),Hm(this,t))}stop(e,t){if(e!==!!e&&(t=e),t){const n=this.springs;Uf(Gf(t),(t=>n[t].stop(!!e)))}else im(this._state,this._lastAsyncId),this.each((t=>t.stop(!!e)));return this}pause(e){if(Bf.und(e))this.start({pause:!0});else{const t=this.springs;Uf(Gf(e),(e=>t[e].pause()))}return this}resume(e){if(Bf.und(e))this.start({pause:!1});else{const t=this.springs;Uf(Gf(e),(e=>t[e].resume()))}return 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t=e.keyCode;if(e.altKey&&!e.ctrlKey||e.metaKey||t>=uy.F1&&t<=uy.F12)return!1;switch(t){case uy.ALT:case uy.CAPS_LOCK:case uy.CONTEXT_MENU:case uy.CTRL:case uy.DOWN:case uy.END:case uy.ESC:case uy.HOME:case uy.INSERT:case uy.LEFT:case uy.MAC_FF_META:case uy.META:case uy.NUMLOCK:case uy.NUM_CENTER:case uy.PAGE_DOWN:case uy.PAGE_UP:case uy.PAUSE:case uy.PRINT_SCREEN:case uy.RIGHT:case uy.SHIFT:case uy.UP:case uy.WIN_KEY:case uy.WIN_KEY_RIGHT:return!1;default:return!0}},isCharacterKey:function(e){if(e>=uy.ZERO&&e<=uy.NINE)return!0;if(e>=uy.NUM_ZERO&&e<=uy.NUM_MULTIPLY)return!0;if(e>=uy.A&&e<=uy.Z)return!0;if(-1!==window.navigator.userAgent.indexOf("WebKit")&&0===e)return!0;switch(e){case uy.SPACE:case uy.QUESTION_MARK:case uy.NUM_PLUS:case uy.NUM_MINUS:case uy.NUM_PERIOD:case uy.NUM_DIVISION:case uy.SEMICOLON:case uy.DASH:case uy.EQUALS:case uy.COMMA:case uy.PERIOD:case uy.SLASH:case uy.APOSTROPHE:case uy.SINGLE_QUOTE:case uy.OPEN_SQUARE_BRACKET:case uy.BACKSLASH:case 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e=this.sliderRef,t=this.props,n=t.vertical,r=t.reverse,i=e.getBoundingClientRect();return n?r?i.bottom:i.top:window.pageXOffset+(r?i.right:i.left)}},{key:"getSliderLength",value:function(){var e=this.sliderRef;if(!e)return 0;var t=e.getBoundingClientRect();return this.props.vertical?t.height:t.width}},{key:"addDocumentTouchEvents",value:function(){this.onTouchMoveListener=ny(this.document,"touchmove",this.onTouchMove),this.onTouchUpListener=ny(this.document,"touchend",this.onEnd)}},{key:"addDocumentMouseEvents",value:function(){this.onMouseMoveListener=ny(this.document,"mousemove",this.onMouseMove),this.onMouseUpListener=ny(this.document,"mouseup",this.onEnd)}},{key:"removeDocumentEvents",value:function(){this.onTouchMoveListener&&this.onTouchMoveListener.remove(),this.onTouchUpListener&&this.onTouchUpListener.remove(),this.onMouseMoveListener&&this.onMouseMoveListener.remove(),this.onMouseUpListener&&this.onMouseUpListener.remove()}},{key:"focus",value:function(){var e;this.props.disabled||null===(e=this.handlesRefs[0])||void 0===e||e.focus()}},{key:"blur",value:function(){var e=this;this.props.disabled||Object.keys(this.handlesRefs).forEach((function(t){var n,r;null===(n=e.handlesRefs[t])||void 0===n||null===(r=n.blur)||void 0===r||r.call(n)}))}},{key:"calcValue",value:function(e){var t=this.props,n=t.vertical,r=t.min,i=t.max,a=Math.abs(Math.max(e,0)/this.getSliderLength());return n?(1-a)*(i-r)+r:a*(i-r)+r}},{key:"calcValueByPos",value:function(e){var t=(this.props.reverse?-1:1)*(e-this.getSliderStart());return this.trimAlignValue(this.calcValue(t))}},{key:"calcOffset",value:function(e){var t=this.props,n=t.min,r=(e-n)/(t.max-n);return Math.max(0,100*r)}},{key:"saveHandle",value:function(e,t){this.handlesRefs[e]=t}},{key:"render",value:function(){var e,t=this.props,i=t.prefixCls,a=t.className,o=t.marks,s=t.dots,l=t.step,u=t.included,c=t.disabled,d=t.vertical,p=t.reverse,f=t.min,h=t.max,C=t.children,m=t.maximumTrackStyle,g=t.style,v=t.railStyle,y=t.dotStyle,b=t.activeDotStyle,x=ty(Dv(n.prototype),"render",this).call(this),w=x.tracks,_=x.handles,M=dn()(i,(Nv(e={},"".concat(i,"-with-marks"),Object.keys(o).length),Nv(e,"".concat(i,"-disabled"),c),Nv(e,"".concat(i,"-vertical"),d),Nv(e,a,a),e));return r.createElement("div",{ref:this.saveSlider,className:M,onTouchStart:c?_y:this.onTouchStart,onMouseDown:c?_y:this.onMouseDown,onMouseUp:c?_y:this.onMouseUp,onKeyDown:c?_y:this.onKeyDown,onFocus:c?_y:this.onFocus,onBlur:c?_y:this.onBlur,style:g},r.createElement("div",{className:"".concat(i,"-rail"),style:qv(qv({},m),v)}),w,r.createElement(ry,{prefixCls:i,vertical:d,reverse:p,marks:o,dots:s,step:l,included:u,lowerBound:this.getLowerBound(),upperBound:this.getUpperBound(),max:h,min:f,dotStyle:y,activeDotStyle:b}),_,r.createElement(iy,{className:"".concat(i,"-mark"),onClickLabel:c?_y:this.onClickMarkLabel,vertical:d,marks:o,included:u,lowerBound:this.getLowerBound(),upperBound:this.getUpperBound(),max:h,min:f,reverse:p}),C)}}]),n}(e),t.displayName="ComponentEnhancer(".concat(e.displayName,")"),t.defaultProps=qv(qv({},e.defaultProps),{},{prefixCls:"rc-slider",className:"",min:0,max:100,step:1,marks:{},handle:function(e){var t=e.index,n=ey(e,["index"]);return delete n.dragging,null===n.value?null:r.createElement(ay,Object.assign({},n,{key:t}))},onBeforeChange:_y,onChange:_y,onAfterChange:_y,included:!0,disabled:!1,dots:!1,vertical:!1,reverse:!1,trackStyle:[{}],handleStyle:[{}],railStyle:{},dotStyle:{},activeDotStyle:{}}),t}var Vy=function(e){Fv(n,e);var t=$v(n);function n(e){var r;Iv(this,n),(r=t.call(this,e)).onEnd=function(e){var t=r.state.dragging;r.removeDocumentEvents(),(t||e)&&r.props.onAfterChange(r.getValue()),r.setState({dragging:!1})};var i=void 0!==e.defaultValue?e.defaultValue:e.min,a=void 0!==e.value?e.value:i;return r.state={value:r.trimAlignValue(a),dragging:!1},Qv(!("minimumTrackStyle"in e),"minimumTrackStyle will be deprecated, please use trackStyle instead."),Qv(!("maximumTrackStyle"in e),"maximumTrackStyle will be deprecated, please use railStyle instead."),r}return zv(n,[{key:"calcValueByPos",value:function(e){return 0}},{key:"calcOffset",value:function(e){return 0}},{key:"saveHandle",value:function(e,t){}},{key:"removeDocumentEvents",value:function(){}},{key:"componentDidUpdate",value:function(e,t){var n=this.props,r=n.min,i=n.max,a=n.value,o=n.onChange;if("min"in this.props||"max"in this.props){var s=void 0!==a?a:t.value,l=this.trimAlignValue(s,this.props);l!==t.value&&(this.setState({value:l}),r===e.min&&i===e.max||!py(s,this.props)||o(l))}}},{key:"onChange",value:function(e){var t=this.props,n=!("value"in t),r=e.value>this.props.max?qv(qv({},e),{},{value:this.props.max}):e;n&&this.setState(r);var i=r.value;t.onChange(i)}},{key:"onStart",value:function(e){this.setState({dragging:!0});var t=this.props,n=this.getValue();t.onBeforeChange(n);var r=this.calcValueByPos(e);this.startValue=r,this.startPosition=e,r!==n&&(this.prevMovedHandleIndex=0,this.onChange({value:r}))}},{key:"onMove",value:function(e,t){xy(e);var n=this.state.value,r=this.calcValueByPos(t);r!==n&&this.onChange({value:r})}},{key:"onKeyboard",value:function(e){var t=this.props,n=t.reverse,r=wy(e,t.vertical,n);if(r){xy(e);var i=this.state.value,a=r(i,this.props),o=this.trimAlignValue(a);if(o===i)return;this.onChange({value:o}),this.props.onAfterChange(o),this.onEnd()}}},{key:"getValue",value:function(){return this.state.value}},{key:"getLowerBound",value:function(){var e=this.props.startPoint||this.props.min;return this.state.value>e?e:this.state.value}},{key:"getUpperBound",value:function(){return this.state.value<this.props.startPoint?this.props.startPoint:this.state.value}},{key:"trimAlignValue",value:function(e){var t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{};if(null===e)return null;var n=qv(qv({},this.props),t);return by(yy(e,n),n)}},{key:"render",value:function(){var e=this,t=this.props,n=t.prefixCls,i=t.vertical,a=t.included,o=t.disabled,s=t.minimumTrackStyle,l=t.trackStyle,u=t.handleStyle,c=t.tabIndex,d=t.ariaLabelForHandle,p=t.ariaLabelledByForHandle,f=t.ariaValueTextFormatterForHandle,h=t.min,C=t.max,m=t.startPoint,g=t.reverse,v=t.handle,y=this.state,b=y.value,x=y.dragging,w=this.calcOffset(b),_=v({className:"".concat(n,"-handle"),prefixCls:n,vertical:i,offset:w,value:b,dragging:x,disabled:o,min:h,max:C,reverse:g,index:0,tabIndex:c,ariaLabel:d,ariaLabelledBy:p,ariaValueTextFormatter:f,style:u[0]||u,ref:function(t){return e.saveHandle(0,t)}}),M=void 0!==m?this.calcOffset(m):0,V=l[0]||l;return{tracks:r.createElement(Jv,{className:"".concat(n,"-track"),vertical:i,included:a,offset:M,reverse:g,length:w-M,style:qv(qv({},s),V)}),handles:_}}}]),n}(r.Component);const ky=My(Vy);var jy=function(e){var t=e.value,n=e.handle,r=e.bounds,i=e.props,a=i.allowCross,o=i.pushable,s=Number(o),l=yy(t,i),u=l;return a||null==n||void 0===r||(n>0&&l<=r[n-1]+s&&(u=r[n-1]+s),n<r.length-1&&l>=r[n+1]-s&&(u=r[n+1]-s)),by(u,i)},Hy=function(e){Fv(n,e);var t=$v(n);function n(e){var r;Iv(this,n),(r=t.call(this,e)).onEnd=function(e){var t=r.state.handle;r.removeDocumentEvents(),(null!==t||e)&&r.props.onAfterChange(r.getValue()),r.setState({handle:null})};var i=e.count,a=e.min,o=e.max,s=Array.apply(void 0,ly(Array(i+1))).map((function(){return a})),l="defaultValue"in e?e.defaultValue:s,u=(void 0!==e.value?e.value:l).map((function(t,n){return jy({value:t,handle:n,props:e})})),c=u[0]===o?0:u.length-1;return r.state={handle:null,recent:c,bounds:u},r}return zv(n,[{key:"calcValueByPos",value:function(e){return 0}},{key:"calcOffset",value:function(e){return 0}},{key:"saveHandle",value:function(e,t){}},{key:"removeDocumentEvents",value:function(){}},{key:"componentDidUpdate",value:function(e,t){var n=this,r=this.props,i=r.onChange,a=r.value,o=r.min,s=r.max;if(("min"in this.props||"max"in this.props)&&(o!==e.min||s!==e.max)){var l=a||t.bounds;l.some((function(e){return py(e,n.props)}))&&i(l.map((function(e){return yy(e,n.props)})))}}},{key:"onChange",value:function(e){var t=this.props;if("value"in t){var n={};["handle","recent"].forEach((function(t){void 0!==e[t]&&(n[t]=e[t])})),Object.keys(n).length&&this.setState(n)}else this.setState(e);var r=qv(qv({},this.state),e).bounds;t.onChange(r)}},{key:"onStart",value:function(e){var t=this.props,n=this.state,r=this.getValue();t.onBeforeChange(r);var i=this.calcValueByPos(e);this.startValue=i,this.startPosition=e;var a=this.getClosestBound(i);if(this.prevMovedHandleIndex=this.getBoundNeedMoving(i,a),this.setState({handle:this.prevMovedHandleIndex,recent:this.prevMovedHandleIndex}),i!==r[this.prevMovedHandleIndex]){var o=ly(n.bounds);o[this.prevMovedHandleIndex]=i,this.onChange({bounds:o})}}},{key:"onMove",value:function(e,t){xy(e);var n=this.state,r=this.calcValueByPos(t);r!==n.bounds[n.handle]&&this.moveTo(r)}},{key:"onKeyboard",value:function(e){var t=this.props,n=t.reverse,r=wy(e,t.vertical,n);if(r){xy(e);var i=this.state,a=this.props,o=i.bounds,s=i.handle,l=o[null===s?i.recent:s],u=r(l,a),c=jy({value:u,handle:s,bounds:i.bounds,props:a});if(c===l)return;this.moveTo(c,!0)}}},{key:"getValue",value:function(){return this.state.bounds}},{key:"getClosestBound",value:function(e){for(var t=this.state.bounds,n=0,r=1;r<t.length-1;r+=1)e>=t[r]&&(n=r);return Math.abs(t[n+1]-e)<Math.abs(t[n]-e)&&(n+=1),n}},{key:"getBoundNeedMoving",value:function(e,t){var n=this.state,r=n.bounds,i=n.recent,a=t,o=r[t+1]===r[t];return o&&r[i]===r[t]&&(a=i),o&&e!==r[t+1]&&(a=e<r[t+1]?t:t+1),a}},{key:"getLowerBound",value:function(){return this.state.bounds[0]}},{key:"getUpperBound",value:function(){var e=this.state.bounds;return e[e.length-1]}},{key:"getPoints",value:function(){var e=this.props,t=e.marks,n=e.step,r=e.min,i=e.max,a=this.internalPointsCache;if(!a||a.marks!==t||a.step!==n){var o=qv({},t);if(null!==n)for(var s=r;s<=i;s+=n)o[s]=s;var 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i.isMouseEnterToShow()&&(k.onMouseEnter=i.onPopupMouseEnter),i.isMouseLeaveToHide()&&(k.onMouseLeave=i.onPopupMouseLeave),k.onMouseDown=i.onPopupMouseDown,k.onTouchStart=i.onPopupMouseDown,r.createElement(sw,hc({prefixCls:t,destroyPopupOnHide:n,visible:_,point:v&&M,className:a,align:V,onAlign:o,animation:l,getClassNameFromAlign:i.getPopupClassNameFromAlign},k,{stretch:g,getRootDomNode:i.getRootDomNode,style:c,mask:d,zIndex:C,transitionName:u,maskAnimation:p,maskTransitionName:f,maskMotion:h,ref:i.popupRef,motion:s,mobile:y,forceRender:b,onClick:x}),"function"==typeof m?m():m)})),Nv(Bv(i),"attachParent",(function(e){Oy.cancel(i.attachId);var t,n=i.props,r=n.getPopupContainer,a=n.getDocument,o=i.getRootDomNode();r?(o||0===r.length)&&(t=r(o)):t=a(i.getRootDomNode()).body,t?t.appendChild(e):i.attachId=Oy((function(){i.attachParent(e)}))})),Nv(Bv(i),"getContainer",(function(){if(!i.portalContainer){var e=(0,i.props.getDocument)(i.getRootDomNode()).createElement("div");e.style.position="absolute",e.style.top="0",e.style.left="0",e.style.width="100%",i.portalContainer=e}return i.attachParent(i.portalContainer),i.portalContainer})),Nv(Bv(i),"setPoint",(function(e){i.props.alignPoint&&e&&i.setState({point:{pageX:e.pageX,pageY:e.pageY}})})),Nv(Bv(i),"handlePortalUpdate",(function(){i.state.prevPopupVisible!==i.state.popupVisible&&i.props.afterPopupVisibleChange(i.state.popupVisible)})),Nv(Bv(i),"triggerContextValue",{onPopupMouseDown:i.onPopupMouseDown}),a="popupVisible"in e?!!e.popupVisible:!!e.defaultPopupVisible,i.state={prevPopupVisible:a,popupVisible:a},cw.forEach((function(e){i["fire".concat(e)]=function(t){i.fireEvents(e,t)}})),i}return zv(n,[{key:"componentDidMount",value:function(){this.componentDidUpdate()}},{key:"componentDidUpdate",value:function(){var e,t=this.props;if(this.state.popupVisible)return this.clickOutsideHandler||!this.isClickToHide()&&!this.isContextMenuToShow()||(e=t.getDocument(this.getRootDomNode()),this.clickOutsideHandler=ny(e,"mousedown",this.onDocumentClick)),this.touchOutsideHandler||(e=e||t.getDocument(this.getRootDomNode()),this.touchOutsideHandler=ny(e,"touchstart",this.onDocumentClick)),!this.contextMenuOutsideHandler1&&this.isContextMenuToShow()&&(e=e||t.getDocument(this.getRootDomNode()),this.contextMenuOutsideHandler1=ny(e,"scroll",this.onContextMenuClose)),void(!this.contextMenuOutsideHandler2&&this.isContextMenuToShow()&&(this.contextMenuOutsideHandler2=ny(window,"blur",this.onContextMenuClose)));this.clearOutsideHandler()}},{key:"componentWillUnmount",value:function(){this.clearDelayTimer(),this.clearOutsideHandler(),clearTimeout(this.mouseDownTimeout),Oy.cancel(this.attachId)}},{key:"getPopupDomNode",value:function(){var e;return(null===(e=this.popupRef.current)||void 0===e?void 0:e.getElement())||null}},{key:"getPopupAlign",value:function(){var e=this.props,t=e.popupPlacement,n=e.popupAlign,r=e.builtinPlacements;return t&&r?function(e,t,n){return qv(qv({},e[t]||{}),n)}(r,t,n):n}},{key:"setPopupVisible",value:function(e,t){var n=this.props.alignPoint,r=this.state.popupVisible;this.clearDelayTimer(),r!==e&&("popupVisible"in this.props||this.setState({popupVisible:e,prevPopupVisible:r}),this.props.onPopupVisibleChange(e)),n&&t&&e&&this.setPoint(t)}},{key:"delaySetPopupVisible",value:function(e,t,n){var r=this,i=1e3*t;if(this.clearDelayTimer(),i){var a=n?{pageX:n.pageX,pageY:n.pageY}:null;this.delayTimer=window.setTimeout((function(){r.setPopupVisible(e,a),r.clearDelayTimer()}),i)}else this.setPopupVisible(e,n)}},{key:"clearDelayTimer",value:function(){this.delayTimer&&(clearTimeout(this.delayTimer),this.delayTimer=null)}},{key:"clearOutsideHandler",value:function(){this.clickOutsideHandler&&(this.clickOutsideHandler.remove(),this.clickOutsideHandler=null),this.contextMenuOutsideHandler1&&(this.contextMenuOutsideHandler1.remove(),this.contextMenuOutsideHandler1=null),this.contextMenuOutsideHandler2&&(this.contextMenuOutsideHandler2.remove(),this.contextMenuOutsideHandler2=null),this.touchOutsideHandler&&(this.touchOutsideHandler.remove(),this.touchOutsideHandler=null)}},{key:"createTwoChains",value:function(e){var t=this.props.children.props,n=this.props;return t[e]&&n[e]?this["fire".concat(e)]:t[e]||n[e]}},{key:"isClickToShow",value:function(){var e=this.props,t=e.action,n=e.showAction;return-1!==t.indexOf("click")||-1!==n.indexOf("click")}},{key:"isContextMenuOnly",value:function(){var e=this.props.action;return"contextMenu"===e||1===e.length&&"contextMenu"===e[0]}},{key:"isContextMenuToShow",value:function(){var e=this.props,t=e.action,n=e.showAction;return-1!==t.indexOf("contextMenu")||-1!==n.indexOf("contextMenu")}},{key:"isClickToHide",value:function(){var e=this.props,t=e.action,n=e.hideAction;return-1!==t.indexOf("click")||-1!==n.indexOf("click")}},{key:"isMouseEnterToShow",value:function(){var e=this.props,t=e.action,n=e.showAction;return-1!==t.indexOf("hover")||-1!==n.indexOf("mouseEnter")}},{key:"isMouseLeaveToHide",value:function(){var e=this.props,t=e.action,n=e.hideAction;return-1!==t.indexOf("hover")||-1!==n.indexOf("mouseLeave")}},{key:"isFocusToShow",value:function(){var e=this.props,t=e.action,n=e.showAction;return-1!==t.indexOf("focus")||-1!==n.indexOf("focus")}},{key:"isBlurToHide",value:function(){var e=this.props,t=e.action,n=e.hideAction;return-1!==t.indexOf("focus")||-1!==n.indexOf("blur")}},{key:"forcePopupAlign",value:function(){var e;this.state.popupVisible&&(null===(e=this.popupRef.current)||void 0===e||e.forceAlign())}},{key:"fireEvents",value:function(e,t){var n=this.props.children.props[e];n&&n(t);var r=this.props[e];r&&r(t)}},{key:"close",value:function(){this.setPopupVisible(!1)}},{key:"render",value:function(){var e=this.state.popupVisible,t=this.props,n=t.children,i=t.forceRender,a=t.alignPoint,o=t.className,s=t.autoDestroy,l=r.Children.only(n),u={key:"trigger"};this.isContextMenuToShow()?u.onContextMenu=this.onContextMenu:u.onContextMenu=this.createTwoChains("onContextMenu"),this.isClickToHide()||this.isClickToShow()?(u.onClick=this.onClick,u.onMouseDown=this.onMouseDown,u.onTouchStart=this.onTouchStart):(u.onClick=this.createTwoChains("onClick"),u.onMouseDown=this.createTwoChains("onMouseDown"),u.onTouchStart=this.createTwoChains("onTouchStart")),this.isMouseEnterToShow()?(u.onMouseEnter=this.onMouseEnter,a&&(u.onMouseMove=this.onMouseMove)):u.onMouseEnter=this.createTwoChains("onMouseEnter"),this.isMouseLeaveToHide()?u.onMouseLeave=this.onMouseLeave:u.onMouseLeave=this.createTwoChains("onMouseLeave"),this.isFocusToShow()||this.isBlurToHide()?(u.onFocus=this.onFocus,u.onBlur=this.onBlur):(u.onFocus=this.createTwoChains("onFocus"),u.onBlur=this.createTwoChains("onBlur"));var c=dn()(l&&l.props&&l.props.className,o);c&&(u.className=c);var d=qv({},u);Zy(l)&&(d.ref=Dy(this.triggerRef,l.ref));var p,f=r.cloneElement(l,d);return(e||this.popupRef.current||i)&&(p=r.createElement(pw,{key:"portal",getContainer:this.getContainer,didUpdate:this.handlePortalUpdate},this.getComponent())),!e&&s&&(p=null),r.createElement(lw.Provider,{value:this.triggerContextValue},f,p)}}],[{key:"getDerivedStateFromProps",value:function(e,t){var n=e.popupVisible,r={};return void 0!==n&&t.popupVisible!==n&&(r.popupVisible=n,r.prevPopupVisible=t.popupVisible),r}}]),n}(r.Component),Nv(fw,"contextType",lw),Nv(fw,"defaultProps",{prefixCls:"rc-trigger-popup",getPopupClassNameFromAlign:function(){return""},getDocument:function(e){return e?e.ownerDocument:window.document},onPopupVisibleChange:uw,afterPopupVisibleChange:uw,onPopupAlign:uw,popupClassName:"",mouseEnterDelay:0,mouseLeaveDelay:.1,focusDelay:0,blurDelay:.15,popupStyle:{},destroyPopupOnHide:!1,popupAlign:{},defaultPopupVisible:!1,mask:!1,maskClosable:!0,action:[],showAction:[],hideAction:[],autoDestroy:!1}),fw);var pw,fw,hw={adjustX:1,adjustY:1},Cw=[0,0],mw={left:{points:["cr","cl"],overflow:hw,offset:[-4,0],targetOffset:Cw},right:{points:["cl","cr"],overflow:hw,offset:[4,0],targetOffset:Cw},top:{points:["bc","tc"],overflow:hw,offset:[0,-4],targetOffset:Cw},bottom:{points:["tc","bc"],overflow:hw,offset:[0,4],targetOffset:Cw},topLeft:{points:["bl","tl"],overflow:hw,offset:[0,-4],targetOffset:Cw},leftTop:{points:["tr","tl"],overflow:hw,offset:[-4,0],targetOffset:Cw},topRight:{points:["br","tr"],overflow:hw,offset:[0,-4],targetOffset:Cw},rightTop:{points:["tl","tr"],overflow:hw,offset:[4,0],targetOffset:Cw},bottomRight:{points:["tr","br"],overflow:hw,offset:[0,4],targetOffset:Cw},rightBottom:{points:["bl","br"],overflow:hw,offset:[4,0],targetOffset:Cw},bottomLeft:{points:["tl","bl"],overflow:hw,offset:[0,4],targetOffset:Cw},leftBottom:{points:["br","bl"],overflow:hw,offset:[-4,0],targetOffset:Cw}};function gw(e){var t=e.showArrow,n=e.arrowContent,i=e.children,a=e.prefixCls,o=e.id,s=e.overlayInnerStyle,l=e.className,u=e.style;return r.createElement("div",{className:dn()("".concat(a,"-content"),l),style:u},!1!==t&&r.createElement("div",{className:"".concat(a,"-arrow"),key:"arrow"},n),r.createElement("div",{className:"".concat(a,"-inner"),id:o,role:"tooltip",style:s},"function"==typeof i?i():i))}var vw=["overlayClassName","trigger","mouseEnterDelay","mouseLeaveDelay","overlayStyle","prefixCls","children","onVisibleChange","afterVisibleChange","transitionName","animation","motion","placement","align","destroyTooltipOnHide","defaultVisible","getTooltipContainer","overlayInnerStyle","arrowContent","overlay","id","showArrow"],yw=function(e,t){var n=e.overlayClassName,i=e.trigger,a=void 0===i?["hover"]:i,o=e.mouseEnterDelay,s=void 0===o?0:o,l=e.mouseLeaveDelay,u=void 0===l?.1:l,c=e.overlayStyle,d=e.prefixCls,p=void 0===d?"rc-tooltip":d,f=e.children,h=e.onVisibleChange,C=e.afterVisibleChange,m=e.transitionName,g=e.animation,v=e.motion,y=e.placement,b=void 0===y?"right":y,x=e.align,w=void 0===x?{}:x,_=e.destroyTooltipOnHide,M=void 0!==_&&_,V=e.defaultVisible,k=e.getTooltipContainer,j=e.overlayInnerStyle,H=e.arrowContent,E=e.overlay,L=e.id,S=e.showArrow,P=void 0===S||S,A=ey(e,vw),T=(0,r.useRef)(null);(0,r.useImperativeHandle)(t,(function(){return T.current}));var N=qv({},A);"visible"in e&&(N.popupVisible=e.visible);var O=!1,q=!1;if("boolean"==typeof M)O=M;else if(M&&"object"===Av(M)){var I=M.keepParent;O=!0===I,q=!1===I}return r.createElement(dw,hc({popupClassName:n,prefixCls:p,popup:function(){return r.createElement(gw,{showArrow:P,arrowContent:H,key:"content",prefixCls:p,id:L,overlayInnerStyle:j},E)},action:a,builtinPlacements:mw,popupPlacement:b,ref:T,popupAlign:w,getPopupContainer:k,onPopupVisibleChange:h,afterPopupVisibleChange:C,popupTransitionName:m,popupAnimation:g,popupMotion:v,defaultPopupVisible:V,destroyPopupOnHide:O,autoDestroy:q,mouseLeaveDelay:u,popupStyle:c,mouseEnterDelay:s},N),f)};const bw=(0,r.forwardRef)(yw);const xw=r.forwardRef((function(e,t){var n=e.visible,i=e.overlay,a=r.useRef(null),o=Dy(t,a),s=r.useRef(null);function l(){Oy.cancel(s.current)}return r.useEffect((function(){return n?s.current=Oy((function(){var e;null===(e=a.current)||void 0===e||e.forcePopupAlign()})):l(),l}),[n,i]),r.createElement(bw,Object.assign({ref:o},e))}));var ww=ky;ww.Range=Ey,ww.Handle=ay,ww.createSliderWithTooltip=function(e){var t;return t=function(t){Fv(i,t);var n=$v(i);function i(){var e;return 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zv(i,[{key:"render",value:function(){return r.createElement(e,Object.assign({},this.props,{handle:this.handleWithTooltip}))}}]),i}(r.Component),t.defaultProps={tipFormatter:function(e){return e},handleStyle:[{}],tipProps:{},getTooltipContainer:function(e){return e.parentNode}},t};const _w=ww;var Mw=i(8607),Vw={};Vw.styleTagTransform=_v(),Vw.setAttributes=yv(),Vw.insert=gv().bind(null,"head"),Vw.domAPI=Cv(),Vw.insertStyleElement=xv(),fv()(Mw.A,Vw),Mw.A&&Mw.A.locals&&Mw.A.locals;const{createSliderWithTooltip:kw}=_w,jw=kw(_w.Range),Hw=({title:e,min:t,max:n,value:r,onChange:i,style:a={}})=>{const o={width:300,margin:50,...a};return(0,dc.jsxs)("div",{style:o,children:[(0,dc.jsx)("p",{children:e}),(0,dc.jsx)(jw,{allowCross:!1,min:t,max:n,value:r,onChange:i})]})};function Ew(e,t,n){e=+e,t=+t,n=(i=arguments.length)<2?(t=e,e=0,1):i<3?1:+n;for(var r=-1,i=0|Math.max(0,Math.ceil((t-e)/n)),a=new Array(i);++r<i;)a[r]=e+r*n;return a}class Lw extends 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Elle montre que le port de Marseille un des trois grands ports commerciaux français à la fin du XVIIIe siècle et que ses échanges allaient bien au-delà des rivages méditerranéens.  ","description_en":"This map allows you to locate Marseille among the other major French ports, on the one hand (Scale = France), and to visualize the relations of the Marseille port with foreign countries and markets (Scale = World). It shows that the port of Marseille was one of the three major French commercial ports at the end of the 18th century and that its trade went well beyond the Mediterranean shores.  ","comment_lire_fr":"Cette visualisation permet une interaction aussi bien au niveau de l\'échelle (France / Monde) qu\'au niveau des sources (Navigation / Commerce).<br/> Avec la combinaison \\"Navigation/France\\" , la carte affiche les départs depuis les 10 principaux ports de France: la largeur supérieure du triangle est proportionnelle au nombre des congés délivrés, la hauteur au tonnage moyen constaté. En survolant un port, une infobulle fournit les données précises pour ces deux variables. Pour Marseille, le tonnage moyen est le fruit d\'une estimation. En bas de la légende, il est possible d\'interagir avec la carte pour augmenter ou diminuer le nombre des ports français qui s\'affichent. Tous les registres des congés n\'étant pas conservés, les données pour la Provence, le Languedoc et une partie de la Bretagne ainsi que de la plupart des ports coloniaux ne s\'affichent pas. Pour plus de précisions sur la complétude des sources, voir http://vizsources.portic.fr/. <br/>La combinaison \\"Navigation\\"/Monde permet de visualiser le nombre des voyages qui aboutissent à Marseille en 1789, par pays (ou groupes de pays) de départ. Les catégories utilisées sont celles de la Balance du Commerce, ce qui permet de comparaisons. La largeur du triangle est proportionnelle au nombre de voyages et la hauteur au tonnage moyen, estimé à partir du type de navire. En sélectionnant l\'icône commerce, on fera apparaître alternativement les flux de commerce de Marseille par rapport aux autres ports français (en cliquant sur l\'icône \\"France\\") ou les flux de commerce du port de Marseille avec l\'étranger (comme des exportations et importations) en sélectionnant l\'icône Monde. Les flux sont représentés sous forme de cercles proportionnels, en pointant le curseur de la souris/du touchpad sur  le cercle, on fera apparaître le montant du flux illustré par le cercle.","comment_lire_en":"This visualization allows interaction both at the scale level (France / World) and at the source level (Navigation / Commerce).<br/> With the \\"Navigation/France\\" combination, the map displays departures from the 10 main ports in France: the upper width of the triangle is proportional to the number of departures delivered, the height to the average tonnage observed. When hovering over a port, a tooltip provides precise data for these two variables. For Marseille, the average tonnage is the result of an estimate. At the bottom of the legend, it is possible to interact with the map to increase or decrease the number of French ports displayed. Not all leave records are kept, so data for Provence, Languedoc and part of Brittany as well as most colonial ports are not displayed. For more details on the completeness of the sources, see http://vizsources.portic.fr/. <br/>The \\"Navigation\\"/World combination allows you to visualize the number of voyages which ended in Marseille in 1789, by country (or groups of countries) of departure. The categories used are those of the Balance of Commerce, which allows comparisons. The width of the triangle is proportional to the number of voyages and the height to the average tonnage, estimated from the type of ship. By selecting the trade icon, we will alternately display the trade flows of Marseille in relation to other French ports (by clicking on the \\"France\\" icon) or the trade flows of the port of Marseille with foreign countries (such as exports and imports) by selecting the World icon. The flows are represented in the form of proportional circles, by pointing the mouse/touchpad cursor on the circle, the amount of flow illustrated by the circle will appear.","comment_cest_fait_fr":"Les données du commerce sont tirées de la base de données toflit18 pour l\'année 1789, et plus particulièrement : des données rapportées par la direction des fermes de Marseille pour les partenaires non-français, et des données du commerce local portant sur les partenaires non-français.<br/>Les données de la navigation internationale sont tirées de la base de données Navigocorpus pour l\'année 1789, avec un filtrage sur le port de départ dans le cas d\'un itinéraire comportant des escales, pour ce qui est des données internationales.<br/>Pour ce qui est de la navigation nationale et du classement des plus grands ports de France, nous avons utilisé les données des registres des congés de 1787 insérés dans Navigocorpus pour connaître leur nombre et calculer le tonnage moyen. Pour Marseille, port pour lequel le registre des congés n\'est pas conservé, nous avons calculé un tonnage moyen à partir des estimations du tonnage de navires entrés (connus grâce aux registres des dépositions des capitaines auprès du bureau de la Santé), en fonction de leur type (tartane, pinque, ...), puis multiplié ce tonnage moyen par le nombre des congés qui est connu grâce au compte-rendu des congés délivré en 1787.","comment_cest_fait_en":"Trade data are taken from the toflit18 database for the year 1789, and more particularly: data reported by the management of Marseille farms for non-French partners, and local trade data relating to non-French partners. -French.<br/>International navigation data are taken from the Navigocorpus database for the year 1789, with filtering on the port of departure in the case of an itinerary with stopovers, for international data.<br/>Regarding national navigation and the classification of the largest ports in France, we used data from the 1787 leave registers inserted in Navigocorpus to know their number and calculate the average tonnage. For Marseille, a port for which the leave register is not kept, we calculated an average tonnage from estimates of the tonnage of ships entered (known thanks to the registers of captains\' statements to the Health office), depending on of their type (tartane, pinque, etc.), then multiplied this average tonnage by the number of holidays which is known thanks to the leave report issued in 1787.","inputs":[],"outputs":["map_backgrounds/intro_map.geojson","intro_data_world.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données toflit18 - commerce international : année 1789, direction des fermes de Marseille, best guess region prodxpart, partenaires non Français, classés par partner_grouping (ou wars pour Italie et Allemagne)<br/>Données toflit18 - commerce local : année 1789, best guess region prod x part, partenaires non français, exclusion des customs_region \\"France\\" et \\"directions de terre\\"<br/>Données navigo navigation internationale - pays de départ des navires à destination de Marseille : pointcalls, outdate_fixed = 1789, pointcall_rank_dedieu = 1, state != France<br/>Données navigation nationale - plus grands ports de France : pour le tonnage moyen navigo pointcalls \\"Out\\" en France en 1787, pour le nombre de départs données des décomptes réalisés à partir des compte-rendus par ports (https://docs.google.com/spreadsheets/d/e/2PACX-1vRNAeIEFhB_RTm2xBgeuXl5oMtNIrGhWT6uCB2S9wEUblwDidRBwv9dp8D0S-YIPUyoASaG2p-NgfWD/pub)<br/>Tonnages calculés à partir des estimations par classe quand tonnage non indiqué (https://docs.google.com/spreadsheets/d/e/2PACX-1vTYdeIwpzaVpY_KS91cXiHxb309iYBS4JN_1_hW-_oyeysuwcIpC2VJ5fWeZJl4tA/pub)."},"dynamique-du-commerce":{"id":"dynamique-du-commerce","partie":"1.A","n_chapitre":1,"lien_permanent_visualisation":"/vizualisation/dynamique-du-commerce","titre_fr":"Dynamisme du commerce des principales directions de ferme","titre_en":"Dynamism of trade of the main farm managements","description_fr":"Le graphique représente les flux du commerce d\'exportations et d\'importations de marchandises de la France et de ses principaux ports de 1740 à 1789 et leurs tendances de moyen terme.","description_en":"The graph represents the flows of trade in exports and imports of goods from France and its main ports from 1740 to 1789 and their medium-term trends.","comment_lire_fr":"D’après les données liées au Bureau de la balance du commerce recueillies par Toflit18, le commerce total de Marseille double entre 1725 et 1738, passant de 11 M de livres tournois à 22 M de livres tournois, puis est multiplié par plus de cinq en deux ans pour atteindre 110 M de lt en 1740. Cette augmentation brutale ne peut être qu’un artefact statistique que nous ne sommes pas arrivés à expliquer. Peut-être est-ce que, comme à Dunkerque en 1789, les Fermes (qui prélevaient les traites et rassemblaient à cette occasion des informations sur les flux) ont-elles pu étendre le champ de leurs investigations ? Dans l’incertitude, nous avons choisi de ne représenter les données sur les graphiques qu’à partir de 1740.  <br/>Le graphique pour les données nationales (\\"France\\") comprend les courbes des importations/importations et leur tendance (la courbe foncée). Les graphiques pour chacune des directions comprennent deux courbes de même nature que celles des données nationales, ainsi qu’un histogramme qui donne le pourcentage que représentent les flux de ce port proportionnellement au total des ports français.  <br/>Il est possible d\'interagir avec la visualisation en sélectionnant dans le menu déroulant en bas le type de données qu\'on souhaite afficher (importations, exportations, avec ou sans les produits coloniaux et avec ou sans les partenaires coloniaux). L\'utilisateur peut également cocher les directions des Fermes dont il souhaite afficher les données. Les données pour chaque année peuvent être obtenues en pointant le curseur sur la courbe/l\'histogramme à l\'endroit approprié.","comment_lire_en":"According to data linked to the Office of the Balance of Commerce collected by Toflit18, Marseille\'s total trade doubled between 1725 and 1738, going from 11 million tournament pounds to 22 million tournament books, then multiplied by more than five in two years to reach 110 million lt in 1740. This sudden increase can only be a statistical artifact that we have not been able to explain. Perhaps, as in Dunkirk in 1789, the Farms (which collected the drafts and on this occasion gathered information on the flows) were able to extend the scope of their investigations? Given the uncertainty, we have chosen to only represent the data on the graphs from 1740.  <br/>The graph for national data (\\"France\\") includes import/import curves and their trend (the dark curve). The graphs for each direction include two curves of the same nature as those of the national data, as well as a histogram which gives the percentage represented by the flows of this port in proportion to the total of French ports.  <br/>It is possible to interact with the visualization by selecting from the drop-down menu at the bottom the type of data you wish to display (imports, exports, with or without colonial products and with or without colonial partners). The user can also check the directions of the Farms whose data they wish to display. Data for each year can be obtained by pointing the cursor over the curve/histogram at the appropriate location.","comment_cest_fait_fr":"Les données du commerce sont tirées de la base de données toflit18, avec les sources issues des directions de fermes pour ce qui est des métriques locales et les sources nationales pour le niveau français, avec exclusion des partenaires français.<br/>Les séries \\"sans produits coloniaux\\" excluent les typologies de produits \\"Plantation foodstuffs\\".<br/>Les séries \\"sans colonies\\" excluent les partenaires correspondant à des colonies françaises (\\"Outre-mers\\", \\"Afrique\\", \\"Amériques\\", \\"Asie\\").<br/>Les régressions ont été calculées avec le module python regress.","comment_cest_fait_en":"Trade data are taken from the toflit18 database, with sources from farm management for local metrics and national sources for the French level, with exclusion of French partners.<br/>The “colonial products free” series exclude “Plantation foodstuffs” product types.<br/>The \\"without colonies\\" series exclude partners corresponding to French colonies (\\"Overseas\\", \\"Africa\\", \\"Americas\\", \\"Asia\\").<br/>Regressions were calculated with the Python regress module.","inputs":[],"outputs":["tradeDynamics.csv","tradeDynamics_reference_france_trade.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données toflit18, best guess region prodxpart pour les directions et best guess national partner pour le national, exclusion des partenaires français.<br/>Séries \\"sans produits coloniaux\\" : product = != \\"Plantation foodstuffs\\"<br/>Séries \\"sans colonies\\" : partner_grouping != [\\"Outre-mers\\", \\"Afrique\\", \\"Amériques\\", \\"Asie\\"]<br/>Régressions calculées avec le module python regress"},"correlation-prix":{"id":"correlation-prix","partie":"1.B","n_chapitre":1,"lien_permanent_visualisation":"/vizualisation/correlation-prix","titre_fr":"Corrélation des prix du blé dans la France du XVIIIe siècle","titre_en":"Correlation of wheat prices in 18th century France","description_fr":"Le graphique permet de visualiser les corrélations des prix du blé des différentes régions françaises et de voir le poids des déterminants géographiques qui influent sur l\'évolution de ces prix.","description_en":"The graph allows you to visualize the correlations of wheat prices in the different French regions and to see the weight of the geographical determinants which influence the evolution of these prices.","comment_lire_fr":"Cette visualisation permet de montrer que les prix du blé en France sont corrélés entre eux.  <br/>Elle propose deux types de représentations graphiques: via un réseau ou plus traditionnellement, par une carte.  <br/>Dans le réseau (menu \\"Positions des villes\\", avec choix: \\"Réseaux de corrélation de prix\\"), la place d\'une ville (dont le nom apparaît lorsque le curseur est placé dessus) par rapport à une autre indique la corrélation plus (lorsqu\'elle est proche) ou moins forte (lorsqu\'elle est éloignée) des prix du blé. Le placement des points n\'a donc rien à voir avec leur emplacement géographique.  Les points seront colorés en fonction de leur appartenance à un ensemble géographique (bassin versant) ou à une communauté de prix (les villes dont le mouvement des prix du blé ressemble à la ville principale). <br/>En sélectionnant, \\"Géographie\\" dans le menu \\"Position des villes\\", le réseau se transformera en carte géographique - cette fois-ci la place des villes correspond à leur place géographique sur le territoire métropolitain. La couleur de la ville est liée dans le cas des bassins versants à leur appartenance à un ensemble géographique dominé par un fleuve ou une grande rivière (la zone bleue pour la Loire par exemple). Si l\'on choisit \\"groupe de prix\\", la couleur sera celle établie par l\'algorithme d\'extraction de communautés. On peut ainsi constater l\'importance de la géographie pour expliquer les corrélations des prix du blé au XVIIIe siècle.","comment_lire_en":"This visualization shows that wheat prices in France are correlated with each other.  <br/>It offers two types of graphic representations: via a network or more traditionally, by a map.  <br/>In the network (\\"Positions of cities\\" menu, with choice: \\"Price correlation networks\\"), the place of a city (whose name appears when the cursor is placed on it) in relation to another indicates the correlation more (when it is close) or less strong (when it is far away) from wheat prices. The placement of the points therefore has nothing to do with their geographical location.  The points will be colored according to their belonging to a geographical group (watershed) or to a price community (cities whose wheat price movement resembles the main city). <br/>By selecting \\"Geography\\" in the \\"Position of cities\\" menu, the network will transform into a geographical map - this time the location of the cities corresponds to their geographic location on the metropolitan territory. The color of the city is linked in the case of watersheds to their belonging to a geographical area dominated by a river or a large river (the blue zone for the Loire for example). If we choose \\"price group\\", the color will be that established by the community extraction algorithm. We can thus see the importance of geography in explaining the correlations of wheat prices in the 18th century.","comment_cest_fait_fr":"La corrélation des prix est calculée à partir de  Federico, G., Schulze, M. S., & Volckart, O. (2021). European goods market integration in the very long run: from the Black Death to the First World War. The Journal of Economic History, 81(1), 276-308.<br/>La coloration topographique est effectuée au moyen l\'algorithme d\'extraction de communautés dit de la méthode de Louvain.","comment_cest_fait_en":"Price correlation is calculated from Federico, G., Schulze, M. S., & Volckart, O. (2021). European goods market integration in the very long run: from the Black Death to the First World War. The Journal of Economic History, 81(1), 276-308.<br/>Topographic coloring is carried out using the community extraction algorithm known as the Louvain method.","inputs":[],"outputs":["wheat_correlations_cities.csv","wheat_correlations_links.csv","map_backgrounds/bassins_versants.json"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Corrélation des prix calculée à partir de  Federico, G., Schulze, M. S., & Volckart, O. (2021). European goods market integration in the very long run: from the Black Death to the First World War. The Journal of Economic History, 81(1), 276-308.par Daudin & Pignède (Daudin et Pignède, Le cmmerce de la France au XVIIIe : inflation et révolution - https://drive.google.com/file/d/1-X-be9zeDtCVx6S80eKV-6MaCQuwx039/view?usp=sharing)<br/>Coloration topographique effectuée avec l\'algorithme de Louvain."},"exportations-sud-est":{"id":"exportations-sud-est","partie":"1.C","n_chapitre":1,"lien_permanent_visualisation":"/vizualisation/exportations-sud-est","titre_fr":"Marseille, exportateur des produits du sud-est","titre_en":"Marseille, exporter of products from the southeast","description_fr":"","description_en":"","comment_lire_fr":"","comment_lire_en":"","comment_cest_fait_fr":"Les données sont tirées de la base de données toflit18, pour les exports de l\'année 1789, en excluant les partenaires français,  et en agrégeant par province d\'origine des produits (valeur en lt.).<br/>Les provinces d\'origine \\"\\"Amérique\\" \\"Outre-Mers\\", ont été reclassées en \\"colonies\\", et les noms de pays ainsi que la dénomination \\"Monde\\" regroupés en \\"étranger\\".<br/>Les exports de Marseille sont repérés en isolant ceux déclarés par la direction des fermes de Marseille.","comment_cest_fait_en":"The data are taken from the toflit18 database, for exports for the year 1789, excluding French partners, and aggregating by province of origin of the products (value in lt.).<br/>The provinces of origin \\"America\\" ​​\\"Overseas\\" were reclassified as \\"colonies\\", and the names of countries as well as the name \\"World\\" grouped together as \\"foreign\\".<br/>Exports from Marseille are identified by isolating those declared by the Marseille farm management.","inputs":[],"outputs":["origins_for_marseille_exports.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données de toflit18, année 1789, partner_grouping != France, best guess region prod x part, exports, aggrégées par origin_province ( et valeur en lt.).<br/>Les provinces d\'origine \\"\\"Amérique\\" \\"Outre-Mers\\", ont été reclassées en \\"colonies\\", et les noms de pays + \\"Monde\\" regroupés en \\"étranger\\".<br/>Les exports de Marseille sont repérés avec customs_region= \'Marseille\'"},"marseille-port-structurant":{"id":"marseille-port-structurant","partie":"1.C","n_chapitre":1,"lien_permanent_visualisation":"/vizualisation/marseille-port-structurant","titre_fr":"Marseille, port structurant de la côte méditerranéenne","titre_en":"Marseille, a key port on the Mediterranean coast","description_fr":"Cette carte permet de visualiser la force d\'attraction de Marseille sur la navigation des ports français en Méditerranée","description_en":"This map allows you to visualize the force of attraction of Marseille on the navigation of French ports in the Mediterranean","comment_lire_fr":"Cette carte représente le nombre des congés délivrés dans les ports français en Méditerranée en 1789. Les couleurs distinguent les 4 provinces concernées (Roussillon, Languedoc, Provence et Corse). Chaque carré est proportionnel au nombre des congés délivrés, qui est indiqué plus précisément dans l\'infobulle qui s\'affiche en survolant chaque carré. La partie en rouge du carré représente le nombre de navires entrés à Marseille en 1789 en provenance du port représenté. La visualisation permet ainsi d\'apprécier la force d\'attraction du port de Marseille sur les ports français proches. Par ex., on retrouve à l\'entrée de Marseille en 1789 un nombre de navires partis depuis Toulon correspondant à 47% du total des congés délivrés à Toulon. ","comment_lire_en":"This map represents the number of leaves issued in French ports in the Mediterranean in 1789. The colors distinguish the 4 provinces concerned (Roussillon, Languedoc, Provence and Corsica). Each square is proportional to the number of leaves issued, which is indicated more precisely in the tooltip that appears when hovering over each square. The red part of the square represents the number of ships entering Marseille in 1789 from the port represented. The visualization thus makes it possible to appreciate the force of attraction of the port of Marseille on nearby French ports. For example, we find at the entrance to Marseille in 1789 a number of ships leaving from Toulon corresponding to 47% of the total leave delivered to Toulon. ","comment_cest_fait_fr":"Les données sont tirées de la base de données Navigocorpus (format \\"pointcalls\\"), pour l\'année 1789. Elles sont issues des registres du petit cabotage et du registre de déclarations des capitaines à la Santé de Marseille. Les doublons ont été éliminés.<br/>Les données ont été agrégées selon le port qui précède l\'entrée à Marseille et filtrées pour ne retenir que les navires en provenance d\'un port français en Méditerranée.<br/>Le nombre de sorties totales de chaque port est connu à partir des compte-rendus des congés (fonds G5 aux Archives Nationales).","comment_cest_fait_en":"The data are taken from the Navigocorpus database (\\"pointcalls\\" format), for the year 1789. They come from the registers of small coastal shipping and the register of captains\' declarations to Marseille Health. Duplicates have been eliminated.<br/>The data was aggregated according to the port preceding entry into Marseille and filtered to only retain ships coming from a French port in the Mediterranean.<br/>The number of total departures from each port is known from the leave reports (G5 funds at the National Archives).","inputs":[],"outputs":["map_backgrounds/intro_map.geojson","navigation_frlevant_to_marseille.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données de navigo/pointcalls, date_fixed contient 1789, pointcall_function = O, source_suite = \\"Registre du petit cabotage (1786-1787)\\" ou \\"la Santé registre de patentes de Marseille\\", net_route_marker != \\"Q\'.<br/>Pointcall original de chaque trajet reconstitué en allant chercher source_doc_id et un pointcall_rank_dedieu inférieur à celui de Marseille.<br/>Agrégation par nombre de voyages vers Marseille à partir de navigo.<br/>Calcul du nombre de sorties totales de chaque port à partir des compte-rendus du G5 (https://docs.google.com/spreadsheets/d/e/2PACX-1vS1YPWol3pcsjiTlDPVPW9ZVpWeu2wcIoobEM_c-MKk9YfeIMvmanCCoPEFjPA0xUPJEnQ9hM4AAgwI/pub)"},"diversite-produits-exportes":{"id":"diversite-produits-exportes","partie":"2.A","n_chapitre":2,"lien_permanent_visualisation":"/vizualisation/diversite-produits-exportes","titre_fr":"Le commerce de Marseille: un commerce diversifié","titre_en":"The trade of Marseille: a diversified trade","description_fr":"Ce graphique permet de visualliser la grande diversité des produits échangés à Marseille comparativement aux autres ports, en particulier Bordeaux, le plus important en valeur.","description_en":"This graph allows you to visualize the great diversity of products traded in Marseille compared to other ports, in particular Bordeaux, the most important in value.","comment_lire_fr":"Chaque brique représente une année d\'échanges pour chacun des ports listés. Plus la brique est rouge, plus le port en question a, dans cette année, commercé un grand nombre de produits, sans qu\'un seul ou un petit nombre représente une part très importante de ses échanges. Inversement, la teinte grise indique une grande concentration des échanges sur un nombre relativement petit de produits (pour Bordeaux, il s\'agit essentiellement de trois types de marchandises: le vin, le sucre et le café). L\'indice de concentration des échanges utilisé est l\'indice Herfindahl-Hirschmann qui mesure la concentration de 0 (le moins concentré) à 100% (le monopole d\'un seul produit). En déplaçant la souris sur le diagramme, il est possible de mettre en évidence une année en particulier.","comment_lire_en":"Each brick represents a year of trade for each of the ports listed. The redder the brick, the more the port in question has, in that year, traded a large number of products, without a single or small number representing a very significant part of its trade. Conversely, the gray tint indicates a large concentration of trade on a relatively small number of products (for Bordeaux, it is essentially three types of goods: wine, sugar and coffee). The trade concentration index used is the Herfindahl-Hirschmann index which measures concentration from 0 (the least concentrated) to 100% (the monopoly of a single product). By moving the mouse over the diagram, it is possible to highlight a particular year.","comment_cest_fait_fr":"Les données du commerce sont tirées de la base de données toflit18, limitée aux exports agrégés par bureau des fermes.<br/>Le calcul de la diversité du commerce est réalisé au moyen de l\'indice Herfindahl-Hirschmann, appliqué sur les typologies de produits de la classification toflit18 intitulée \\"Revolution&Empire aggregate\\", rapportées à la valeur d\'export en livre tournoi de chaque catégorie de produit.","comment_cest_fait_en":"Trade data are taken from the toflit18 database, limited to exports aggregated by farm office.<br/>The calculation of trade diversity is carried out using the Herfindahl-Hirschmann index, applied to the product typologies of the toflit18 classification entitled \\"Revolution & Empire aggregate\\", compared to the export value in tournament pounds of each product category .","inputs":[],"outputs":["herfindal-exports-marseille.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données toflit18, exports, best guess region prod_x_part, agrégation par bureau des fermes (customs_office).<br/>Calcul avec l\'indice Herfindahl-Hirschmann à partir des typologies de produits Revolution&Empire aggregate, rapportées à la valeur d\'export en livre tournoi de chaque catégorie de produit.Notes sur la réponse à cette question:Pour certains bureaux et directions et bureaux, on a calculé l\'indice Herfindhal en tout année dont les données sur les produits exportés étaient enregistrées en toflit18_all_flows.Les six directions principales sélectionnées étaient : BordeauxMarseilleRouenNantesLa RochelleBayonneLes huit bureaux de ferme sélectionnées pour l\'année 1789 étaient : BordeauxMarseilleRouenNantesLa RochelleBayonneSaint-MaloLe HavrePuisqu\'il y a plus de données pour les directions que pour les bureaux, on a bouclé sur toute année enregistrée et on a calculé l\'indice Herfindhal.La calculation étaient fait selon les étapes suivantes : calculer la somme de la valeur de tout produit exporté par la direction / le bureau ciblé → all_product_valueagréger les exports par type et sommé leur valeur agrégéeles agrégations étaient fait sur la colonne \'product_revolutionempire\'GROUP BY product_revolutionempire → product_revolutionempire, SUM(value) AS sum_valuecalculer le ratio entre la totale en valeur d\'un produit et la totale du bureau / direction et le multiplier par lui-même(sum_value/all_product_value)2 → carre_part_marchecalculer la somme du ratio"},"part-des-etrangers-dans-navigation":{"id":"part-des-etrangers-dans-navigation","partie":"2.B","n_chapitre":2,"lien_permanent_visualisation":"/vizualisation/part-des-etrangers-dans-navigation","titre_fr":"Part des navires étrangers dans la navigation marseillaise en comparaison avec d\'autres ports","titre_en":"Share of foreign ships in Marseille navigation in comparison with other ports","description_fr":"Le graphique montre la part de la navigation assurée par de navires étrangers dans les principaux ports de France en 1787. Le bas du graphique indique la distribution des pavillons des navires étrangers arrivés à Marseille en 1789,","description_en":"The graph shows the share of navigation carried out by foreign ships in the main ports of France in 1787. The bottom of the graph indicates the distribution of flags of foreign ships arriving in Marseille in 1789,","comment_lire_fr":"La partie supérieure de cette visualisation permet de situer la part de la navigation effectuée par des navires étrangers dans les 10 principaux ports français en 1787. Les données expriment le tonnage total, connu par les registres des congés (et estimé dans le cas de Marseille à partir du type du navire). Le cas de Marseille n\'est pas tout-à-fait comparable, car il prend en compte les entrées des navires, le registre des congés n\'étant plus conservé. La forte internationalisation du transport est néanmoins évidente. En survolant le graphique, l\'infobulle précise le pourcentage du tonnage des navires étrangers.<br/>La partie inférieure de cette visualisation montre le degré d\'implication des différents pavillons étrangers qui arrivent à Marseille en 1789. Le tonnage est estimé à partir du type de navire, le total s\'affiche dans l\'infobulle en survolant un pavillon ou groupe de pavillon. On constate ainsi l\'importance des marines méditerranéennes, qu\'il s\'agisse des anciens Etats italiens, des Espagnols (pour l\'essentiel, des Catalans), ou encore de Ragusois, c\'est à dire des navires de l\'actuelle Dubrovnik. La part des trois principales flottes nordiques (britanniques, néerlandais et danois) est d\'environ un tiers, le pavillon suédois étant quasiment absent en 1789 en raison de la guerre qui oppose la Suède à la Russie de 1788 à 1790.","comment_lire_en":"The upper part of this visualization allows us to locate the share of navigation carried out by foreign ships in the 10 main French ports in 1787. The data expresses the total tonnage, known from the leave registers (and estimated in the case of Marseille at from the type of vessel). The case of Marseille is not completely comparable, because it takes into account the entries of ships, the leave register is no longer kept. The strong internationalization of transport is nevertheless evident. When hovering over the graph, the tooltip specifies the percentage of foreign vessel tonnage.<br/>The lower part of this visualization shows the degree of involvement of the different foreign flags arriving in Marseille in 1789. The tonnage is estimated from the type of ship, the total is displayed in the tooltip when hovering over a flag or group of flag. We thus see the importance of the Mediterranean navies, whether they are the former Italian States, the Spanish (mainly the Catalans), or even the Ragusois, that is to say the ships of today\'s Dubrovnik. . The share of the three main Nordic fleets (British, Dutch and Danish) is around a third, the Swedish flag being almost absent in 1789 due to the war between Sweden and Russia from 1788 to 1790.","comment_cest_fait_fr":"Pour le calcul de la part des pavillons étrangers sur le total, le graphique utilise les données de Navigocorpus pour l\'année 1787 : pour l\'ensemble des ports de la façade atlantique représentés, il s\'agit des navires sortis, connus par les registres des congés. Pour Marseille, nous avons utilisé les entrées et les tonnages estimés à partir des types de navires.  <br />Pour la répartition des pavillons des navires étrangers arrivés à Marseille, nous avons utilisé les données de 1789. Le tonnage est basé sur des estimations fondées sur le type de navire (tratane, pinque, etc.), quand celui-ci n\'est pas directement mentionné par la source. ","comment_cest_fait_en":"To calculate the share of foreign flags in the total, the graph uses data from Navigocorpus for the year 1787: for all the ports on the Atlantic coast represented, these are ships released, known from the registers leave. For Marseille, we used entries and tonnages estimated from ship types.  <br />For the distribution of flags of foreign ships arriving in Marseille, we used data from 1789. The tonnage is based on estimates based on the type of ship (tratane, pinque, etc.), when this is not directly mentioned by the source. ","inputs":[],"outputs":["share_of_strangers_1787_french_ports.csv","share_of_strangers_marseille_1789.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données navigo (flows), année 1787 et 1789 (indate_fixed), regroupement du détail par flag.<br/>Aggrégation par tonnage, calculés à partir des estimations fondées sur les classes de navire quand nécessaire (https://docs.google.com/spreadsheets/d/e/2PACX-1vTYdeIwpzaVpY_KS91cXiHxb309iYBS4JN_1_hW-_oyeysuwcIpC2VJ5fWeZJl4tA/pub)"},"part-des-francais-dans-provenance":{"id":"part-des-francais-dans-provenance","partie":"2.B","n_chapitre":2,"lien_permanent_visualisation":"/vizualisation/part-des-francais-dans-provenance","titre_fr":"Part des Français dans les provenances de voyages arrivés à Marseille","titre_en":"Share of French people in the origins of trips arriving in Marseille","description_fr":"Le graphique montre la part des entrées à Marseille effectuées par de navires de pavillon français par grandes catégories de provenance et pour les années de paix dont nous avons collecté les données. ","description_en":"The graph shows the share of entries into Marseille made by French-flagged ships by major categories of origin and for the years of peace for which we collected the data. ","comment_lire_fr":"Cette visualisation représente la présence de navires français dans les années de paix étudiées, en pourcentage du nombre d\'arrivées à Marseille (partie haute) ou en tonnage cumulé (estimé à partir du type de navire) (partie basse de la visualisation). Les infobulles fournissent le détail des données et les pourcentages. Les barres en couleur distinguent les ports de départ des navires, agrégés par pays ou groupes de pays. Le graphique permet tout d\'abord de constater le quasi-monopole de la flotte française dans le commerce en provenance des ports français et de l\'Empire ottoman. Dans le premier cas, cela s\'explique par la législation qui empêche aux étrangers de commercer entre deux ports français (s\'ils le font, ils sont alors vides ou en transit). Dans le second cas, c\'est l\'effet des droits prohibitifs qui pèsent sur les navires étrangers qui arrivent à Marseille depuis l\'Empire ottoman. En termes de tonnage cumulé, la navigation nationale et celle avec l\'Empire ottoman constituent les deux secteurs les plus importants. Ils sont suivis par les Etats de la péninsule italienne et de l\'Espagne (pour l\'essentiel, provenant des ports de ses côtes méditerranéennes), marchés sur lesquels la part de la navigation française n\'est pas négligeable, se situant autour de 40-50% des voyages. La navigation française depuis l\'Espagne est en perte de vitesse relative, les tonnages étant quant à eux plus stables. Dans le commerce avec les Provinces-Unies, la part des Français est très modeste; pour ce qui est des arrivées depuis de ports sous souveraineté britannique, la force des Français s\'explique par leur présence dans la pêche à Terre-Neuve: une quarantaine de navires par an viennent vendre leur poisson à Marseille, la pêche française étant protégée de la concurrence étrangère, frappée par de droits dissuasifs et des interdictions. Ainsi, le pourcentage important de navires français revèle en creux la relative faiblesse de la navigation vers Marseille depuis les Îles britanniques.","comment_lire_en":"This visualization represents the presence of French ships in the peace years studied, as a percentage of the number of arrivals in Marseille (upper part) or in cumulative tonnage (estimated from the type of ship) (lower part of the visualization). Tooltips provide data details and percentages. The colored bars distinguish the ports of departure of ships, aggregated by country or group of countries. The graph first allows us to see the quasi-monopoly of the French fleet in trade coming from French ports and the Ottoman Empire. In the first case, this is explained by legislation which prevents foreigners from trading between two French ports (if they do so, they are then empty or in transit). In the second case, it is the effect of the prohibitive duties which weigh on foreign ships which arrive in Marseille from the Ottoman Empire. In terms of cumulative tonnage, national navigation and that with the Ottoman Empire constitute the two most important sectors. They are followed by the States of the Italian peninsula and Spain (mainly from ports on its Mediterranean coasts), markets on which the share of French shipping is not negligible, standing at around 40 -50% of trips. French shipping from Spain is losing relative speed, with tonnages being more stable. In trade with the United Provinces, the French share is very modest; As for arrivals from ports under British sovereignty, the strength of the French is explained by their presence in fishing in Newfoundland: around forty ships per year come to sell their fish in Marseille, French fishing being protected from foreign competition, hit by dissuasive duties and bans. Thus, the large percentage of French ships implicitly reveals the relative weakness of navigation to Marseille from the British Isles.","comment_cest_fait_fr":"Les données de ce graphique ont été produites à partir de la base navigocorpus dans laquelle on a sélectionné les flux concernant des année de paix (1749,1769,1787,1789) à destination de Marseille. Les provenances ont été regroupées selon une classification ad hoc réalisée en fonction des questions de recherche que la visualisation sert à explorer.<br/>Les quantités correspondent à des agrégations des tonnages des navires ayant effectué les voyages, qui sont estimés à partir des types de navires quand c\'est nécessaire.","comment_cest_fait_en":"The data for this graph were produced from the navigocorpus database from which we selected the flows concerning peace years (1749, 1769, 1787, 1789) to Marseille. The provenances were grouped according to an ad hoc classification carried out based on the research questions that the visualization is used to explore.<br/>The quantities correspond to aggregations of the tonnages of the ships having carried out the voyages, which are estimated based on the types of ships when necessary.","inputs":[],"outputs":["compare_french_ships_to_marseille_accross_time.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données navigo (flows), année de paix (1749,1769,1787,1789) (indate_fixed), regroupement par departure_state_1789_fr, destination = Marseille.<br/>Aggrégation des groupes de provenances selon les règles suivantes (pour departure_state_1789_fr) : <br/>\\"France\\": \\"France\\",<br/>\\"République de Gênes\\": \\"Péninsule italienne\\",<br/>\\"Royaume de Naples\\": \\"Péninsule italienne\\",<br/>\\"multi-Etat\\": \\"autre\\",<br/>\\"Espagne\\": \\"Espagne\\",<br/>\\"Royaume de Piémont-Sardaigne\\": \\"Péninsule italienne\\",<br/>\\"Empire ottoman\\": \\"Empire ottoman\\",<br/>\\"zone maritime\\": \\"autre\\",<br/>\\"Etats pontificaux\\": \\"Péninsule italienne\\",<br/>\\"Toscane\\": \\"Péninsule italienne\\",<br/>\\"Duché de Massa et Carrare\\": \\"Péninsule italienne\\",<br/>\\"Monaco\\": \\"France\\",<br/>\\"Principauté de Piombino\\": \\"Péninsule italienne\\",<br/>\\"République de Lucques\\": \\"Péninsule italienne\\",<br/>\\"République de Raguse\\": \\"Péninsule italienne\\",<br/>\\"Malte\\": \\"autre\\",<br/>\\"Autriche\\": \\"autre\\",<br/>\\"République de Venise\\": \\"Péninsule italienne\\",<br/>\\"Grande-Bretagne\\": \\"Grande-Bretagne\\",<br/>\\"Maroc\\": \\"autre\\",<br/>\\"Principauté de Lampédouse\\": \\"Péninsule italienne\\",<br/>\\"Provinces-Unies\\": \\"Provinces-Unies\\",<br/>\\"Portugal\\": \\"autre\\",<br/>\\"Hambourg\\": \\"autre\\",<br/>\\"Pologne\\": \\"autre\\",<br/>\\"Danemark\\": \\"autre\\",<br/>\\"Empire russe\\": \\"autre\\",<br/>\\"\\": \\"autre\\"<br/>Aggrégation par tonnage, calculés à partir des estimations fondées sur les classes de navire quand nécessaire (https://docs.google.com/spreadsheets/d/e/2PACX-1vTYdeIwpzaVpY_KS91cXiHxb309iYBS4JN_1_hW-_oyeysuwcIpC2VJ5fWeZJl4tA/pub)"},"styles-navigation":{"id":"styles-navigation","partie":"2.C","n_chapitre":2,"lien_permanent_visualisation":"/vizualisation/styles-navigation","titre_fr":"Des types de navigation variés","titre_en":"Various types of navigation","description_fr":"Cette visualisation permet d\'apprécier les caractéristiques des navires qui arrivent à Marseille dans les années de paix étudiées (1749, 1769, 1787, 1789). Plus particulièrement, il indique la distribution de leurs tonnage estimé, et le nombre d\'escales qu\'ils effectuent avant d\'arriver à Marseille. ","description_en":"This visualization allows us to appreciate the characteristics of the ships that arrived in Marseille in the years of peace studied (1749, 1769, 1787, 1789). More particularly, it indicates the distribution of their estimated tonnage, and the number of stopovers they make before arriving in Marseille. ","comment_lire_fr":"La carte en haut à gauche distingue par couleur trois grandes aires de provenance des navires arrivés à Marseille en 1749, 1769, 1787 et 1789. Le terme “Ponant” désigne, dans la France d’Ancien Régime, la façade atlantique, par opposition à celle méditerranéenne. Nous y incluons le Portugal, les ports de la France métropolitaine sur l’Atlantique et la Manche, les ports européens en Atlantique, mer du Nord et Baltique, ainsi que les navires de pêche en provenance de Terre-Neuve. Pour les ports des Pays-Bas autrichiens, ceux dans l\'actuelle Belgique ont été rattachés à la catégorie \\"Ponant\\" alors que ceux en Méditerranée (Trieste et Fiume, aujourd’hui Rijeka) ont été rattachés à la catégorie \\"Méditerranée occidentale\\". Cette dernière s\'étend dans cette visualisation à l\'ensemble des Etats italiens ainsi que Ragusa (Dubrovnik) et inclut donc une partie des ports dans la mer Adriatique. Nous y rattachons aussi les départs depuis les ports espagnols situés en Atlantique et l\'ensemble des départs depuis le Maroc.  Sur cette carte, les cercles représentent les différents ports de départ, dont le toponyme s\'affiche en les survolant. La taille du cercle est proportionnelle au nombre de départ des navires arrivés à Marseille depuis ces ports. Les mêmes couleurs se retrouvent dans les trois diagrammes correspondants à ces trois grandes aires géographiques.  <br/>Les diagrammes agrègent le nombre des voyages arrivés à Marseille depuis l\'ensemble des ports de cette aire géographique sur les 4 années étudiées. Les diagrammes affichent la distribution des tonnages (axe horizontal), estimé à partir du type de navire indiqué par les sources. La taille des cercles est proportionnelle au nombre des voyages (voir la légende à la verticale à gauche de chaque diagramme ; attention: l\'échelle change en fonction de l\'aire géographique). Les données s\'affichent en prenant en compte le nombre d\'escales effectués sur la route qui amène le navire depuis le port de départ déclaré jusqu\'à Marseille.  <br/>Le total des voyages par nombre d\'escale s\'affiche dans le rectangle en couleur à droite. Ainsi, on dénombre 317 voyages depuis l\'Empire ottoman et la mer Noire dont les capitaines ont effectué 2 escales. Le total des voyages par catégorie de tonnage s\'affiche dans le rectangle de couleur en dessous de chaque graphique : ainsi, on dénombre 3108 voyages de navires estimés à 50 tonneaux depuis l\'Europe méditerranéenne.  <br/>La visualisation permet de constater que la navigation depuis l\'Europe méditerranéenne est le fait pour l\'essentiel de petites unités, celle depuis l\'Empire ottoman est le fait de navires de taille moyenne, alors que celle depuis le Ponant concerne de navires de grande taille. Les navires depuis l\'Empire ottoman effectuent un nombre nettement plus élevé d\'escales que tous les autres.","comment_lire_en":"The map at the top left distinguishes by color three large areas of origin of the ships arriving in Marseille in 1749, 1769, 1787 and 1789. The term “Ponant” designates, in Ancien Régime France, the Atlantic coast, as opposed to the Mediterranean one. We include Portugal, the ports of mainland France on the Atlantic and the Channel, European ports in the Atlantic, North Sea and Baltic, as well as fishing vessels from Newfoundland. For the ports of the Austrian Netherlands, those in what is now Belgium were attached to the \\"Ponant\\" category while those in the Mediterranean (Trieste and Fiume, today Rijeka) were attached to the \\"Western Mediterranean\\" category. The latter extends in this visualization to all Italian states as well as Ragusa (Dubrovnik) and therefore includes part of the ports in the Adriatic Sea. We also include departures from Spanish ports located in the Atlantic and all departures from Morocco.  On this map, the circles represent the different departure ports, whose toponyms are displayed when hovering over them. The size of the circle is proportional to the departure number of ships arriving in Marseille from these ports. The same colors are found in the three diagrams corresponding to these three large geographical areas.  <br/>The diagrams aggregate the number of trips arriving in Marseille from all the ports in this geographical area over the 4 years studied. The diagrams display the distribution of tonnages (horizontal axis), estimated from the type of vessel indicated by the sources. The size of the circles is proportional to the number of trips (see the vertical legend to the left of each diagram; note: the scale changes depending on the geographical area). The data is displayed taking into account the number of stops made on the route which takes the ship from the declared port of departure to Marseille.  <br/>The total trips by number of stopovers are displayed in the colored rectangle on the right. Thus, there are 317 voyages from the Ottoman Empire and the Black Sea whose captains made 2 stopovers. The total voyages by tonnage category are displayed in the colored rectangle below each graph: thus, there are 3,108 voyages of ships estimated at 50 tons from Mediterranean Europe.  <br/>The visualization shows that navigation from Mediterranean Europe is mainly carried out by small units, that from the Ottoman Empire is carried out by medium-sized ships, while that from Ponant involves large ships. size. Ships from the Ottoman Empire make a significantly higher number of port calls than all others.","comment_cest_fait_fr":"Les données de ce graphique ont été fabriquées à partir de la base navigocorpus, dans laquelle on a sélectionné les flux provenant de la source archivistique correspondant au registre de patentes de Marseille, réduits à ceux se déroulant durant des années de paix (1759, 1779, 1799). Dans cet ensemble, nous avons identifié le premier port de départ des voyages enregistrés.<br/>Nous avons regroupé les ports français en deux groupes \\"Ponant\\" et \\"méditerrannée occidentale\\" à partir de la province de départ des voyages, et nous avons groupé les ports étrangers au moyen d\'une classification manuelle réalisée à partir des états de départ.<br/>Les tonnages sont calculés à partir des estimations fondées sur les classes de navire quand c\'est nécessaire.","comment_cest_fait_en":"The data for this graph were produced from the navigocorpus database, in which we selected the flows coming from the archival source corresponding to the Marseille patent register, reduced to those taking place during years of peace (1759, 1779, 1799). In this set, we identified the first port of departure for recorded voyages.<br/>We grouped French ports into two groups \\"Ponant\\" and \\"Western Mediterranean\\" based on the province of departure of the trips, and we grouped foreign ports by means of a manual classification carried out from the states of departure.<br/>Tonnages are calculated from estimates based on ship classes when necessary.","inputs":[],"outputs":["map_backgrounds/intro_map.geojson","styles_navigation_long_cours.csv","styles_navigation_long_cours_ports.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données issues de navigo/flows, destination_function=\\"O\\", source_suite = \\"la Santé registre de patentes de Marseille\\".<br/>Premier flow de chaque voyage (et nombre d\'étapes intermédiaires) retrouvé avec source_doc_id et travel_rank.<br/>Filtrage sur les années de paix (indate_fixed du premier flow différent de \\"1759\\", \\"1779\\", \\"1799\\")<br/>Sélection des ports français des groupes \\"Ponant\\" et \\"méditerrannée occidentale\\" à partir de departure_province selon les règles suivantes :<br/>\'Normandie\': \'Ponant\', <br/>\'Aunis\': \'Ponant\', <br/>\'Guyenne\': \'Ponant\', <br/>\'Languedoc\': \'méditerranée occidentale\', <br/>\'Provence\': \'méditerranée occidentale\', <br/>\'Flandre\': \'Ponant\', <br/>\'Picardie\': \'Ponant\', <br/>\'Corse\': \'méditerranée occidentale\', <br/>\'Bretagne\': \'Ponant\',<br/>\'Roussillon\': \'méditerranée occidentale\'<br/><br/>Sélection des ports étrangers des groupes \\"méditerrannée occidentale\\" à partir de departure_state_1789_fr selon les règles suivantes :<br/>\'Etats pontificaux\': \'méditerranée occidentale\', <br/>\'Hambourg\': \'Ponant\', <br/>\'Monaco\': \'méditerranée occidentale\', <br/>\'Provinces-Unies\': \'Ponant\', <br/>\'Prusse\': \'Ponant\', <br/>\'Grande-Bretagne\': \'Ponant\', <br/>\'République romaine\': \'méditerranée occidentale\', <br/>\'Duché de Massa et Carrare\': \'méditerranée occidentale\', <br/>\'Royaume de Naples\': \'méditerranée occidentale\', <br/>\'Malte\': \'méditerranée occidentale\', <br/>\'République ligurienne\': \'méditerranée occidentale\', <br/>\'Pologne\': \'Ponant\', <br/>\'République de Gênes\': \'méditerranée occidentale\', <br/>\'Autriche\': \'Ponant\', <br/>\'République de Raguse\': \'méditerranée occidentale\', <br/>\'Toscane\': \'méditerranée occidentale\', <br/>\'Danemark\': \'Ponant\',<br/>\'République de Venise\': \'méditerranée occidentale\', <br/>\'Maroc\': \'méditerranée occidentale\', <br/>\'Espagne\': \'méditerranée occidentale\', <br/>\'Empire ottoman\': \'empire ottoman\', <br/>\'Royaume de Piémont-Sardaigne\': \'méditerranée occidentale\', <br/>\'Suède\': \'Ponant\', <br/>\'Portugal\': \'Ponant\', <br/>\'Empire russe\': \'Ponant\', <br/>\'Brême\': \'méditerranée occidentale\', <br/>\'République de Lucques\': \'méditerranée occidentale\'<br/>Tonnages calculés à partir des estimations fondées sur les classes de navire quand nécessaire (https://docs.google.com/spreadsheets/d/e/2PACX-1vTYdeIwpzaVpY_KS91cXiHxb309iYBS4JN_1_hW-_oyeysuwcIpC2VJ5fWeZJl4tA/pub)<br/>"},"impact-guerre-sur-commerce-et-navigation":{"id":"impact-guerre-sur-commerce-et-navigation","partie":"3.A","n_chapitre":3,"lien_permanent_visualisation":"/vizualisation/impact-guerre-sur-commerce-et-navigation","titre_fr":"Impact de la guerre sur la croissance du commerce et de la navigation","titre_en":"Impact of the war on the growth of trade and navigation","description_fr":"Cette visualtion permet de montrer l\'évolution du commerce des principaux ports français au cours du XVIIIe siècle et d\'évaluer le poids relatif des exportations, des importations et du commerce colonial dans cette évolution.","description_en":"This visualization makes it possible to show the evolution of trade in the main French ports during the 18th century and to assess the relative weight of exports, imports and colonial trade in this evolution.","comment_lire_fr":"Les différents graphiques décrivent l\'évolution du commerce des principaux ports français en volume de commerce (en abscisse) en regardant l\'impact que les guerres ont pu avoir sur chacun d\'entre eux, afin de mesurer si cet impact est différent en fonction de la position géographique de ces ports. Afin de mieux comprendre ces évolutions, ils proposent également une lecture ciblant exclusivement les exportations ou les importations. Les trois dernières lignes analysent le commerce de ces ports en ôtant le commerce avec les colonies. En effet, ce dernier est particulièrement touché pendant les guerres du fait de la supériorité de la marine de guerre britannique. Chaque graphique propose deux courbes et deux chiffres qui leur correspondent. Le commerce du port est représenté par la courbe en vert et son évolution moyenne sur l\'ensemble de la période est donnée par le pourcentage indiqué en bleu en haut à gauche. La courbe en rouge décrit le niveau du flux commerce qui aurait existé en l\'absence de conflit (si l\'évolution du commerce avait continué sur le même rythme qu\'avant-guerre) et le chiffre en rouge à droite indique la perte moyenne de commerce due aux guerres sur toute la période. En déplaçant le curseur sur la courbe, vous verrez apparaître le volume de commerce en livres tournois et la perte estimée liée à la guerre (égale à 0 lorsqu\'il n\'y a pas de conflit). Le dernier cadran (navigation de Marseille) intègre des données sur la navigation de Marseille issue de différentes sources: le nombre d\'entrées relevé par Charles Carrière (1973) à partir des dépositions des capitaines; ceux issus de la même source saisis dans Navigocorpus qui permettent 1) d\'ajouter des données pour 1787, 1789 et 1799; 2) d\'indiquer le tonnage total estimé à partir des types de navires ; 3) de représenter les distances parcourues par les navires. Ces trois variables donnent une image différente de l\'impact de la guerre: celui-ci n\'est que de -22,9% en termes de nombre de navires entrés, mais de -44% pour le tonnage, et de -66,4% pour les distances. En d\'autres termes, en temps de guerre, les navires qui entrent à Marseille sont moins nombreux, plus petits, et proviennent des ports plus proches qu\'en temps de paix.","comment_lire_en":"The different graphs describe the evolution of the trade of the main French ports in volume of trade (on the abscissa) by looking at the impact that the wars may have had on each of them, in order to measure whether this impact is different depending on the geographical position of these ports. In order to better understand these developments, they also offer a reading targeting exclusively exports or imports. The last three lines analyze the trade of these ports by removing trade with the colonies. Indeed, the latter is particularly affected during wars due to the superiority of the British navy. Each graph offers two curves and two figures that correspond to them. The port\'s trade is represented by the green curve and its average evolution over the entire period is given by the percentage indicated in blue at the top left. The red curve describes the level of trade flow which would have existed in the absence of conflict (if the evolution of trade had continued at the same pace as before the war) and the red figure on the right indicates the average loss of trade due to wars throughout the period. By moving the cursor on the curve, you will see the trade volume in tournament pounds and the estimated loss linked to the war (equal to 0 when there is no conflict). The last dial (navigation of Marseille) integrates data on the navigation of Marseille from different sources: the number of entries recorded by Charles Carrière (1973) from the captains\' statements; those from the same source entered in Navigocorpus which allow 1) to add data for 1787, 1789 and 1799; 2) to indicate the total tonnage estimated from the types of vessels; 3) to represent the distances traveled by ships. These three variables give a different picture of the impact of the war: it is only -22.9% in terms of number of ships entered, but -44% for tonnage, and -66. 4% for distances. In other words, in times of war, the ships entering Marseille are fewer, smaller, and come from closer ports than in times of peace.","comment_cest_fait_fr":"Les données du commerce de ce graphique sont tirées de la base de données toflit18, agrégées par directions des fermes. Les produits coloniaux sont détectés au moyen de la classification toflit18 \\"product_sitc_simplEN\\" (ici, il s\'agit des produits relevant de la classe \\"Plantation foodstuffs\\" dans cette classification). Les partenaires coloniaux sont repérés au moyen de la classification toflit18 \\"partner_grouping\\" (quand ces derniers correspondent à \\"Outre-mers\\", \\"Afrique\\", \\"Amériques\\", ou \\"Asie\\".<br />Les régressions ont été calculées calculées avec le module python reg, à partir de la régression de l\'évolution de la période de paix précédant chaque guerre.<br />Les données de navigation sont issues de la base navigocorpus Carrière et de : Carrière Charles, Négociants marseillais au XVIIIe siècle. Contribution à l\'étude des économies maritimes, Marseille, Institut historique de Provence, 1973, 2 tomes.","comment_cest_fait_en":"The trade data in this graph are taken from the toflit18 database, aggregated by farm management. Colonial products are detected using the toflit18 classification \\"product_sitc_simplEN\\" (here, these are products falling under the class \\"Plantation foodstuffs\\" in this classification). Colonial partners are identified using the toflit18 classification \\"partner_grouping\\" (when the latter correspond to \\"Overseas\\", \\"Africa\\", \\"Americas\\", or \\"Asia\\".<br />The regressions were calculated with the python reg module, from the regression of the evolution of the period of peace preceding each war.<br />The navigation data comes from the Carrière navigocorpus database and from: Carrière Charles, Marseille merchants in the 18th century. Contribution to the study of maritime economies, Marseille, Historical Institute of Provence, 1973, 2 volumes.","inputs":[],"outputs":["impact-guerre-sur-croissance.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données toflit18 : flows, best_guess_region_prodxpart,  aggrégés par directions des fermes.<br/>Détection des produits coloniaux : product_sitc_simplEN = \\"Plantation foodstuffs\\"<br />Détection des partenaires coloniaux : partner_grouping [\\"Outre-mers\\", \\"Afrique\\", \\"Amériques\\", \\"Asie\\"]<br />Régressions calculées avec le module python reg, à partir de la régression de l\'évolution de la période de paix précédant chaque guerre.<br />Données de navigation issues de Carrière et de navigo (même méthode pour les régressions)."},"guerre-et-navigation":{"id":"guerre-et-navigation","partie":"3.B","n_chapitre":3,"lien_permanent_visualisation":"/vizualisation/guerre-et-navigation","titre_fr":"Qui profite de la guerre en termes de navigation ?","titre_en":"Who benefits from war in terms of navigation?","description_fr":"Cette visualisation montre les changements provoqués par la guerre sur la navigation de Marseille pour ce qui est des acteurs de la navigation (c\'est-à-dire des pavillons des navires qui arrivent à Marseille).","description_en":"This visualization shows the changes caused by the war on the navigation of Marseille in terms of the actors of navigation (i.e. the flags of the ships arriving in Marseille).","comment_lire_fr":"Le diagramme montre sur l\'axe verticale les années se terminant par \\"9\\" pour lesquelles nous avons collecté les données relatives aux navires entrés à Marseille. Elles alternent une année de paix et une année de guerre. L\'axe horizontal indique pour chaque année la distribution de différents groupes de pavillons. La perte en pourcentage pour chaque groupe, entre l\'année de paix et l\'année de guerre qui suit, s\'affiche en survolant le diagramme. Les groupes de pavillons sont différenciés par couleur, en fonction de leur statut lors de la guerre en cours ou de celle qui suit: neutre, français (en distinguant les navires des ports de la France méditerranéenne - \\"France du Levant\\" de ceux de l\'Atlantique - \\"France du Ponant\\"), belligérants alliés de la France, et ennemis de la France. Les données représentent le tonnage estimé agrégé (qui a été calculé sur la base du type de navires), en pourcentage. Elles ne prennent donc pas en compte la diminution globale du tonnage, que nous avons représentée ailleurs. Ainsi, si les navires français des ports méditerranéens ne perdent que quelques points en pourcentage (indiqués en noir \\"pp\\"), la perte est bien plus nette pour les navires de la France atlantique, dont le voyage devient trop risqué. Sans surprise, les pavillons ennemis disparaissent en temps de guerre (sauf pour ce qui est des prises des corsaires ou des navires parlementaires). Le grand gagnant des conflits, ce sont les pavillons neutres, qui accroissent considérablement leur part tant lors de la guerre de Sept Ans (1756-63) que pendant celle d\'Indépendance américaine (1778-1783). Les guerres de la décennie révolutionnaire sont radicalement différentes: en 1799 il n\'y a presque plus de neutres.","comment_lire_en":"The diagram shows on the vertical axis the years ending in \\"9\\" for which we collected data relating to ships entering Marseille. They alternate a year of peace and a year of war. The horizontal axis indicates for each year the distribution of different groups of flags. The percentage loss for each group, between the year of peace and the following year of war, is displayed by hovering over the chart. The groups of flags are differentiated by color, depending on their status during the current or subsequent war: neutral, French (distinguishing the ships from the ports of Mediterranean France - \\"France du Levant\\" from those of the Atlantic - \\"France du Ponant\\"), belligerent allies of France, and enemies of France. The data represents the aggregate estimated tonnage (which was calculated based on vessel type), as a percentage. They therefore do not take into account the overall reduction in tonnage, which we have represented elsewhere. Thus, if French ships from Mediterranean ports only lose a few percentage points (indicated in black \\"pp\\"), the loss is much clearer for ships from Atlantic France, whose journey becomes too risky. Unsurprisingly, enemy flags disappear in time of war (except for the capture of privateers or parliamentary ships). The big winner of the conflicts were the neutral flags, which considerably increased their share both during the Seven Years\' War (1756-63) and during that of American Independence (1778-1783). The wars of the revolutionary decade were radically different: in 1799 there were almost no neutrals left.","comment_cest_fait_fr":"Les données de ce graphique sont produites à partir de la base Navigocorpus, pour laquelle on a sélectionné les flux enregistrés grâce à la source archivistique du registre des patentes de Marseille pour les années 1749, 1759, 1769, 1779, 1787, 1789, et 1799.<br/>Le repérage des statuts des partenaires durant les guerres a été documenté qualitativement année par année par l\'équipe pour les besoins de cette publication.<br/>Les catégorisations sont réalisées en fonction du pavillon pour les navires étrangers, en fonction du lieu de naissance du capitaine pour la distinction entre France du Levant et France du Ponant.<br/>Pour les catégories correspondant à des pays étrangers, on projette sur les années de paix le statut des pays lors de la guerre qui suit afin de mesurer l\'impact du conflit sur la répartition des personnels de navigation.<br/>Les quantifications sont réalisées par tonnage aggrégé, calculé à partir des estimations fondées sur les classes de navire quand c\'est nécessaire.","comment_cest_fait_en":"The data in this graph are produced from the Navigocorpus database, for which we selected the flows recorded using the archival source of the Marseille patent register for the years 1749, 1759, 1769, 1779, 1787, 1789, and 1799 .<br/>The identification of the statuses of partners during the wars was qualitatively documented year by year by the team for the purposes of this publication.<br/>Categorizations are made according to the flag for foreign ships, according to the place of birth of the captain for the distinction between France du Levant and France du Ponant.<br/>For the categories corresponding to foreign countries, the status of the countries during the following war is projected onto the years of peace in order to measure the impact of the conflict on the distribution of navigation personnel.<br/>Quantifications are carried out by aggregate tonnage, calculated from estimates based on ship classes when necessary.","inputs":[],"outputs":["navigation_guerre.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données navigo/pointcalls.<br/>Sélection des années : \\"1749\\", \\"1759\\", \\"1769\\", \\"1779\\", \\"1787\\", \\"1789\\", \\"1799\\" - via date_fixed.<br/>Source_suite = \\"la Santé registre de patentes de Marseille\\".<br/>Utilisation d\'un tableau spécifiant le statut année par année (https://docs.google.com/spreadsheets/d/e/2PACX-1vRxr78qK0zubFIDR7w38JqWOkqD-P6uqZi-pXChSLwYxesUGJwZnxCx-0sYIKKxwr3SJvb5P5HVGW1o/pub)<br/><br/>Catégorisation :<br/>\\"neutre\\", \\"en guerre allié de la France\\", \\"en guerre ennemi de la France\\" : à partir de ship_flag_standardized_fr et du tableau ci-dessus<br/>\\"France du Levant\\" : captain_birthplace dans un port situé dans l\'une des provinces \\"Corse\\", \\"Provence\\", <br/>\\"France du Ponant\\" : tout ce qui n\'est pas Levant<br/>\\"Languedoc\\", \\"Roussillon\\".<br/><br/>Pour les catégories correspondant à des pays étrangers, on projette sur les années de paix le statut des pays lors de la guerre qui suit afin de mesurer l\'impact du conflit sur la répartition des personnels de navigation.<br/><br/>Aggrégation par tonnage, calculés à partir des estimations fondées sur les classes de navire quand nécessaire (https://docs.google.com/spreadsheets/d/e/2PACX-1vTYdeIwpzaVpY_KS91cXiHxb309iYBS4JN_1_hW-_oyeysuwcIpC2VJ5fWeZJl4tA/pub)"},"effets-guerre-sur-commerce-levant":{"id":"effets-guerre-sur-commerce-levant","partie":"3.C","n_chapitre":3,"lien_permanent_visualisation":"/vizualisation/effets-guerre-sur-commerce-levant","titre_fr":"Les effets de la guerre sur les importations du port de Marseille","titre_en":"The effects of the war on imports from the port of Marseille","description_fr":"Les deux graphiques illustrent l\'impact des guerres sur les importations de Marseille détaillées par partenaire. ","description_en":"The two graphs illustrate the impact of wars on Marseille\'s imports detailed by partner. ","comment_lire_fr":"La partie supérieure de la visualisation mesure l\'évolution du commerce par partenaire en valeur absolue (en livres tournois). Les zones grisées correspondent aux périodes de guerre. En plaçant le curseur sur les courbes, on fait apparaître le chiffre exact tiré des statistiques de la balance du commerce. La partie inférieure montre l\'évolution relative pour mieux faire apparaître les changements intervenus pour ce qui est des parts relatives des partenaires pendant les guerres. En plaçant le curseur sur l\'histogramme on fait apparaître le pourcentage exact de chacun des partenaires.","comment_lire_en":"The upper part of the visualization measures the evolution of trade per partner in absolute value (in tournament pounds). The gray areas correspond to periods of war. By placing the cursor on the curves, the exact figure taken from the balance of trade statistics appears. The lower part shows the relative evolution to better show the changes that occurred in the relative shares of the partners during the wars. By placing the cursor on the histogram, the exact percentage of each partner appears.","comment_cest_fait_fr":"Les données du commerce sont tirées de la base de données toflit18, dans laquelle on a sélectionné les imports déclarés par la direction des Fermes de Marseille.<br/>Le groupement des partenaires a été défini manuellement sur la base de la classification toflit18 \\"partner_grouping\\" pour les besoins de cette visualisation spécifique.","comment_cest_fait_en":"The trade data are taken from the toflit18 database, from which we selected the imports declared by the management of Fermes de Marseille.<br/>The partner grouping was manually defined based on the toflit18 classification \\"partner_grouping\\" for the purposes of this specific visualization.","inputs":[],"outputs":["evolution-exports-levant.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données toflit18, best guess region prodxpart, customs_region = Marseille, imports.<br/><br/>Aggrégation par valeur et par partner_grouping selon les règles suivantes :<br/>\\"Italie\\": \\"Italie & Espagne\\",<br/>\\"Espagne\\": \\"Italie & Espagne\\",<br/>\\"Levant et Barbarie\\": \\"Levant & Barbarie\\",<br/>\\"Angleterre\\": \\"Angleterre & Amériques\\",<br/>\\"Amériques\\": \\"Angleterre & Amériques\\",<br/>\\"Nord\\": \\"Nord, Hollande & Flandres\\",<br/>\\"Hollande\\": \\"Nord, Hollande & Flandres\\",<br/>\\"Flandre et autres états de l\'Empereur\\": \\"Nord, Hollande & Flandres\\""},"levant-navigation":{"id":"levant-navigation","partie":"3.C","n_chapitre":3,"lien_permanent_visualisation":"/vizualisation/levant-navigation","titre_fr":"La navigation depuis l’Empire ottoman vers Marseille","titre_en":"Navigation from the Ottoman Empire to Marseille","description_fr":"Cette carte représente le premier port de départ déclaré par les capitaines qui entrent à Marseille depuis un port de l\'Empire ottoman dans les années étudiées.","description_en":"This map represents the first port of departure declared by captains entering Marseille from a port in the Ottoman Empire in the years studied.","comment_lire_fr":"Cette carte montre les ports de départ des capitaines arrivés à Marseille en 1749, 1759, 1769, 1779, 1787, 1789 et 1799 en provenance d\'un port de l\'Empire ottoman. Le cercle est proportionnel au nombre de voyages concernés. En survolant les cercles, l\'infobulle indique le nombre de ceux-ci, le toponyme et le tonnage total agrégé que nous avons estimé à partir du type du navire. Cette carte montre la densité des relations entre Marseille et l\'Empire ottoman, et l\'importance de Smyrne et des ports tunisiens de Tunis et de Bône (aujourd’hui El-Annaba).","comment_lire_en":"This map shows the departure ports of captains arriving in Marseille in 1749, 1759, 1769, 1779, 1787, 1789 and 1799 from a port in the Ottoman Empire. The circle is proportional to the number of trips involved. Hovering over the circles, the tooltip indicates the number of these, the toponym and the total aggregate tonnage that we estimated from the type of vessel. This map shows the density of relations between Marseille and the Ottoman Empire, and the importance of Smyrna and the Tunisian ports of Tunis and Bône (today El-Annaba).","comment_cest_fait_fr":"Les données de cette visualisation sont produites à partir de la base de données Navigocorpus, dans laquelle nous avons sélectionné les flux provenant de la source archivistique du registre du petit cabotage, ou de celle du registre des patentes de Marseille. Dans cette dernière nous avons sélectioné les voyages au départ d\'un port appartenant à l\'Empire ottoman, pour les années 1749, 1759, 1769, 1779, 1787, 1789, ou 1799.<br/>Les tonnages sont calculés à partir des estimations par classe quand c\'est nécessaire.","comment_cest_fait_en":"The data for this visualization are produced from the Navigocorpus database, from which we have selected the flows coming from the archival source of the small cabotage register, or that of the Marseille patent register. In the latter we have selected voyages departing from a port belonging to the Ottoman Empire, for the years 1749, 1759, 1769, 1779, 1787, 1789, or 1799.<br/>Tonnages are calculated from estimates by class when necessary.","inputs":[],"outputs":["map_backgrounds/intro_map.geojson","navigation_depuis_levant.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données navigo, flows, departure_state_1789_fr = \\"Empire ottoman\\", source_suite = \\"\\"Registre du petit cabotage (1786-1787)\\" ou \\"la Santé registre de patentes de Marseille\\".<br/>Sélection des années : 1749, 1759, 1769, 1779, 1787, 1789, 1799<br/>Tonnages calculés à partir des estimations par classe quand nécessaire (https://docs.google.com/spreadsheets/d/e/2PACX-1vTYdeIwpzaVpY_KS91cXiHxb309iYBS4JN_1_hW-_oyeysuwcIpC2VJ5fWeZJl4tA/pub)."},"levant-navigation-guerre":{"id":"levant-navigation-guerre","partie":"3.C","n_chapitre":3,"lien_permanent_visualisation":"/vizualisation/levant-navigation-guerre","titre_fr":"Qui assure la navigation avec le Levant en temps de guerre ?","titre_en":"Who ensures navigation with the Levant in times of war?","description_fr":"Cette visualisation montre les changements provoqués par la guerre sur la navigation de Marseille pour ce qui est des acteurs de la navigation depuis l\'Empire ottoman","description_en":"This visualization shows the changes caused by the war on the navigation of Marseille with regard to the actors of navigation since the Ottoman Empire","comment_lire_fr":"L’axe vertical du diagramme montre les années se terminant par \\"9\\" dont nous avons collecté les données relatives aux navires entrés à Marseille. Elles alternent une année de paix et une année de guerre. Le couleur distingue les différents pavillons, en fonction de leur statut lors de la guerre qui suit: neutre, français (en distinguant les navires des ports de la France méditerranéenne - \\"France du Levant\\" de ceux de l\'Atlantique - \\"France du Ponant\\"), belligérants alliés de la France, et ennemis de la France. Les données représentent le tonnage agrégé estimé (calculé sur la base du type de navires) et sont affichées en pourcentage. Elles ne prennent donc pas en compte la diminution globale du tonnage, que nous avons représentée ailleurs. On constate tout d\'abord que l\'essentiel de la navigation avec l\'Empire ottoman est assuré par des navires français méditerranéens, et ce tant en temps de paix que de guerre (à l\'exception de 1799). La mise en place de convois escortés permet à ainsi de protéger ce commerce des attaques de la Navy et des corsaires britanniques. Les Français des ports méditerranéens perdent certes quelques points en pourcentage (indiqués en noir \\"pp\\") lors des conflits mais ne sont pas supplantés pour autant par les neutres. En 1799, en revanche, le commerce avec l\'Empire ottoman s\'effondre: les pertes pour les Français ne sont pas simplement en parts de marchés (-77%), mais aussi en absolu (ce que le graphique ne montre pas).","comment_lire_en":"The vertical axis of the diagram shows the years ending in \\"9\\" for which we collected data relating to ships entering Marseille. They alternate a year of peace and a year of war. The color distinguishes the different flags, depending on their status during the following war: neutral, French (distinguishing the ships from the ports of Mediterranean France - \\"France du Levant\\" from those of the Atlantic - \\"France du Ponant \\"), belligerent allies of France, and enemies of France. The data represents the estimated aggregate tonnage (calculated based on vessel type) and is displayed as a percentage. They therefore do not take into account the overall reduction in tonnage, which we have represented elsewhere. First of all, we note that most of the navigation with the Ottoman Empire is carried out by French Mediterranean ships, both in times of peace and war (with the exception of 1799). The establishment of escorted convoys thus made it possible to protect this trade from attacks by the Navy and British privateers. The French in Mediterranean ports certainly lose a few percentage points (indicated in black \\"pp\\") during conflicts but are not supplanted by neutrals. In 1799, on the other hand, trade with the Ottoman Empire collapsed: the losses for the French were not simply in market share (-77%), but also in absolute terms (which the graph does not show).","comment_cest_fait_fr":"Les données de cette visualisation sont produites à partir de la base de données Navigocorpus, dans laquelle nous avons sélectionné les flux provenant de la source archivistique du registre du petit cabotage, ou de celle du registre des patentes de Marseille. Dans cette dernière nous avons sélectioné les voyages au départ d\'un port appartenant à l\'Empire ottoman, pour les années 1749, 1759, 1769, 1779, 1787, 1789, ou 1799.<br/>Le repérage des statuts des partenaires durant les guerres a été documenté qualitativement année par année par l\'équipe pour les besoins de cette publication.<br/>Les catégorisations sont réalisées en fonction du pavillon pour les navires étrangers, en fonction du lieu de naissance du capitaine pour la distinction entre France du Levant et France du Ponant.<br/>Pour les catégories correspondant à des pays étrangers, on projette sur les années de paix le statut des pays lors de la guerre qui suit afin de mesurer l\'impact du conflit sur la répartition des personnels de navigation.<br/>Les quantifications sont réalisées par tonnage aggrégé, calculé à partir des estimations fondées sur les classes de navire quand c\'est nécessaire.","comment_cest_fait_en":"The data for this visualization are produced from the Navigocorpus database, from which we have selected the flows coming from the archival source of the small cabotage register, or that of the Marseille patent register. In the latter we have selected voyages departing from a port belonging to the Ottoman Empire, for the years 1749, 1759, 1769, 1779, 1787, 1789, or 1799.<br/>The identification of the statuses of partners during the wars was qualitatively documented year by year by the team for the purposes of this publication.<br/>Categorizations are made according to the flag for foreign ships, according to the place of birth of the captain for the distinction between France du Levant and France du Ponant.<br/>For the categories corresponding to foreign countries, the status of the countries during the following war is projected onto the years of peace in order to measure the impact of the conflict on the distribution of navigation personnel.<br/>Quantifications are carried out by aggregate tonnage, calculated from estimates based on ship classes when necessary.","inputs":[],"outputs":["navigation_levant_guerre.csv"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données navigo/pointcalls.<br/>Sélection des années : \\"1749\\", \\"1759\\", \\"1769\\", \\"1779\\", \\"1787\\", \\"1789\\", \\"1799\\" - via date_fixed.<br/>Source_suite = \\"la Santé registre de patentes de Marseille\\".<br/>state_fr = \\"Empire ottoman\\"<br/>Utilisation d\'un tableau spécifiant le statut année par année (https://docs.google.com/spreadsheets/d/e/2PACX-1vRxr78qK0zubFIDR7w38JqWOkqD-P6uqZi-pXChSLwYxesUGJwZnxCx-0sYIKKxwr3SJvb5P5HVGW1o/pub)<br/><br/>Catégorisation :<br/>\\"neutre\\", \\"en guerre allié de la France\\", \\"en guerre ennemi de la France\\" : à partir de ship_flag_standardized_fr et du tableau ci-dessus<br/>\\"France du Levant\\" : captain_birthplace dans un port situé dans l\'une des provinces \\"Corse\\", \\"Provence\\", <br/>\\"France du Ponant\\" : tout ce qui n\'est pas Levant<br/>\\"Languedoc\\", \\"Roussillon\\".<br/><br/>Pour les catégories correspondant à des pays étrangers, on projette sur les années de paix le statut des pays lors de la guerre qui suit afin de mesurer l\'impact du conflit sur la répartition des personnels de navigation.<br/><br/>Agrégation par tonnage, calculés à partir des estimations fondées sur les classes de navire quand nécessaire (https://docs.google.com/spreadsheets/d/e/2PACX-1vTYdeIwpzaVpY_KS91cXiHxb309iYBS4JN_1_hW-_oyeysuwcIpC2VJ5fWeZJl4tA/pub)"},"fonctionnement-port-franc":{"id":"fonctionnement-port-franc","partie":"annexe","n_chapitre":5,"lien_permanent_visualisation":"/vizualisation/fonctionnement-port-franc","titre_fr":"Le fonctionnement du port franc (1789)","titre_en":"How does the free port work ? (1789)","description_fr":"","description_en":"","comment_lire_fr":"Le graphique montre les valeurs des flux de commerce liés à la Direction des Fermes de Marseille en 1789. Le sens des flèches indique qui est exportateur et qui est importateur. Les données sont abondamment discutées dans l’index.","comment_lire_en":"The graph shows the values ​​of trade flows linked to the Direction des Fermes de Marseille in 1789. The direction of the arrows indicates who is an exporter and who is an importer. The data are discussed extensively in the index.","comment_cest_fait_fr":"Les données de ce diagrammesont tirées de la base de données toflit18 pour l’année 1789, en utilisant le filtre \\"Best Guess customs region product x partner\\" pour identifier les flux pertinents (voir https://toflit18.medialab.sciences-po.fr/#/exploration/sources).","comment_cest_fait_en":"The data in this diagram is taken from the toflit18 database for the year 1789, using the filter \\"Best Guess customs region product x partner\\" to identify relevant flows (see https://toflit18.medialab.sciences-po. fr/#/exploration/sources).","inputs":[],"outputs":["fonctionnement-port-franc-complete.gexf","fonctionnement-port-franc-simplified.gexf"],"cacher_atlas":"","comment_cest_fait_fr_tech":"Données toflit18, année 1789, best_guess_region_prodxpart.<br/>Regroupement à partir de customs_region, partner_simplification, et 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secondary-page",children:[(0,dc.jsx)(ar,{children:(0,dc.jsx)("title",{children:vf(t,i)})}),(0,dc.jsx)("div",{className:"centered-contents",children:(0,dc.jsxs)(Xu.Provider,{value:{onRegisterVisualization:function(e){o({type:"MERGE",payload:{[e.callerId]:{...e}}})},onClickCallerScroll:()=>{},activeCallerId:void 0},children:[(0,dc.jsx)("h1",{children:t}),(0,dc.jsx)(e,{components:{Caller:({id:e})=>(0,dc.jsx)(XT,{id:e,lang:i}),Link:Ve}})]})})]})};function KT(e){const{Caller:t}=e.components||{};return t||function(){throw new Error("Expected component `Caller` to be defined: you likely forgot to import, pass, or provide it.")}(),(0,dc.jsxs)("div",{id:"part-1",children:[(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"intro",mode:"toflit18_world"})}),(0,dc.jsx)("p",{children:"À la veille de la Révolution française, malgré le développement de ses échanges extérieurs vers les espaces atlantique et asiatique, le commerce de Marseille reste profondément ancré en Méditerranée. La carte ci-contre, qui illustre la valeur des exportations et des importations marseillaises telles qu’elles furent enregistrées par le bureau de la balance du commerce, le montre. En 1789, ses deux partenaires privilégiés sont les Etats italiens (notamment le royaume de Naples) et le Levant. Le dynamisme Atlantique existe aussi: le volume des échanges avec les colonies françaises en Amérique (catégorie \"Amériques\" sur la carte) arrive presque au même niveau en 1789. Un autre partenaire important est l’Espagne: les liens de Marseille avec Cadix, nœud de communication obligé avec l'Amérique espagnole, sont anciens et importants. Le commerce avec l’Europe du Nord et la Baltique est plus modeste, et dominé par l'exportation de produits méditerranéens (huile d’olive, etc.). "}),(0,dc.jsx)("p",{children:"Durant la décennie 1780, alors que les échanges avec le Levant déclinent, les flux vers et en provenance des espaces atlantiques et asiatiques connaissent une croissance accélérée. D’une part, la hausse de la demande européenne et levantine en sucre, café, cacao et indigo dynamise les échanges de Marseille avec les colonies françaises des Caraïbes (Guadeloupe, Martinique, Saint-Domingue). D’autre part, l’ouverture du commerce avec les États-Unis, qui viennent d’obtenir leur indépendance en 1783, ont ouvert des marchés nouveaux pour les produits français. Enfin, la suppression du monopole de Lorient en 1769 a ouvert le marché des Indes orientales, (c’est-à-dire la Chine et les comptoirs français en Inde) aux négociants marseillais."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"intro",mode:"navigo_world"})}),(0,dc.jsxs)("p",{children:["Les données relatives aux arrivées de navires à Marseille confirment pour l’essentiel celles de la balance du commerce: elles montrent la part toujours dominante des trafics méditerranéens, en provenance de la péninsule italienne, du Levant et d’Espagne.",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"La navigation méditerranéenne de Marseille est d’ailleurs encore plus significative si on considère que la catégorie «Flandres et États de l’Empereur» comprend en réalité davantage des départs depuis Trieste et Fiume (Rijeka) que depuis Ostende.",children:"?"})," Les navires méditerranéens sont de tonnage moindre par rapport à ceux qui relient le port phocéen aux mondes atlantiques. La carte représente visuellement le tonnage moyen, qui repose sur nos estimations. Au niveau agrégé, les trafics de proximité courts mais fréquents, comme le cabotage en Méditerranée nord-occidentale, tout comme les voyages à plus large rayon dans la Méditerranée centrale et orientale, l’emportent largement sur la navigation océanique."]}),(0,dc.jsxs)("p",{children:["Le port de Marseille possède plusieurs spécificités géographiques et institutionnelles qu’il convient d’explorer pour mieux comprendre les logiques géographiques et économiques qui l’animent en 1789. Ici, il est utile de le mettre en regard du cas de Dunkerque auquel nous avons consacré une ",(0,dc.jsx)("a",{className:"c9",href:"https://medialab.github.io/portic-storymaps-2022/#/fr",rel:"noopener noreferrer",target:"_blank",children:"autre étude"})," dans le cadre du programme Portic",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Voir le site de ce programme ANR.",children:"?"}),". Comme Dunkerque, Marseille est un port franc - c’est-à-dire qu’il bénéficie de privilèges douaniers spécifiques - et sa position géographique lui donne un avantage de proximité avec certains des partenaires commerciaux de la France. Dunkerque a utilisé ses atouts pour devenir, à sa mesure, un port d’entrepôt pour l’Angleterre et l’Europe du Nord. Ses liens commerciaux – même frauduleux – avec le reste de la France forment une partie significative de son activité. En est-il de même pour Marseille ? "]}),(0,dc.jsx)("p",{children:"Pour le savoir, nous suivons trois pistes. Dans un premier temps, nous analyserons le commerce de Marseille sur le temps long, pour souligner qu’elles présentent des caractéristiques différentes de celles des autres ports français. Ensuite nous examinerons le marché du blé pour faire apparaître l’aire commerciale de Marseille qui remonte assez loin dans l’intérieur, notamment le long du Rhône et de la Saône. Finalement, l’examen du mouvement des navires et des marchandises permet de mesurer plus finement l’importance de Marseille pour le Sud-Est de la France. Marseille est intégré à son arrière-pays de manière beaucoup plus puissante que Dunkerque ou La Rochelle."}),(0,dc.jsx)("h2",{id:"h.9aefnfi0kgry",children:"1.A Marseille, un port international important"}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"intro",mode:"toflit18_france"})}),(0,dc.jsx)("p",{children:"La carte ci-contre montre la valeur du commerce de chaque direction des Fermes en 1789: Marseille est en deuxième position, juste derrière Bordeaux. Il lui est même légèrement supérieur en ce qui concerne les importations, mais Bordeaux le dépasse largement en ce qui concerne les exportations, composées pour une part importante de ré-exportations de produits coloniaux (sucre, café) vers l’Europe du Nord."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"intro",mode:"navigo_france"})}),(0,dc.jsxs)("p",{children:["L’activité maritime de Marseille est sans équivalent à la fin de l'Ancien Régime: le nombre de congés délivrés en 1787 à Marseille est plus du double qu’à Bordeaux.",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Le congé est un document légal que tout navire sortant d’un port français doit posséder. Il ne correspond pas exactement au nombre de sorties car, dans certains cas, le congé est valable pour une aller-retour, ou pour une période de quelques mois, voire d’une année (Marzagalli et Pfister, 2014). Si tout navire sortant d’un port français doit être pourvu d’un congé, leur nombre n’est pas parfaitement comparable entre un port et l’autre, dans la mesure où dans certains endroits il existe des congés valables pour une année, quel que soit le nombre d’allers-retours. Ce n’est toutefois pas le cas en Provence, où seuls les petits pêcheurs peuvent bénéficier d’un congé annuel.",children:"?"})," Cet indicateur est toutefois assez approximatif car il additionne des navires de taille très différente. Il est donc utile de comparer aussi les tonnages. Ceux-ci nous sont connus en 1787 pour la plupart des ports français grâce aux registres des congés, mais nous ne disposons, pour Marseille, que du tonnage des navires sortis du port. Nous avons donc procédé à une estimation des tonnages entrés à partir du type de navire, information consignée par le bureau de la Santé de Marseille aussi bien dans les registres des dépositions des capitaines que dans les cahiers du petit cabotage. Cette estimation nous permet d’évaluer le tonnage moyen des navires entrés pour pouvoir comparer approximativement les trafics maritimes de Marseille avec ceux des autres ports français. En raison du très grand nombre de bâtiments assurant une navigation de proximité, le tonnage moyen d’un navire sortant de Marseille est moitié moins élevé que celui d’un navire sortant de Bordeaux, et inférieur à celui des navires desservant Nantes ou Le Havre. Mais comme le nombre de sorties depuis Marseille est plus du double que dans ces autres grands ports, au total les trafics du port de Marseille dépassent en tonnage ceux de n’importe quel autre port métropolitain. "]}),(0,dc.jsxs)("p",{children:["Marseille est donc un des deux ports français les plus importants en 1789. Sa participation dans le système colonial est moindre que celle de Bordeaux; il est en revanche le premier port européen (et levantin) français. Il convient ensuite de se pencher sur l’évolution au cours du XVIIIe siècle. Nous n’avons malheureusement pas de sources aisément mobilisables pour mesurer ce dynamisme avec précision pour ce qui est de la navigation. Les données sur les sorties commencent en 1732, avec les comptes rendus de congés, qui ne fournissent que le nombre de navires par grandes catégories (Marzagalli & Pfister-Langanay, 2011). Pour les entrées, les dépositions des capitaines au bureau de la Santé existent depuis 1709, et précisent origine et cargaison navire par navire, mais ils ne comprennent pas toutes les arrivées",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"La navigation dite du petit cabotage - celle provenant d’une aire comprise entre la Catalogne et la Toscane, Corse incluse, ne transportant pas de passagers ou d’autres produits spécifiques (tels l’huile, le vin, etc.), et n’ayant pas fait de rencontres en mer avec des corsaires - est en effet enregistrée à part. Les cahiers du petit cabotage ne sont conservés qu’à partir de 1786, ce qui les rend inutilisables dans ce cadre.",children:"?"}),". Néanmoins, en dépit de ces inconvénients, la corrélation de deux courbes est très forte (taux de corrélation = 0.89) entre 1732 et 1780 ce qui nous assure que nos statistiques décrivent de manière fiable l’évolution des flux maritimes marseillais."]}),(0,dc.jsx)("p",{children:"Le nombre des congés délivrés à Marseille montre une nette croissance dans les années 1740 (et ce, en dépit de la guerre de succession d’Autriche) et une reprise au lendemain de la guerre de Sept Ans, sur des niveaux nettement plus élevés qu’avant ce conflit. La crise financière liée aux faillites en chaîne des courtiers en 1774, très sensible, est de courte durée. Le port accroît son commerce au XVIIIe siècle en élargissant sa géographie commerciale vers l’Atlantique et l’océan Indien, tout en gardant une position de force dans les marchés méditerranéens et notamment levantins. "}),(0,dc.jsx)("p",{children:"Ces données de navigation présentent néanmoins un défaut pour comprendre ce qui a pu faire la différence à Marseille : elles n’ont pas d’équivalent dans les autres ports français et ne permettent pas d’étude comparative. Nous nous sommes tournés donc vers les données commerciales."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"dynamique-du-commerce",kind:"exports",rows:"Marseille,Bordeaux"})}),(0,dc.jsx)("p",{children:"En 1740, Marseille assure près de 30% des exportations de la France, alors que Bordeaux en représente moins de 10%. Les exportations de textile à destination du Levant connaissant une certaine stagnation à partir des années 1750, puis une baisse sensible dans les années 1770. Toutefois, le trafic de Marseille continue de progresser, tiré par les exportations de denrées coloniales. La place relative de Marseille recule tout de même, au profit de Bordeaux. Alors que les exportations françaises croissent de 1,3% par an entre 1740 et 1789, celles de Marseille entre 1740 et 1780 n’augmentent que de 0,4% par an et celles de Bordeaux... de 3,2% par an."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"dynamique-du-commerce",kind:"exports",rows:"Marseille, Bordeaux, Rouen, Nantes, La Rochelle"})}),(0,dc.jsx)("p",{children:"L’analyse de la tendance de la croissance des exportations principales régions françaises vient renforcer l’idée que Marseille était un port important au début de la période et que sa position s’est légèrement dégradée au cours du siècle au bénéfice de Bordeaux. Certes, Marseille est devenu le deuxième port colonial en France, à parité avec Nantes, mais loin derrière Bordeaux. Le moindre dynamisme du port phocéen dans ce secteur spécifique qui soutient l’envol de Bordeaux, a plusieurs raisons. La distance aux Antilles est un peu plus importante que pour les ports Atlantiques, elle est surtout plus éloignée des principaux marchés de réexportation pour les produits coloniaux français, qui se trouvent dans le nord de l’Europe; enfin, Marseille ne pratique que le commerce en droiture puisque les négociants ont fait le choix de ne pas participer au commerce triangulaire."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"dynamique-du-commerce",kind:"imports",rows:"Marseille, Bordeaux, Rouen, Nantes, La Rochelle"})}),(0,dc.jsx)("p",{children:"Le succès de Marseille après 1815 ne s’inscrit donc pas dans la continuité de sa dynamique du XVIIIe siècle."}),(0,dc.jsx)("h2",{id:"h.s8r3lug8yvf9",children:"1.B Marseille, un hub méditerranéen du blé "}),(0,dc.jsx)("p",{children:"Puisque l’importance de Marseille semble plutôt liée à sa situation d’importateur, plutôt que sa connexion avec les marchés extérieurs en forte croissance que sont les colonies françaises, il est intéressant d’étudier de manière plus précise ces caractéristiques en analysant sa zone d’influence en France. Malheureusement, les sources pour mesurer les relations économiques à l’intérieur du Royaume sont plus rares que celles pour mesurer les relations économiques à l’extérieur. Une mesure traditionnelle de l’importance des relations bilatérales entre les différentes régions est la synchronicité des fluctuations des prix, notamment pour le produit le plus important des économies pré-industrielles : le blé."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{colorby:"community",id:"correlation-prix",layout:"network"})}),(0,dc.jsxs)("p",{children:["Nous disposons pour cette étude des données rassemblées par Federico, Schulze et Volckart (2021). Ils disposent de prix annuels du blé pour 129 villes en France entre 1209 et 1940, mais seules 108 sont incluses dans cette analyse car nous restreignons l’étude à la période 1716-1815. Nous calculons des corrélations entre le prix du blé dans chaque paire de villes puis utilisons cette valeur comme une mesure de proximité. Nous utilisons ensuite un algorithme pour déterminer des groupes de villes. Le résultat est affiché dans le réseau ci-contre. Les liens n’y sont représentés que si la corrélation entre deux villes est supérieure à 0,87 (0,87 = 3,5^0,5-1). Marseille se place dans un groupe qui se différencie de ceux dans lesquels sont placés Rouen, Nantes, Orléans, Issoire et Bordeaux.",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Les positions dans le réseau, décidées par l’algorithme, ne sont pas géographiques. Elles sont simplement le fruit de la proximité du comportement des prix du blé entre chaque ville. Ainsi, deux villes ayant presque les mêmes prix du blé seront voisines dans le réseau.",children:"?"})," "]}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{colorby:"bassin",id:"correlation-prix",layout:"geography"})}),(0,dc.jsx)("p",{children:"Pour comprendre ces corrélations, nous pouvons reporter les villes sur la carte des six principaux bassins versants français. Les villes de notre étude sont réparties sur tout le territoire et représentent tous les bassins versants. Dans la carte ci-contre, les villes sont colorées suivant leur appartenance à l’un ou à l’autre. "}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{colorby:"community",id:"correlation-prix",layout:"geography"})}),(0,dc.jsx)("p",{children:"Nous pouvons maintenant comparer les groupes issus de notre analyse du réseau des villes obtenu en utilisant la corrélation comme une mesure de proximité d’une part et des bassins versants d’autre part. C’est ce que fait la carte ci-contre. Les groupes de Rouen, Bordeaux, Nantes et Issoire sont assez cohérents et correspondent respectivement à la Normandie et la vallée de la Seine, le Sud-Ouest (bassin Adour-Garonne), la Bretagne et le sud de la Loire et l’Auvergne. Le groupe d’Orléans est moins géographiquement cohérent, et les bassins Rhin-Meuse et Artois-Picardie sont dispersés entre plusieurs groupes. "}),(0,dc.jsx)("p",{children:"Le groupe de Marseille correspond assez exactement à l’ensemble du vaste bassin Rhône-Méditerranée, hors Carcassonne et Narbonne (qui, en partie sans doute à cause du canal du Midi, regardent plus en direction de Bordeaux). Sa cohérence (il n’y a pas de discontinuité géographique contrairement au groupe d’Orléans) suggère que les flux des échanges commerciaux du port de Marseille irriguent une vaste zone économique dépendante de Marseille. "}),(0,dc.jsxs)("p",{children:["Il serait intéressant d’effectuer le même travail pour des produits moins pondéreux que le blé. Les sources manquent pour le faire sur l’ensemble du pays. Ce qu’il est possible, par contre, c’est de comparer l’évolution des valeurs unitaires des biens importés",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Les biens exportés sont trop différents entre chaque port pour que l’analyse soit intéressante.",children:"?"})," dans les cinq ports du Royaume pour lesquels nous avons des données sur une période assez longue: Nantes, Marseille, Bordeaux, Bayonne et La Rochelle. Ce travail a été fait par Daudin et Pingnède (2021). Ils montrent que les prix marseillais sont peu corrélés avec ceux des autres ports et que, surtout, cette corrélation décline au cours du temps, alors que les quatre ports de la façade atlantique voient augmenter toutes leurs corrélation bilatérales. "]}),(0,dc.jsx)("h2",{id:"h.o2phdo3p8par",children:"1.C Marseille, porte du Sud-Est de la France "}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"marseille-port-structurant"})}),(0,dc.jsx)("p",{children:"Nous venons de voir que la conjoncture commerciale de Marseille était assez différente de celle des autres ports français. Par ailleurs, l’étude de la structure des prix des blés en France suggère que Marseille domine économiquement un arrière-pays très vaste. Dans cette section, nous allons essayer de comprendre la manière dont Marseille s’insère dans des logiques économiques d’échelles variées au niveau national."}),(0,dc.jsxs)("p",{children:["La première échelle est celle du pourtour méditerranéen. Elle peut être analysée à partir de données collectées dans le cadre du programme Portic. Quelle est la part des navires partant des autres ports français en Méditerranée qui déclare Marseille comme destination ? La comparaison entre le nombre des congés délivrés dans chaque port du Sud-Est en 1789 (où par Sud-Est nous entendons les ports de Provence, Languedoc, du Roussillons et de la Corse) et le nombre des entrées à Marseille en provenance de chacun de ces ports démontre l’attractivité de Marseille. Il ne s’agit pas d’un port marginalisé dans sa propre région comme peut l’être celui de ",(0,dc.jsx)("a",{className:"c9",href:"https://medialab.github.io/portic-storymaps-2021/fr/",rel:"noopener noreferrer",target:"_blank",children:"La Rochelle"}),". Les ports de Provence (Toulon, Saint-Tropez, Arles, Fréjus, Bandol, Sanary-sur-Mer, Bormes et La Seyne) sont manifestement dans l’orbite de la cité phocéenne. Le cas de Cassis ou des Bormes, où tous les congés délivrés correspondent à des entrées à Marseille, sont les plus emblématiques. "]}),(0,dc.jsx)("p",{children:"En revanche, les trafics de Sète et Narbonne, tous deux situés en Languedoc, sont moins dépendants de Marseille - c’est également ce qui était ressorti de l’examen des corrélations du prix du blé. Les ports du Roussillon (Collioure, Port-Vendres et Saint-Laurent-de-la-Salanque) et la Corse sont encore moins liés à Marseille."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{colonies:"oui",id:"exportations-sud-est",inconnu:"oui"})}),(0,dc.jsxs)("p",{children:["La seconde source que nous pouvons utiliser fournit l’origine des produits exportés en 1789 par la Direction des Fermes de Marseille. Elle comprend aussi les bureaux d’Arles, La Ciotat, La Penne, Lambesc et Septèmes (voir Annexe), mais les exportations vers l’étranger de ces autres bureaux sont très faibles par rapport à l’origine des produits exportés de la France dans son ensemble. Les données de la Balance du Commerce confortent les données de navigation. Cependant, pour des raisons probablement liées au fonctionnement du port franc (voir ce ",(0,dc.jsx)("a",{className:"c9",href:"https://medialab.github.io/portic-storymaps-2023/#/fr/atlas/fonctionnement-port-franc",rel:"noopener noreferrer",target:"_blank",children:"graphique"}),' qui donne une idée de la multiplicité et de la complexité des sources), nous ne disposons de l’origine des produits exportés par Marseille que pour moins de la moitié de ses exportations. Sur 80 M. de lt d’exportations, 42 M. sont donc d’origine "inconnue", alors que 25 M. viennent des colonies. Les 15 M. restants sont dominés par les produits provençaux (9 M.) et lyonnais (1.5 M.). En raison de ces lacunes, il est donc nécessaire d’aller au-delà des sources pour pouvoir analyser le lien entre Marseille et son arrière-pays. ']}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"exportations-sud-est"})}),(0,dc.jsxs)("p",{children:["Pour aller plus loin, nous émettons deux hypothèses. D’une part, il n’y a pas de produits coloniaux parmi les produits d’origine inconnue. C’est plausible, car les ré-exportations coloniales sont tirées d’un document qui leur est propre. D’autre part, l’origine des produits d’origine inconnue se répartit suivant les mêmes proportions que l’origine des produits d’origine connue. Nous ne disposons pas de raisons de penser que ce n’est pas le cas.",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"À vrai dire, les origines inconnues ne sont pas dispersées aléatoirement dans les différents bureaux de Marseille. Marseille - Domaine d'Occident et Marseille, Poids et Casse n’en déclarent jamais (et il y en a une poignée dans les exportations de Marseille). Mais nous n’avons pas percé le mystère de la règle de répartition des différents flux d’exportation dans ces différentes sources.",children:"?"})," "]}),(0,dc.jsx)("p",{children:"Si on accepte ces deux hypothèses, il faut multiplier par 3,8 (57 M d’exportations d’origine non-coloniales / 15 M d’exportations connues) les montants des exportations connues. Marseille exporterait donc 34,2 M de produits venant de Provence (34,2=9×3,8). C’est plus que les exportations connues venant de Provence de toute la France (14.5 M), mais cet écart peut tout à fait être expliqué par les 61 M d’exportations françaises d’origine inconnue. Restent donc 5,5 M. de produits venant de Provence dont on sait qu’ils ne sont pas exportés par Marseille (5,5=14,5-9). AInsi 86% des produits provençaux exportés par la France (0,86=34,2/(34,2+14,5-9)) passeraient par Marseille."}),(0,dc.jsx)("p",{children:"Appliquons le même raisonnement pour le Lyonnais: Marseille exporterait 5,7 M de lt de produits originaires de cette région (5,7=1,5×3,8). La France exporte 24 M. de produits de cette région. Donc 20% des produits originaires du Lyonnais exportées (0,2=5,7/(24+5,7-1,5) passeraient par Marseille. Par le même raisonnement, elle exporte 2,85 M de lt de produits du Languedoc (2,85= 0,75×3,8), soit 19% des exportations totales (0,19=2,85/(12,7+2,85-0,75)). Elle exporte aussi 18% des produits originaires d’Île de France (0,18=0,5×3,8/(9+0,5×3,8-0,5)) et 25% des produits originaires du Dauphiné (0,25=0,15×3,8/(1,85+0,15×3,8-0,15)."}),(0,dc.jsx)("p",{children:"Marseille est manifestement le principal relais de son arrière-pays provençal vers l’étranger. Par contre, les provinces avec lesquelles elle a un marché des blés intégré (Languedoc, Lyonnais et Dauphiné) ne l’utilisent pas - du moins à la fin de l’Ancien Régime - comme port d’exportation majoritaire, peut-être parce qu’elles assurent elles-mêmes leur commerce vers les voisins espagnols, italiens et suisses. Elle est sans doute aussi la voie d’exportation des produits du bassin de l’Île de France vers la Méditerranée. "})]})}function QT(e){return(0,dc.jsxs)("div",{id:"part-1",children:[(0,dc.jsx)("p",{children:"Au vu de l’existence d’un port franc, est-ce que Marseille est intégré à l’économie français ou plutôt elle domine le marché du Sud-Est ? Est-ce que le fait que Marseille soit relativement autonome par rapport au marché français mais ait eu une forte emprise sur le Sud-Est est un facteur de force ? Plus grande autonomie par rapport aux dynamiques françaises. GD : Sans elle, notre question n’a pas de sens puisque Marseille serait trop lié à la France"}),(0,dc.jsx)("p",{children:"caractéristiques de Marseille: participent peu à dynamiques qui caractérisent les autres ports français"}),(0,dc.jsx)("p",{children:"présence des Provençaux dans la navigation de Marseille -> Marseille port méditerranéen"}),(0,dc.jsx)("h2",{id:"h.wwcfzm6r9k8n",children:"(Intro C passe ici et devient I.A) : Pas exceptionnel du côté de la croissance1.A Intégration de Marseille au reste du royaume vu par les prix (devient le 1B)"}),(0,dc.jsxs)("p",{children:["Est-ce que les prix de Marseille évoluent à court/moyen terme comme ceux du reste de la France ? Intégration de Marseille par rapport au reste de l’économie vue par les prix ?Une évolution des prix différente qu’ailleurs en France: La co-évolution des prix pour certains types de produits démontre l’intégration de Marseille dans le commerce du royaume ? (voir article ",(0,dc.jsx)("a",{className:"c12",href:"https://drive.google.com/file/d/1-X-be9zeDtCVx6S80eKV-6MaCQuwx039/view?usp%3Dshare_link",rel:"noopener noreferrer",target:"_blank",children:"Daudin"}),")"]}),(0,dc.jsx)("p",{children:"Paramètres (voir projet gephi sur le git) : "}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"liens créés avec : (corrélation + 1) au carré"}),(0,dc.jsx)("li",{children:"filtré les liens > 3.5 (max 4)"}),(0,dc.jsx)("li",{children:"couleur = modularité"}),(0,dc.jsx)("li",{children:"spatialisation ForceAtlas 2"})]}),(0,dc.jsx)("p",{children:"Nous avons ensuite annoté la visualisation avec les cours d’eau qui semblent prépondérants dans l’interprétation des corrélations de prix :"}),(0,dc.jsx)("p",{children:"Nous avons ensuite étudié le réseau des corrélations pour un ensemble réduits de ports français (1714-1789) : "}),(0,dc.jsx)("h2",{id:"h.o2phdo3p8par",children:"1.B Marseille, porte du sud-est de la France "}),(0,dc.jsx)("p",{children:"(sud-est = Provence, Languedoc, Lyonnais, Corse et Roussillon)"}),(0,dc.jsx)("p",{children:"NB: Expliquer fonctionnement de la Ferme/port franc"}),(0,dc.jsx)("p",{children:"montrer importance de l’hinterland (pour quels produits ?)"}),(0,dc.jsx)("p",{children:"montrer importance du petit cabotage"}),(0,dc.jsx)("p",{children:"montrer l’importance des transporteurs locaux"}),(0,dc.jsx)("p",{children:"NB: Dans cette partie il faudrait aussi expliquer le fonctionnement du port franc:"}),(0,dc.jsx)("p",{children:"Il y a un souci avec la compréhension du fonctionnement du port franc de Marseille. Voir les commentaires de Pierre et Guillaume:"}),(0,dc.jsx)("p",{children:"Expliquer le fonctionnement du port franc. Mystère des différents bureaux. déclarés par Toflit18 1789..:"}),(0,dc.jsx)("p",{children:"Hors 1789 & Importations : "}),(0,dc.jsx)("p",{children:'Toujours "Marseille"'}),(0,dc.jsx)("p",{children:"Exports de 1789, des bureau que nous avons rassemblés"}),(0,dc.jsx)("p",{children:'"Marseille" (2202 flux en 1789)'}),(0,dc.jsx)("p",{children:'MDO "Marseille - Domaine d\'Occident" (1359)'}),(0,dc.jsx)("p",{children:'MPC "Marseille – Poids et Casse" (203 flux)'}),(0,dc.jsx)("p",{children:'"Marseille" : utilisé seulement par F2B14 tableaux 5 et 20, pour les exportations vers l’Afrique, les Amériques et le Monde (ré-exportations de produits coloniaux")'}),(0,dc.jsx)("p",{children:'MPC "Marseille -- Poids et Casse" : 202 flux d’ exportations vers la France (AN F12 1666) + 1 exportation vers l’Asie (ANOM F2B14 tableau 28)'}),(0,dc.jsx)("p",{children:'Que vers "Marseille" et que des produits français'}),(0,dc.jsx)("p",{children:'MDO "Marseille – Domaine d’Occident" : le reste'}),(0,dc.jsx)("p",{children:"Dont 2 exportations vers l’Asie d’ANOM F2B14 tableau 28"}),(0,dc.jsx)("p",{children:"Ce fameux tableau 28 porte sur le commerce des particuliers vers l’Asie (y compris en fait des envois de la Compagnie ?)"}),(0,dc.jsx)("p",{children:"Et 120 exportations vers la France (aussi AN F12 1666)"}),(0,dc.jsx)("p",{children:'Les grandes catégories de produits sont présentes dans "MDO" et "MPC"'}),(0,dc.jsx)("p",{children:"Ne correspond pas à ce que dit Rambert : "}),(0,dc.jsx)("p",{children:"- MDO n’est d’après lui que du colonial"}),(0,dc.jsx)("p",{children:"- MPC est d’après lui le plus actif et porte sur tout ce qui est vendu à Marseille."}),(0,dc.jsx)("p",{children:"Mystère à éclairer."}),(0,dc.jsx)("p",{children:"Il faudrait comparer les exportations de MDO vers la France avec les flux miroirs, et peut-être celle de MPC avec les flux miroirs. Y a-t-il double compte ou régime douanier différent ?"}),(0,dc.jsx)("p",{children:'Rambert, tome IV, p. 225: "Les plus importants [bureaux, ndr] étaient au nombre de trois: le bureau du fameux droit de 20% perçu au profit de la Chambre de Commerce en même temps que le droit de Consulat; le bureau des fermes du domaine d\'Occident qui percevait un droit de 3% sur les marchandises d\'origine coloniale [je comprends = importations depuis les colonies, ndr], enfin le bureau du Poids et Casse, où 75 peseurs publics procédaient au pesage des marchandises vendues sur place et percevaient au profit du Roi un droit qui avait été doublé en 1669. Note 1: Colbert avait pris cette mesure pour donner au Roi une compensation aux pertes subies par l\'application de l\'édit du port franc. [Donc, j\'interprète: droit sur toutes les marchandises vendues à Marseille, ndr]. C\'était le bureau le plus actif; il délivrait les acquits-à-caution, recevait les manifestes des capitaines et faisait visiter les colis à leur débarquement, percevait les droits sur les marchandises étrangères envoyées directement de Marseille aux colonies françaises et plombait celles qui étaient expédiées en transit [Je ne sais pas si Rambert dit "le plus actif" pour dire "celui qui fait plus d\'opérations" ou pour dire "toutes les marchandises passent par là", comme il devrait être, vu qu\'il parle de "toutes les marchandises vendues à Marseille"]".'}),(0,dc.jsxs)("p",{children:["Pour ces informations, Rambert presque recopie ce qui avait écrit Julliany en 1812 : ",(0,dc.jsx)("a",{className:"c12",href:"https://books.google.sm/books?id%3DB43FQMyap0sC%26printsec%3Dfrontcover%26hl%3Dit%26source%3Dgbs_vpt_read#v%3Donepage%26q%26f%3Dfalse",rel:"noopener noreferrer",target:"_blank",children:"https://books.google.sm/books?id=B43FQMyap0sC&printsec=frontcover&hl=it&source=gbs_vpt_read#v=onepage&q&f=false"})]}),(0,dc.jsx)("p",{children:"Guillaume: D’après mon étude pour les escargots du datascape dunkerque, je n’ai pas l’impression qu’il y ait des doubles comptes. Voir Présentation Données Marseille dans Toflit18.pptx et Pour graphiques escargots.do et Pour graphiques escargots.log. Hypothèse: MPC représente des biens français qui ont été mis à l’entrepôt et en sortent pour la consommation locale de Marseille."}),(0,dc.jsx)("p",{children:"Regarder les stats pour 1789 (origine des exports)"}),(0,dc.jsx)("p",{children:"Ci-dessus : "}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"Liens roses = Marseille rapporteur"}),(0,dc.jsx)("li",{children:"Liens verts = France rapporteur"}),(0,dc.jsx)("li",{children:"network_bureaux_with_mirrors.png"})]}),(0,dc.jsx)("p",{children:"Ci-dessus : "}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"Liens roses = Marseille rapporteur"}),(0,dc.jsx)("li",{children:"Liens verts = France rapporteur"}),(0,dc.jsx)("li",{children:"network_bureaux_with_mirrors_simplified.png"})]}),(0,dc.jsx)("p",{children:"Titre: Nombre de congés des ports du Sud-Est et par province en 1789"}),(0,dc.jsx)("p",{children:"Titre: Ratios entre le nombre de navires arrivant à Marseille et le nombre total des congés de ports de la région en 1789. NB: les ports dont le ratio est > 101% ne figurent pas ici: Bormes et Cassis. "}),(0,dc.jsx)("p",{children:"Titre: Ratios entre le nombre de navires arrivant à Marseille et le nombre total des congés de ports de la région en 1789. "}),(0,dc.jsx)("p",{children:"La comparaison entre le nombre des congés de chaque port du Sud-Est en 1789 et le nombre des entrées à Marseille en provenance de chacun de ces ports démontre l’attractivité de Marseille. Les ports les plus polarisés par la cité phocéenne se situent en Provence (Toulon, Saint-Tropez, Arles, Fréjus, Bandol, Sanary-sur-Mer, Bormes et La Seyne) et en Corse. Le cas de Cassis, petit port très proche de Marseille, est le plus emblématique parmi les ports provençaux qui pouvaient sans doute bénéficier, comme c’est le cas en Normandie et en Bretagne, d’un congé annuel pour les trafics intérieurs à la province, ce qui permettait de nombreux allers-retours vers Marseille qui n’apparaissent qu’une seule fois parmi les congés. "}),(0,dc.jsx)("p",{children:"En revanche, Sète et Narbonne, tous deux situés en Languedoc, sont nettement moins polarisés par Marseille. Par conséquent, l’attractivité de Marseille pour le commerce des ports du Sud-Est semble plus forte dans sa propre province, la Provence, que dans la province voisine, le Languedoc. Les ports du Roussillon (Collioure, Port-Vendres et Saint-Laurent-de-la-Salanque) sont encore moins liés à Marseille. Ces données confortent celles de la balance du commerce quant à l’origine des produits exportés par Marseille en 1789."})]})}function JT(e){const{Caller:t}=e.components||{};return t||function(){throw new Error("Expected component `Caller` to be defined: you likely forgot to import, pass, or provide it.")}(),(0,dc.jsxs)("div",{id:"part-2",children:[(0,dc.jsx)("p",{children:"La diversification du commerce est une autre explication possible de la résilience de Marseille au XIXe siècle ? La diversification recouvre en réalité trois types de phénomènes. Elle peut renvoyer aux produits: une économie diversifiée est plus à même de résister à des chocs politiques et économiques majeurs. Elle peut renvoyer aux hommes, ici les acteurs du commerce. Enfin, elle peut désigner la diversité des types de navigation."}),(0,dc.jsx)("h2",{id:"h.ipbpmiriq4tr",children:"2.A Diversité des produits du commerce de Marseille"}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"diversite-produits-exportes"})}),(0,dc.jsx)("p",{children:"Pour étudier la diversité des exportations de Marseille, nous calculons des indices de Herfindahl : il s’agit de la somme des carrés de la part de chaque produit, suivant une classification unifiée en cent-cinquante produits au cours des années et des ports. Cet indice est égal à un si un seul produit constitue toutes les exportations, et est proche de zéro si tous les produits ont la même part de marché. De ce point de vue, Bordeaux est exceptionnel en 1750 : son indice est de 75% alors que les autres ports ont des indices entre 23% (Bayonne) et 40% (Nantes). Ceci est dû à la forte spécialisation de ses exportations sur un petit nombre de marchandises: le vin et les produits coloniaux (café, sucre)."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{annee:"1750",id:"diversite-produits-exportes"})}),(0,dc.jsx)("p",{children:"Cette hiérarchie évolue peu au cours du siècle. La Rochelle devient un port d’exportation très spécialisé (72% en 1789), dépassant même Bordeaux en cette année (qui descend exceptionnellement à 54%). Marseille devient le port le plus diversifié (entre 27 et 29% entre 1775 et 1789), alors que Bayonne perd de la diversification durant la guerre d’Indépendance américaine, Rouen passe au-dessus de 40% et Nantes fluctue autour de 40%. "}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{annee:"1789",id:"diversite-produits-exportes"})}),(0,dc.jsx)("p",{children:"Marseille est donc le moins concentré des ports d’exportation en 1789 et surtout c’est le port qui connaît une diversification grandissante au cours du siècle. Il contraste fortement avec Bordeaux et La Rochelle qui sont très spécialisés ou le deviennent au cours du siècle. Il faut toutefois noter que Marseille n’est pas beaucoup plus diversifiée que certains ports de l’Atlantique, notamment Bayonne, mais Marseille a un volume de commerce beaucoup plus important que ce dernier. "}),(0,dc.jsx)("h2",{id:"h.5xt17flpsq8c",children:"2.B Diversité des acteurs de la navigation de Marseille"}),(0,dc.jsx)("p",{children:"Est-ce que la particularité de Marseille, et un facteur de sa résilience, est à rechercher plutôt du côté d’une présence d’acteurs plus diversifiés qu’ailleurs dans son commerce maritime, et/ou à une participation directe plus importante des Provençaux dans sa navigation ? Ces facteurs interrogent la question des retombées de l’existence de ce grand port méditerranéen pour le Royaume. "}),(0,dc.jsxs)("p",{children:[(0,dc.jsx)(t,{id:"part-des-etrangers-dans-navigation"})," "]}),(0,dc.jsx)("p",{children:"Les navires étrangers sont présents de manière significative dans l’ensemble des premiers ports français (représentés ici par importance du tonnage total). Certes, les données de Marseille ne sont pas comparables avec celles des autres ports, car elles prennent en compte la seule source des déclarations des capitaines à l’arrivée (3290 entrées, sur un total connu de 4557 congés délivrés), alors que pour les autres ports, il s’agit des sorties; aussi et surtout, les tonnages marseillais sont issus d’estimations à partir du type de navires, alors que pour les autres ports, ils sont connus grâce aux registres des congés. Les ordres de grandeur sont toutefois vraisemblables: le pourcentage des congés étrangers délivrés à Marseille, connu grâce aux comptes rendus de l’ensemble des congés délivrés, est de 29,4% (1341 congés sur 4557), soit sensiblement le même pourcentage que l’on trouve via l’estimation des tonnages. "}),(0,dc.jsx)("p",{children:"Ces données comprennent toutes les destinations (ou, pour Marseille, les origines), y compris celles réservées par la législation aux transporteurs nationaux (cabotage, commerce colonial) et celles où les droits sur les étrangers deviennent de facto prohibitifs (Levant, pêche hauturière). En général, dans la France d’Ancien Régime, la navigation sur laquelle ce type de contraintes ne pèse pas - pour l’essentiel, les trafics internationaux avec l’Europe-, est largement tributaire des services de transport des flottes étrangères. Or, nous constatons que les navires français assurent à Marseille une partie des trafics bien plus importante que dans d’autres grands ports éloignés des frontières, comme Bordeaux ou Le Havre, où la moitié des tonnages est étrangère. "}),(0,dc.jsxs)("p",{children:[(0,dc.jsx)(t,{id:"part-des-francais-dans-provenance"})," "]}),(0,dc.jsx)("p",{children:"Cette caractéristique marseillaise se cumule avec une autre spécificité significative. Le port phocéen attire un nombre de pavillons étrangers différents plus élevé que partout ailleurs (20 nationalités en 1787). Le graphique permet de voir, pour les principaux marchés, la part de la navigation effectuée par les Français et le tonnage total estimé. Cette part demeure importante y compris sur des marchés extérieurs qui sont partout ailleurs dominés par les transporteurs étrangers. "}),(0,dc.jsx)("p",{children:"En se limitant à l’analyse des années de paix dont nous avons collecté les données représentées ici, on constate que les navires français gèrent une partie écrasante (plus de 90%) du trafic maritime entre Marseille et les autres ports de France - commerce certes réservé aux nationaux -, tout comme avec l’Empire ottoman, marché privilégié du port phocéen. Sous fond d’une importante croissance des volumes concernés par ces deux secteurs protégés (partie inférieure du graphique, qui indique les tonnages cumulés), la part du pavillon français ne change pas de manière significative au fil du temps: les armateurs français savent donc faire face à la hausse des besoins de services de transport. "}),(0,dc.jsx)("p",{children:"Pour ce qui est des liaisons avec les ports de la péninsule italienne et de l’Espagne, marchés primordiaux pour Marseille, les navires français réussissent à assurer un peu moins de la moitié des trajets environ, ce qui est remarquable, si on considère par exemple que les liaisons entre Bordeaux et les villes hanséatiques, essentielles à la prospérité bordelaise, sont presque exclusivement assurée par des navires nordiques (hollandais, hanséatiques, scandinaves pour l’essentiel). Si les Français perdent de parts sur les marchés ibériques et stagnent, ils parviennent à accroître le tonnage total, et à conserver leurs positions dans la péninsule italienne."}),(0,dc.jsx)("p",{children:'La navigation depuis les pays "Nordiques" (ici, nous avons mis en évidence les départs depuis des ports britanniques et néerlandais) est minime en valeur absolue, et elle est largement gérée par les étrangers: la présence des Français en provenance des ports sous souveraineté britannique est due aux navires qui reviennent de la pêche sédentaire à Terre-Neuve. Le commerce avec les Provinces-Unies - comme du reste avec toute l’Europe du Nord et la Baltique - échappe entièrement aux armateurs français. '}),(0,dc.jsx)("h2",{id:"h.agycgsyuh378",children:"2.C La coexistence de styles de navigation différents "}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"styles-navigation"})}),(0,dc.jsxs)("p",{children:["Il est possible que le principal élément de robustesse de Marseille vienne de la diversification de ses trafics maritimes, c’est-à-dire la coexistence de logiques de navigation différentes. Pour approfondir cet aspect, nous avons voulu interroger la navigation marseillaise de long cours à partir de ses caractéristiques, en se focalisant sur trois différents marchés : celui de la Méditerranée occidentale",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Nous y incluons aussi les voyages en provenance des ports italiens et autrichiens en Adriatique, ainsi que ceux de la façade atlantique de l’Espagne du du Maroc.",children:"?"}),", celui de l’Empire ottoman",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Y compris donc les régences d’Alger, Tunis, et Tripoli en Afrique du Nord et le Moyen-Orient, ainsi que les ports russes sur la mer Noire. Le fond de carte présente des erreurs, les frontières des régences étant celles de Etats contemporains, et le Moyen Orient ne s’affiche pas en vert.",children:"?"})," et celui du Ponant",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Tous les ports européens situés en Atlantique, mer du Nord et mer Baltique (Espagne exclue).",children:"?"}),". Ces marchés correspondent à des logiques de navigation différentes, que la visualisation ci-contre permet d’apprécier pour les années de paix dont nous avons collecté les données (1749, 1769, 1787, 1789). "]}),(0,dc.jsx)("p",{children:'Nous avons représenté le nombre de voyages total pour ces quatre années qui nous sont livrés par les registres des dépositions des capitaines auprès du Bureau de la Santé de Marseille. Le graphique permet d’apprécier la distribution des tonnages, estimés à partir du type d’embarcation, et le nombre d’étapes intermédiaires entre le port de départ et l’arrivée à Marseille. Il s’agit de mettre en avant la pluralité de manières de gérer le transport maritime, et de suggérer que celle-ci a pu contribuer à accroître la capacité de résilience du port phocéen: la variété d’embarcations, la large palette de styles de navigation, comprenant des escales parfois nombreux, que ce soit d’ordre technique ou pour "aller à la cueillette", c’est-à-dire, charger ou décharger une partie de la cargaison, ont pu finalement permettre à Marseille de pouvoir jouer sur plusieurs plans et plusieurs marchés, sans se rendre dépendante d’un seul marché ou d’une seule modalité d’effectuer le transport. Cette flexibilité pourrait expliquer aussi sa meilleure tenue en temps de guerre.'}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{categorie:"méditerranée",id:"styles-navigation"})}),(0,dc.jsx)("p",{children:"La navigation depuis les ports de la Méditerranée occidentale - notion étendue ici à l’Adriatique européenne - comprend un très grand nombre de données (plus de 7 600 arrivées à Marseille sur les quatre années, et encore une bonne partie des trafics de proximité entre la Toscane et la Catalogne nous échappe, car ils étaient inscrits sur les cahiers du petit cabotage). Cette masse de voyages, pour l’essentiel en provenance d’une multitude de ports situés entre le détroit de Gibraltar et le royaume de Naples, se caractérise par la prépondérance de bâtiments de faible portée (5-50 tonneaux) comme les bateaux, les chasse-marées, les felouques, les goélettes et surtout les tartanes qui naviguent principalement en droiture (c.à.d. sans escales), ou en effectuant une seule escale. Cette navigation ne requiert pas de compétences nautiques particulières, et n’a pas beaucoup attiré l’attention des historien.nes. Elle se révèle pourtant essentielle pour le ravitaillement quotidien et le commerce de redistribution du grand port de Marseille."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"styles-navigation",tonnage:"150"})}),(0,dc.jsx)("p",{children:"Les grands navires sont rares sur ces routes de proximité. Si on met en avant par exemple la navigation des brigantins, des navires ou des senaus, c.à.d. des bâtiments estimés à 150 tonneaux mis en évidence ci-contre, la géographie commerciale change radicalement, et l’Europe méditerranéenne disparaît au profit du commerce avec l’Empire ottoman et l’Europe atlantique."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{categorie:"empire",id:"styles-navigation"})}),(0,dc.jsx)("p",{children:"Le tonnage et le nombre d’escales intermédiaires sont bien plus importants depuis les grands nœuds du commerce français au Levant, qui emploient le plus souvent des navires de tonnage moyen (50-150 tonneaux) comme l’allège, le brick, le chebec, la pinque ou la queche. Parmi les « Échelles » ottomanes, Smyrne est le principal protagoniste du trafic français, et dépasse largement les départs depuis les autres grands ports de l’Empire (Salonique, Alexandrie d’Égypte et Constantinople). Alexandrette, Coron, Enos et La Canée ne viennent qu’au deuxième rang. En réalité, la navigation française fréquente de dizaines de ports au Levant tant en droiture que, surtout, dans le cadre de la caravane maritime (voir partie 3.C). S’ils n’apparaissent pas sur la carte, qui ne représente que le port de départ du voyage, on lit leur présence en filigrane par le nombre d’escales intermédiaires avant l’arrivée du navire à Marseille - le plus souvent, entre un et quatre, sans que la taille du navire n’affecte cette variable. "}),(0,dc.jsx)("p",{children:'Les ports du Maghreb (Tunis, Bonne, La Cale, Alger) rivalisent avec les principales Échelles ottomanes par le nombre des expéditions. Au cours du XVIIIe siècle ils se révèlent de plus en plus stratégiques pour le ravitaillement en céréales de Marseille et de son arrière-pays. Les arrivées en droiture, sans escales intermédiaires, depuis la catégorie agrégée "Empire ottoman" sont le plus souvent de leur fait.'}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{categorie:"ponant",id:"styles-navigation"})}),(0,dc.jsx)("p",{children:"Les ports européens situés au-delà du détroit de Gibraltar expédient un nombre de navires à Marseille comparables à ceux en provenance de l’Empire ottoman et de la mer Noire (1160 voyages contre 1230). Les navires de portée moyenne et forte (150-300 tonneaux) dominent. Il s’agit d’une navigation de long cours, où les navires se dirigent à Marseille, principal emporium méditerranéen, pour décharger leur cargaison et trouver un fret ou une cargaison de retour. L’écrasante majorité des bâtiments navigue en réalité en droiture, l’escale indiquée sur le graphique n’étant le plus souvent que le passage par le détroit de Gibraltar, dont les sources relatent la date. Les lieux de départ sont multiples, sans que l’importance de Londres et Amsterdam se dégage de manière écrasante. "}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"styles-navigation",steps:"3"})}),(0,dc.jsx)("p",{children:"La relation entre le nombre d’étapes, révélateur d’une logique de navigation qui ne vise pas à maximiser la durée du voyage, et la géographie commerciale mériterait d’être affinée, mais la visualisation ci-contre, qui met en évidence les voyages avec 3 étapes, montre qu’elle est pour l’essentiel le fait des navigations avec l’Empire ottoman."}),(0,dc.jsx)("p",{children:"Ce qui émerge cette analyse de ces trois grandes aires commerciales-maritimes, c’est la représentation de la coexistence (et la complémentarité?) de différents styles de navigation qui desservent un grand port européen à la fin de l’époque moderne. Marseille au XVIIIe siècle peut jouer sur plusieurs réseaux de navigation ayant des caractéristiques et fonctions différentes. Cabotage, caravane, long cours, navigation commerciale en droiture : chacun a sa part dans le fonctionnement et la résilience du port phocéen au XVIIIe siècle. "})]})}function eN(e){const t=Object.assign({code:"code"},e.components);return(0,dc.jsxs)("div",{id:"part-2",children:[(0,dc.jsx)("p",{children:"Diversification dans la variété des produits, dans les partenaires (et dans le croisement produits x partenaires : matrice), dans les acteurs de la navigation."}),(0,dc.jsx)("h2",{id:"h.ipbpmiriq4tr",children:"2.A Diversité des produits du commerce de Marseille"}),(0,dc.jsx)("p",{children:"Est-ce que Marseille est, en termes de produits, plus diversifié que les autres ports français ? + évolution dans le temps"}),(0,dc.jsx)("p",{children:"Notes sur la réponse à cette question:"}),(0,dc.jsx)("p",{children:"Pour certains bureaux et directions et bureaux, on a calculé l'indice Herfindhal en tout année dont les données sur les produits exportés étaient enregistrées en toflit18_all_flows."}),(0,dc.jsx)("p",{children:"Les six directions principales sélectionnées étaient : "}),(0,dc.jsxs)("ol",{children:[(0,dc.jsx)("li",{children:"Bordeaux"}),(0,dc.jsx)("li",{children:"Marseille"}),(0,dc.jsx)("li",{children:"Rouen"}),(0,dc.jsx)("li",{children:"Nantes"}),(0,dc.jsx)("li",{children:"La Rochelle"}),(0,dc.jsx)("li",{children:"Bayonne"})]}),(0,dc.jsx)("p",{children:"Les huit bureaux de ferme sélectionnées pour l'année 1789 étaient : "}),(0,dc.jsxs)("ol",{children:[(0,dc.jsx)("li",{children:"Bordeaux"}),(0,dc.jsx)("li",{children:"Marseille"}),(0,dc.jsx)("li",{children:"Rouen"}),(0,dc.jsx)("li",{children:"Nantes"}),(0,dc.jsx)("li",{children:"La Rochelle"}),(0,dc.jsx)("li",{children:"Bayonne"}),(0,dc.jsx)("li",{children:"Saint-Malo"}),(0,dc.jsx)("li",{children:"Le Havre"})]}),(0,dc.jsx)("p",{children:"Puisqu'il y a plus de données pour les directions que pour les bureaux, on a bouclé sur toute année enregistrée et on a calculé l'indice Herfindhal."}),(0,dc.jsx)("p",{children:"La calculation étaient fait selon les étapes suivantes : "}),(0,dc.jsxs)("ol",{children:[(0,dc.jsx)("li",{children:"calculer la somme de la valeur de tout produit exporté par la direction / le bureau ciblé → all_product_value"}),(0,dc.jsx)("li",{children:"agréger les exports par type et sommé leur valeur agrégée"}),(0,dc.jsx)("li",{children:"les agrégations étaient fait sur la colonne 'product_revolutionempire'"}),(0,dc.jsx)("li",{children:"GROUP BY product_revolutionempire → product_revolutionempire, SUM(value) AS sum_value"}),(0,dc.jsx)("li",{children:"calculer le ratio entre la totale en valeur d'un produit et la totale du bureau / direction et le multiplier par lui-même"}),(0,dc.jsx)("li",{children:"(sum_value/all_product_value)2 → carre_part_marche"}),(0,dc.jsx)("li",{children:"calculer la somme du ratio"})]}),(0,dc.jsx)("p",{children:"Lié à l’intersection de plusieurs espaces. "}),(0,dc.jsx)("h2",{id:"h.8lvwm85ep7f9",children:"2.B Une diversification des marchés plus forte qu’ailleurs ?"}),(0,dc.jsx)("p",{children:"Pour les catégories et/ou les produits les plus importants en valeur : Une diversification des marchés plus forte qu’ailleurs ? (voir si Marseille est moins dépendante que d’autres ports d’un seul marché pour ses produits principaux) + évolution dans le temps. Travail sur la matrice."}),(0,dc.jsxs)("p",{children:["analyse préliminaire pour blé et huile à Marseille (construit à partir des données dispos ",(0,dc.jsx)("a",{className:"c12",href:"https://github.com/medialab/portic-storymaps-2023/blob/main/datascripts/module_2B/partners.csv",rel:"noopener noreferrer",target:"_blank",children:"ici"})," en utilisant ‘python compute_data.py’ dans le dossier ",(0,dc.jsx)("a",{className:"c12",href:"https://github.com/medialab/portic-storymaps-2023/tree/main/datascripts/module_2B",rel:"noopener noreferrer",target:"_blank",children:"datascripts/module_2B"}),")"]}),(0,dc.jsx)("p",{children:"On crée un indice de variabilité des partenaires d’un port pour un type de produit (en import ou en export) comme la moyenne des variances des ratios d’un partenaire sur une année par rapport à l’ensemble des partenaires pour cette même année, on l’applique aux 10 principaux produits en import et 10 principaux en export pour les principaux grands ports (Marseille, Bordeaux, Nantes, Rouen, La Rochelle, Bayonne)."}),(0,dc.jsxs)("p",{children:["On produit les données avec ",(0,dc.jsx)(t.code,{children:"python compare_ports.py"})," dans le dossier ",(0,dc.jsx)("a",{className:"c12",href:"https://github.com/medialab/portic-storymaps-2023/tree/main/datascripts/module_2B",rel:"noopener noreferrer",target:"_blank",children:"datascripts/module_2B"})," ce qui produit les données ",(0,dc.jsx)("a",{className:"c12",href:"https://github.com/medialab/portic-storymaps-2023/blob/main/datascripts/module_2B/variances_ports_produits.csv",rel:"noopener noreferrer",target:"_blank",children:"suivantes"})," visualisées sous la forme de boxplot ou de violin plot ci-dessous (résultats contradictoires avec l’objectif initial)"]}),(0,dc.jsx)("p",{children:"Titre: Top 5 produits (imports et exports)"}),(0,dc.jsx)("h2",{id:"h.5xt17flpsq8c",children:"2.C . Diversité des acteurs de la navigation de Marseille "}),(0,dc.jsx)("p",{children:"Marseille attire plus de pavillons étrangers que tout autre port français. "}),(0,dc.jsx)("p",{children:"Titre: Nombre de pavillons étrangers différents en 1787 dans les 20 principaux ports français"}),(0,dc.jsx)("p",{children:"La navigation entre la France et les pays étrangers est largement tributaire des services de transport des flottes étrangères. Or, la présence française est plus élevée sur les marchés méditerranéens. "}),(0,dc.jsx)("p",{children:"Titre: Navigation de la France avec les pays étrangers en 1787. Nombre total des navires et pavillons"}),(0,dc.jsx)("p",{children:"Les étrangers assurent un trafic important, qui vient conforter la position de force du port phocéen, et ce d’autant plus que les données de Marseille prennent en compte la seule source des déclarations des capitaines (3290 entrées, sur un total connu de 4XXX congés), mise ici en comparaison avec le tonnage sortis des autres ports, connu grâce aux congés délivrés. "}),(0,dc.jsx)("p",{children:"Titre: Tonnage étranger dans les 20 principaux ports français en 1787 (en tonneaux)"}),(0,dc.jsx)("p",{children:"NB: congés pour tous les ports sauf Marseille = entrées (petit cabotage exclu)"}),(0,dc.jsx)("p",{children:"Les étrangers sont présents de manière significative dans l’ensemble des premiers ports français (par importance du tonnage total), sans que la position de Marseille se détache des autres."}),(0,dc.jsx)("p",{children:"Titre: Tonnage étranger versus tonnage total des 10 premiers ports français en 1787 (en tonneaux). NB: congés pour tous les ports sauf Marseille = entrées (petit cabotage exclu)"}),(0,dc.jsx)("p",{children:"Titre: Part du tonnage étranger dans les dix premiers ports de France en 1787 (en tonneaux)- Marseille = entrées; autres = congés"}),(0,dc.jsx)("p",{children:"Marseille est donc un port attractif pour le commerce et les frets. Il s’agit de voir la diversité et la part des différents acteurs sur les différents marchés en tant que facteur de force du commerce marseillais sur le long terme (car pas dépendante d’un seul pavillon) mais aussi de souligner (si c’est le cas) que la part de la navigation gérée par les Provençaux est plus importante qu’ailleurs (= sont plus autonomes)"}),(0,dc.jsx)("p",{children:"Parmi les principaux partenaires de Marseille (en tonnage), les navires français gèrent la plupart du trafic maritime entre Marseille et les autres ports de France, tout comme celui avec l’Empire ottoman, marché privilégié du port phocéen. La part du pavillon français ne change pas au fil du temps. Pour ce qui est des liaisons avec les ports de la péninsule italienne, marchés primordiaux pour Marseille, ce sont les étrangers à gérer la plupart du trafic. Depuis l’Espagne, la part des Français diminue au cours du temps."}),(0,dc.jsx)("p",{children:"Expliquer les données avec Grande-Bretagne"}),(0,dc.jsx)("p",{children:"Titre: Part de la navigation avec les principaux partenaires de Marseille (tonnage) assurée par les Français (années de paix)"}),(0,dc.jsx)("p",{children:"Titre: Tonnage assuré par les Français dans la navigation avec les principaux partenaires de Marseille (années de paix)"}),(0,dc.jsx)("p",{children:"Visus ex 4A"}),(0,dc.jsx)("p",{children:"Titre: Vitesse moyenne en miles par jour pour chaque décennie"}),(0,dc.jsx)("p",{children:"Titre: Vitesse moyenne pour chaque pavillon et chaque décennie"}),(0,dc.jsx)("p",{children:"Titre: Vitesse moyenne pour chaque pavillon et chaque décennie"}),(0,dc.jsx)("p",{children:"Titre: Nombre de trajet par pavillon et par types de bateau"}),(0,dc.jsx)("p",{children:"Titre: Durée moyenne par pavillon et par types de bateau "}),(0,dc.jsx)("p",{children:"Titre: Évolution des types de bateau en pourcentage, pour chaque décennie et chaque pavillon"}),(0,dc.jsx)("p",{children:"Possibilité de faire la même chose pour Marseille en 1787 (avec seulement les entrées) - > carte avec import (avec possibilité de sélectionner) et de comparer "}),(0,dc.jsxs)("ol",{children:[(0,dc.jsx)("li",{children:"Est-ce que les étrangers assurent le transport depuis les marchés les plus importants (hors colonies) ? projeter la part de la navigation française versus étrangère pour années Navigo (quels pavillons transportent les cargaisons de plus forte valeur) [ex: carte avec valeurs Toflit par pays import/export qui avance dans le temps] "}),(0,dc.jsx)("li",{children:'NB: étranger n’est pas synonyme de "Nordique"'})]}),(0,dc.jsx)("p",{children:"Hypothèse Silvia: diversifications entre marchés atlantiques et marchés méditerranéens en termes de pavillons (liées aussi à la taille des navires) qui permet aux ports avec des infrastructures importantes (lazarets, consulats etc.) d’être desservis par tout le monde, avec en parallèle des routes interstitielles réservés à d’autres acteurs (provençaux, méditerranéens) qui demeurent importantes -> Une géographie des acteurs plus ‘granulaire’ que chez Carrière qui ne croise pas pavillons et routes (hypothèse: les Nordiques ne sont présents que sur certains circuits / ports structurés; les Provençaux/Languedociens investissent la péninsule italienne, le Levant, la Barbarie, peut-être l’Espagne de manière significative)"})]})}function tN(e){const{Caller:t}=e.components||{};return t||function(){throw new Error("Expected component `Caller` to be defined: you likely forgot to import, pass, or provide it.")}(),(0,dc.jsxs)("div",{id:"part-3",children:[(0,dc.jsx)("p",{children:"Le commerce français est très affecté par les guerres maritime tout au long du XVIIIe siècle : Guerre de Succession d’Autriche (1744-1748), Guerre de Sept Ans (1756-1763 en Europe), Guerre d’Indépendance américaine (1778-1783), Guerres de la Révolution et de l’Empire (1793-1815, avec quelques mois de paix en 1801-1802 et 1814). La Méditerranée n’est pas neutralisée, loin de là : elle aussi est un champ de bataille. Cependant, elle est moins souvent sous l’emprise de la puissance navale britannique. Peut-être est-ce là un avantage pour Marseille, qui aurait moins souffert de la pression guerrière que les ports français de l’Atlantique ?"}),(0,dc.jsx)("h2",{id:"h.92qf38d5u0ri",children:"3.A Impact de la guerre sur le commerce de Marseille"}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{directions:"Marseille",id:"impact-guerre-sur-commerce-et-navigation",series:"total"})}),(0,dc.jsx)("p",{children:"Pour vérifier cela, nous utilisons une statistique élaborée dans une recherche en cours Guillaume Daudin et Elisa Tirindelli. Elle consiste à calculer l’écart moyen entre le commerce observé en temps de guerre et le commerce tel qu’il aurait été s’il avait suivi sa tendance durant la période de paix précédant la guerre. Ainsi, sur la visualisation ci-contre, on peut lire que le commerce total de Marseille diminue de 40% en temps de guerre. La comparaison des droites rouges (l’évolution hypothétique du commerce durant chaque guerre si la paix avait continué) et les lignes noires (le commerce effectivement observé) montre aussi que cette diminution est d’ampleur comparable pour les trois guerres maritimes."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{directions:"Marseille",id:"impact-guerre-sur-commerce-et-navigation","navigation-metric":"carrière",series:"navigation"})}),(0,dc.jsx)("p",{children:"La chute de la navigation est moins forte: 6% en moyenne si on n’utilise les données annuelles de Carrière."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{directions:"Marseille",id:"impact-guerre-sur-commerce-et-navigation","navigation-metric":"entrées",series:"navigation"})}),(0,dc.jsx)("p",{children:"Les données de Navigocorpus pour Marseille concernent les entrées des dépositions des capitaines auprès du bureau de la Santé, mais ne sont disponibles que tous les dix ans (1749-1799). Elles indiquent un effet plus important de la guerre que les données collectées par Charles Carrière à partir de la même source (-23%). Dans tous les cas, ce déclin est moins important que celui visible à partir des données de la valeur du commerce."}),(0,dc.jsx)("p",{children:"La différence s’explique en partie à cause d’une couverture temporelle différente. La série de données de Charles Carrière comprend la période de la guerre de Succession d’Autriche qui a un impact faible mais pas celle de la guerre d’Indépendance américaine ni de la décennie révolutionnaire, qui ont un impact important d'après les données sur la navigation collectées par Navigocorpus."}),(0,dc.jsx)("p",{children:"En tout état de cause, il n’est pas surprenant que la navigation soit moins affectée par la guerre que le commerce, car une partie importante se fait à courte distance ou sur des navires de petite taille. La valeur des marchandises transportées par ces deux flux, moins vulnérables aux désordres apportés par la guerre, est relativement faible."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{directions:"Marseille",id:"impact-guerre-sur-commerce-et-navigation","navigation-metric":"mileage",series:"navigation"})}),(0,dc.jsx)("p",{children:"Le nombre d’entrées à Marseille rend imparfaitement compte de l’impact des conflits sur la navigation marseillaise, qui apparaît davantage en prenant en compte les tonnages et le rétrécissement des aires de navigation, mesuré ici en milles maritimes agrégées. Ainsi, lorsqu’on observe ces deux variables (graphique ci-contre), les pertes liées à la guerre sont beaucoup plus importantes (44% et 66% respectivement): la guerre n’est donc pas anodine, même pour la navigation."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{directions:"Marseille, Bordeaux, Rouen, Nantes, La Rochelle, Bayonne",id:"impact-guerre-sur-commerce-et-navigation"})}),(0,dc.jsx)("p",{children:"Pour savoir si ces réactions à la guerre sont malgré tout un facteur potentiel de la résilience marseillaise, il faut comparer le comportement du commerce de Marseille à celui des autres ports français. Comme le montre le graphique ci-contre, Nantes est plus vulnérable que Marseille (-55%). Mais c’est le seul port à l’être : la réduction du commerce de Bordeaux, Rouen (y compris le Havre) et La Rochelle varie entre 15 et 25%. Bayonne bénéficie même des guerres (pour un commerce, il est vrai, plus faible). La comparaison n’est pas parfaite, car les mêmes années ne sont pas disponibles pour chaque port. Mais en tous les cas, il n’y a pas de signe évident d’une particulière résilience de Marseille à la guerre."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"impact-guerre-sur-commerce-et-navigation","navigation-metric":"entrées",series:"total, imports, exports"})}),(0,dc.jsx)("p",{children:"Le graphique ci-contre élargit l’analyse en considérant les exportations et les importations, il confirme les résultats présentés ci-dessus. De même si on étudie le problème en regardant de manière plus spécifique le commerce colonial, notre constat initial en sort renforcé: il n’existe pas d’éléments statistiques probants qui permettent d’affirmer que le commerce maritime de Marseille est moins affecté par les guerres que celui des autres ports français."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"impact-guerre-sur-commerce-et-navigation","navigation-metric":"entrées",series:"total_no_colonial_trade, imports_no_colonial_trade, exports_no_colonial_trade"})}),(0,dc.jsx)("p",{children:"Même constatation si l’on exclut le commerce colonial, sinon que dans ce cas, la vulnérabilité de La Rochelle et de Nantes sont comparables à celles de Marseille."}),(0,dc.jsx)("h2",{id:"h.wwo855isgynu",children:"3.B Qui assure la navigation en temps de guerre ?"}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"guerre-et-navigation"})}),(0,dc.jsx)("p",{children:"Une approche différente, mais complémentaire, pour comprendre l’impact des conflits sur le commerce consiste à étudier les changements affectant les acteurs du transport maritime. Plus précisément, il s’agit de questionner la permanence de la navigation française - et donc l’éventuelle perte des marchés du transport maritime - et le jeu des pavillons neutres. La guerre affecte profondément les logiques des trafics maritimes et les vitesses de navigation (que ce soit en raison de l’introduction des convois depuis le Levant, ou d’une navigation plus proche des côtes, avec des escales plus fréquentes, pour échapper aux corsaires ennemis). Faute de données permettant une comparaison avec les autres ports français, cette étude a été menée sur le seul cas marseillais. "}),(0,dc.jsx)("p",{children:"L’analyse s’est concentrée sur le changement des pavillons qui desservent Marseille dans une année de guerre étudiée (1759, 1779, 1799) par rapport à l’année de paix dix ans plus tôt. Les pavillons ont été répartis en cinq catégories, représentant le statut diplomatique envers la France du pays respectif dans l’année de guerre (allié, ennemi, neutre) et, pour le pavillon français, en distinguant ceux de la façade méditerranéenne et ceux du Ponant (façade atlantique et Manche). Nous avons introduit cette distinction car les navires des ports français au-delà du détroit de Gibraltar doivent prendre des risques bien plus importants lors de leur trajet jusqu’à Marseille, en raison de la présence britannique sur mer dans la Manche et en Atlantique."}),(0,dc.jsx)("p",{children:"Les pavillons qui desservent Marseille présentent une dynamique similaire tant pendant la guerre des Sept Ans que pendant celle de l’Indépendance américaine. Les grands gagnants lors de la guerre de Sept Ans et de celle d'Indépendance américaine sont les pavillons neutres, qui passent de 20-25 % du trafic à 50-60%. La part de la navigation française du Ponant diminue fortement, alors que celle du Levant se maintient nettement mieux. Sans grande surprise, la navigation des pavillons ennemis de la France disparaît pendant les deux conflits, la seule différence entre les deux guerres étant que leur part en 1749 (19 %) - l’année de paix précédente qui sert de référence - est considérablement supérieure à leur part en 1769 (5 %). "}),(0,dc.jsx)("p",{children:"La part de la navigation assurée par les alliés de la France dans la navigation marseillaise demeure négligeable aussi bien pendant la guerre de Sept Ans que pendant celle d’Indépendance américaine. Cela change fortement en 1799, lorsque la France révolutionnaire a su, par ses conquêtes militaires, mettre sous son contrôle aussi bien les Provinces-Unies qu’une bonne partie de la péninsule italienne pendant plusieurs mois de l’année. La position de force de la France sur le continent en 1799 explique en grande partie l’effondrement du rôle de la navigation neutre à Marseille en 1799 par rapport aux conflits précédents. Mais ce n’est pas pour autant un signe d’une meilleure position de la France sur mer. Exprimée en pourcentage, cette répartition des pavillons masque un changement radical: le nombre de gros bâtiments s’effondre: brigantins, polacres, senaus et navires - soit de types de navires de 150 tonneaux ou plus en moyenne (Sofia, 2024) - passent de plus de 800 en 1789 à moins de 200 en 1799, contre une diminution d’un tiers seulement entre 1769 et 1779. Ce n’est donc plus que le cabotage par de petites unités qui se maintient car elles échappent plus facilement à la vigilance britannique sur mer."}),(0,dc.jsx)("p",{children:"La compréhension des effets de compensation entre pavillons et des changements de fond dans les marchés et la navigation requiert de prendre en compte simultanément les différentes variables. Nous allons le faire pour le commerce du Levant, dont on a déjà souligné l’importance centrale pour Marseille. Il nous a semblé plus intéressant de suivre ce cas, plutôt que celui du commerce colonial, dont l’importance est moindre pour Marseille. "}),(0,dc.jsx)("h2",{id:"h.8uq6vxnsuzpw",children:"3.C Zoom sur le Levant"}),(0,dc.jsx)("p",{children:"Comme nous avons vu plus haut, le Levant représente un ensemble important de ports de départ pour les arrivées à Marseille :"}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"levant-navigation"})}),(0,dc.jsxs)("p",{children:["La présence française est en effet capillaire, ce dont témoigne aussi l’effort majeur, par la monarchie française, d’étoffer le réseau consulaire et le nombre de vice-consuls afin d’assister les capitaines. Outre le commerce direct, les Provençaux se sont spécialisés aussi dans le commerce dit de caravane (Panzac 2004; Buti 2010)",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Le terme de caravane désigne des contrats de transport individuels, enregistrés auprès des chancelleries des consulats européens, entre un marchand généralement turc ou arabe, un capitaine chrétien et un intermédiaire souvent issu des minorités religieuses du monde ottoman (Grecs, Arméniens ou Juifs), en qui les deux parties ont confiance dans la mesure où il n’appartient pas à la communauté de l’autre contractant. Les campagnes, d’une durée théorique de deux ans maximum d’après le législateur français, sont assez fréquemment plus longues.",children:"?"}),". Les capitaines partent depuis la France vers le Levant, et associent au fil de leurs escales commerce et services de transport, naviguant donc de port et port au gré des contrats d'affrètement. Les Provençaux ne sont pas les seuls à s’adonner à ces trafics profitables, car les Vénitiens et Ragusains sont aussi actifs, et leur ravissent des parts de marché quand les Français sont en guerre. Ces trois groupes d’acteurs méditerranéens assurent 95% de la navigation sous pavillon européen à Alexandrie dans les années 1785-1789. "]}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"effets-guerre-sur-commerce-levant"})}),(0,dc.jsx)("p",{children:"Au regard du graphique ci-contre, on peut constater que l’impact des guerres avec l'Angleterre est significatif en ce qui concerne le commerce avec le Levant. Cet impact est visible aussi bien à partir des données de la balance du commerce que de celles de la navigation. En effet, il est le commerce le plus affecté après celui des colonies françaises, alors que ses conséquences sur le commerce avec les pays méditerranéens plus proches (l’Italie et l’Espagne) sont plus bénins. Seule la guerre d'indépendance américaine fait un peu exception. Comme le rapport entre les flottes de guerre françaises et ses alliés contre celle de l’Angleterre est bien plus favorable que pendant les trois autres guerres et que le principal théâtre d’opération se situe dans l’Atlantique Nord, les risques de pertes pour les marchands à destination du Levant étaient beaucoup moins grands. L’utilisation des données de navigation permet d'affiner ce constat: la perte de commerce vers le Levant est moins grande que ne le laisse imaginer les flux bilatéraux car une partie de celui-ci est pris en charge par les navires neutres, italiens en particulier. C’est ce qui explique que, pendant les guerres de succession d’Autriche et de Sept Ans, le commerce vers l’Espagne et le Portugal connaisse une certaine croissance: ces relais- l’Italie en particulier - sont en fait des étapes depuis ou vers des destinations plus éloignées et trop risquées en temps de guerre."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"levant-navigation-guerre"})}),(0,dc.jsx)("p",{children:'Pour ce qui est de la navigation, on constate que les Provençaux (les "Français du Levant" sont essentiellement des Provençaux, la participation des Languedociens étant limitée) parviennent à garder le contrôle sur la navigation en provenance du Levant tant pendant la guerre de Sept Ans que, encore plus, pendant celle d’Indépendance américaine (où quatre convois par an sont organisés pour escorter les navires français depuis Smyrne et Malte, et quatre autres depuis les régences barbaresques). En revanche, ils sont définitivement évincés des activités de tramping lors des guerres révolutionnaires: en 1799, seulement un navire sur quatre en provenance du Levant qui parvient à Marseille navigue sous pavillon français. Ces changements, exprimés en pourcentage de tonnages agrégés, nécessitent d’être éclairés par les chiffres absolus: le nombre de départs depuis l’Empire ottoman (régences barbaresques comprises) vers Marseille se contracte aussi bien pendant la guerre de Sept Ans que lors de celle d’Indépendance américaine, et se situe autour de 45% du nombre des entrées dix ans plus tôt. En revanche, en 1799 ce commerce disparaît presque entièrement, car on passe de 192 arrivées de l’Empire ottoman en 1789 à 8 seulement en 1799 ! '}),(0,dc.jsx)("p",{children:"Dans la décennie révolutionnaire, la France perd en effet définitivement ses positions de force au Levant, et abandonne également le commerce de caravane qui permettait à l’armement français des profits substantiels (Panzac, 2004). Lorsque la paix revient, en 1815, le contexte méditerranéen a profondément changé: la fin du corso, activité prédatrice qui affecte lourdement au XVIIIe siècle la sécurité des navires ottomans et des pays de chrétienté qui n’avaient pas de traités de paix avec les régences barbaresques, permet désormais à tout et chacun de naviguer librement en Méditerranée, alors que la suppression des privilèges qui favorisent le commerce de Marseille avec l’Empire ottoman (droit de 20%) ouvre la voie à la concurrence. Un demi siècle plus tard, quand la navigation à vapeur et le chemin de fer auront changé en profondeur les modalités des échanges en Méditerranée et en Europe, Marseille trouvera de nouvelles possibilités de s’insérer dans ce monde qui change."})]})}function nN(e){return(0,dc.jsxs)("div",{id:"part-3",children:[(0,dc.jsx)("p",{children:"on pose la question de l’impact et on montre que finalement ce n’est pas un facteur essentiel de la résilience de Marseille"}),(0,dc.jsx)("h3",{id:"h.92qf38d5u0ri",children:"3.A Impact de la guerre sur le commerce de Marseille"}),(0,dc.jsx)("p",{children:"Un impact de la guerre moins important qu’ailleurs? Voir si les guerres ont toutes un moindre impact (quelques doutes pour celle de Sept Ans)"}),(0,dc.jsxs)("ol",{children:[(0,dc.jsx)("li",{children:"Regarder les évolutions du commerce de Marseille pendant les guerres 1740-1748, 1756-1763 et 1776-1783 comparé au commerce français total."}),(0,dc.jsx)("li",{children:"Quels marchés à Marseille sont les plus affectés par la guerre? Est-ce que certains marchés accroissent leur part ? "})]}),(0,dc.jsx)("p",{children:"On distingue trois périodes de guerre : "}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"1744-1748 : succession Autriche"}),(0,dc.jsx)("li",{children:"1756-1763: sept ans"}),(0,dc.jsx)("li",{children:"1776-1783: indépendance américaine"})]}),(0,dc.jsx)("p",{children:"Pour ces trois périodes on calcule une prédiction du commerce en appliquant une régression linéaire sur les données de commerce des années précédent la guerre."}),(0,dc.jsx)("p",{children:"On teste deux manières de considérer les périodes de paix pré-guerre: "}),(0,dc.jsxs)("ol",{children:[(0,dc.jsx)("li",{children:"avec mémoire: on considère toutes les périodes de paix précédentes"}),(0,dc.jsx)("li",{children:"sans mémoire: on ne considère que la dernière période de paix précédente"})]}),(0,dc.jsx)("p",{children:"Sur les représentations ci-dessous, les régressions en rouge sont celles calculées avec mémoire, en orange sans mémoire (sur la première période de guerre, les deux régressions sont identiques)."}),(0,dc.jsx)("p",{children:"On calcule ensuite un taux de perte en comparant les valeurs attendues par régression aux valeurs constatées dans les stats de commerce. Ce taux de perte est exprimé comme suit : (effectif - prédit) / prédit"}),(0,dc.jsx)("p",{children:"On agrège ensuite les taux de perte annuels en faisant une moyenne."}),(0,dc.jsx)("p",{children:"Ces taux sont indiqués dans les coins hauts gauche et droites des visualisations."}),(0,dc.jsx)("p",{children:"On calcule les mêmes indicateurs de perte sur les indicateurs de navigation:"}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"entrées suivant Carrière"}),(0,dc.jsx)("li",{children:"entrées suivant Navigo"}),(0,dc.jsx)("li",{children:"distances parcourues suivant Navigo"}),(0,dc.jsx)("li",{children:"tonnage suivant Navigo"})]}),(0,dc.jsx)("p",{children:"On observe une différence importante entre les taux de pertes des séries navigo comparées à Carrière. La série de donnée Carrière contient la période de la guerre de succession qui a un impact faible mais ne contient pas la période de la guere d’indépendance qui semble très impactante d’arès navigo. La série Carrière est donc globalement moins impactée. "}),(0,dc.jsx)("p",{children:"Les données navigo nous permettent de constater que si les entrées sont les moins influencées par les guerres, la taille et la distance parcourue par les navires subissent elles une diminution importante."}),(0,dc.jsxs)("p",{children:["Explication après exploration Toflit18 :",(0,dc.jsx)("a",{className:"c12",href:"http://toflit18.medialab.sciences-po.fr/#/exploration/indicators?lines=%5B%7B%22color%22%3A%22#504342%22%2C%22partnerClassification%22%3A%22partner_grouping%22%2C%22partner%22%3A%5B%7B%22id%22%3A%22Italie%7Epartner_grouping%22%2C%22name%22%3A%22Italie%22%7D%2C%7B%22id%22%3A%22Espagne%7Epartner_grouping%22%2C%22name%22%3A%22Espagne%22%7D%5D%2C%22region%22%3A%22Marseille%22%2C%22kind%22%3A%22import%22%2C%22sourceType%22%3A%22Best%20Guess%20customs%20region%20product%20x%20partner%22%7D%2C%7B%22color%22%3A%22#A563B7%22%2C%22partnerClassification%22%3A%22partner_grouping%22%2C%22partner%22%3A%5B%7B%22id%22%3A%22Levant_et_Barbarie%7Epartner_grouping%22%2C%22name%22%3A%22Levant%20et%20Barbarie%22%7D%5D%2C%22region%22%3A%22Marseille%22%2C%22kind%22%3A%22import%22%2C%22sourceType%22%3A%22Best%20Guess%20customs%20region%20product%20x%20partner%22%7D%2C%7B%22color%22%3A%22#85C85B%22%2C%22partnerClassification%22%3A%22partner_grouping%22%2C%22partner%22%3A%5B%7B%22id%22%3A%22Angleterre%7Epartner_grouping%22%2C%22name%22%3A%22Angleterre%22%7D%2C%7B%22id%22%3A%22Am%E9riques%7Epartner_grouping%22%2C%22name%22%3A%22Am%E9riques%22%7D%5D%2C%22region%22%3A%22Marseille%22%2C%22kind%22%3A%22import%22%2C%22sourceType%22%3A%22Best%20Guess%20customs%20region%20product%20x%20partner%22%7D%2C%7B%22color%22%3A%22#C14F4C%22%2C%22partnerClassification%22%3A%22partner_grouping%22%2C%22partner%22%3A%5B%7B%22id%22%3A%22Nord%7Epartner_grouping%22%2C%22name%22%3A%22Nord%22%7D%2C%7B%22id%22%3A%22Hollande%7Epartner_grouping%22%2C%22name%22%3A%22Hollande%22%7D%2C%7B%22id%22%3A%22Flandre_et_autres_%E9tats_de_l%27Empereur%7Epartner_grouping%22%2C%22name%22%3A%22Flandre%20et%20autres%20%E9tats%20de%20l%27Empereur%22%7D%5D%2C%22region%22%3A%22Marseille%22%2C%22kind%22%3A%22import%22%2C%22sourceType%22%3A%22Best%20Guess%20customs%20region%20product%20x%20partner%22%7D%5D",rel:"noopener noreferrer",target:"_blank",children:" le commerce du Levant est fortement réduit en temps de guerre. Faire une viz avec les part Toflit."})]}),(0,dc.jsx)("p",{children:"En 1748, baisse Italie (il y a une guerre là-bas je crois)."}),(0,dc.jsx)("h3",{id:"h.ts1t7dr716s7",children:"3.B Stratégies de maintien de la navigation à Marseille face à la guerre "}),(0,dc.jsx)("p",{children:"Le nombre d’entrées à Marseille rend imparfaitement compte de l’impact des conflits sur la navigation marseillaise, qui apparaît davantage en prenant en compte le rétrécissement des aires de navigation, mesuré ici en milles maritimes agrégées."}),(0,dc.jsx)("p",{children:"Titre: Tonnages estimés totaux passant par Marseille chaque année considérée"}),(0,dc.jsx)("p",{children:"Titre: Stage_length total agrégé pour tous et pour le pavillon FR"}),(0,dc.jsx)("p",{children:"Titre: Stage_length moyen par bateau pour tous et pour le pavillon FR"}),(0,dc.jsx)("p",{children:"Titre: répartition du tonnage total par pavillons"}),(0,dc.jsx)("p",{children:"Titre: répartition du nombre de bateaux par pavillons"}),(0,dc.jsx)("p",{children:"Titre: Répartition du ratio de tonnage par statut en guerre"}),(0,dc.jsx)("p",{children:"Titre: Répartition du ratio de bateaux par statut en guerre"}),(0,dc.jsx)("p",{children:"Hypothèse à vérifier: 1799 forte diminution de l’arrivée de gros bateaux"}),(0,dc.jsx)("p",{children:"Visus ex 4A"}),(0,dc.jsx)("p",{children:"Titre: Nombre total de miles parcourus pour chaque pavillon et chaque décennie"}),(0,dc.jsx)("p",{children:"Titre: Nombre moyen d’étapes pour chaque pavillon et chaque décennie"}),(0,dc.jsx)("p",{children:"La guerre questionne ainsi la permanence de la navigation française et le jeu des pavillons neutres. Elle affecte toutefois aussi les vitesses de navigation, que ce soit en raison de l’introduction des convois depuis le Levant, ou d’une navigation plus proche des côtes, avec des escales plus fréquentes, pour échapper aux corsaires ennemis."}),(0,dc.jsx)("p",{children:"Titre: Nombre de pavillons par décennies"}),(0,dc.jsx)("p",{children:"Titre: Vitesse moyenne pour chaque pavillon (années de guerre versus années de paix)"}),(0,dc.jsx)("p",{children:"Titre: Nombre de trajets total pour chaque pavillon (années de guerre versus années de paix)"}),(0,dc.jsx)("p",{children:"Titre: Nombre de trajets du pavillon français et des pavillons étrangers (années de guerre versus années de paix)"}),(0,dc.jsx)("p",{children:"Une tenue de la navigation française et/ou provençale ? (Convois, Navigation de concert)"}),(0,dc.jsxs)("ol",{children:[(0,dc.jsx)("li",{children:"Les neutres au service de Marseille: Effets de substitution dans le transport maritime "}),(0,dc.jsx)("li",{children:"Montrer la part du commerce qui passe aux neutres dans les années de guerre à partir des tonnages estimés des navires présents dans Navigo en projetant valeurs importations de Marseille par pays"}),(0,dc.jsx)("li",{children:"Sur quels marchés la présence neutre devient fondamentale?"})]})]})}function rN(e){return(0,dc.jsx)("div",{id:"part-4",children:(0,dc.jsx)("p",{children:"Finalement, la force de Marseille n’est pas sa participation à la croissance du commerce Atlantique français tirée par le système colonial. Elle ne repose pas non plus sur un dynamisme exceptionnel de son économie. Elle s’appuie sur sa situation de port méditerranéen dominant. Cette domination s'assoit sur la géographie. Idéalement placée à l’embouchure d’un axe fluvial majeur qui ouvre sur la deuxième métropole française, Lyon, Marseille est d’abord un emporium qui permet la rencontre entre les produits de son arrière pays (draps du Languedoc en particulier) destinés principalement aux marchés méditerranéens (Italie, Levant et dans une moindre mesure l’Espagne) et les produits du pourtour méditerranéen qui nourrissent le Sud-est français et son économie (Blé, cochenille, cotonnades ottomanes). Aussi, même si la Méditerranée est un espace en déclin relatif, elle constitue une base extrêmement solide pour le fonctionnement d’une économie portuaire dynamique tout au long de l’époque moderne et au XIXe siècle. Ces avantages s’inscrivent dans la longue durée, ils persistent après la fin de l’Ancien Régime et seront même renouvelés avec la conquête d’une partie de l’Afrique du Nord sous la restauration, puis l’ouverture du canal de Suez. Aujourd'hui encore, Marseille est un des deux principaux ports internationaux français."})})}function iN(e){return(0,dc.jsx)("div",{id:"part-4",children:(0,dc.jsx)("p",{children:"Finalement, la force de Marseille n’est pas sa participation à la croissance française du xviiie siècle tirée par le système colonial. Il n’est pas non plus dû à un dynamisme exceptionnel. C’est le fait que c’est un port méditerranéen important depuis très longtemps, pour des raisons géographiques persistantes. Même si la Méditerranée est un espace en déclin relatif, l’importance de son commerce est telle qu’elle forme une base pour le fonctionnement d’une économie portuaire dynamique tout au long de l’époque moderne et au xixe siècle. Le 2e empire français donne un nouveau sursi à Marseille. À force de sursis, le condamné enterre ses juges et ses concurrents. "})})}function aN(e){const{Caller:t}=e.components||{};return t||function(){throw new Error("Expected component `Caller` to be defined: you likely forgot to import, pass, or provide it.")}(),(0,dc.jsxs)("div",{id:"part-5",children:[(0,dc.jsx)("h2",{id:"h.glt45mz12av1",children:"Élucider le fonctionnement du port franc"}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{id:"fonctionnement-port-franc",mode:"complete"})}),(0,dc.jsx)("p",{children:"Marseille bénéficie depuis au moins 1669 de privilèges commerciaux exceptionnels pour son commerce avec le Levant. À partir de 1703, une barrière douanière sépare la ville du reste du royaume, consacrant la franchise du port de Marseille. Le statut de port franc de Marseille a ensuite été étendu au commerce colonial par les lettres patentes de 1779 qui lui octroient la liberté du commerce avec les colonies françaises, sous condition d’accepter le régime d’entrepôt. Le fonctionnement du port franc n’apparaît pas très clairement dans les sources portant sur son commerce en 1789 (c’est-à-dire les références F12/1666 et 1667 aux Archives Nationales et F2/B14 aux Archives Nationales d’Outre-Mer, désormais ANOM). En 1789, trois bureaux proprement marseillais sont mentionnés par celles-ci, en plus des bureaux non-marseillais de la Direction des fermes de Marseille."}),(0,dc.jsx)("p",{children:"Mentionnons tout d’abord ces derniers, qui ne posent pas de difficultés particulières : il s’agit des bureaux de Arles, La Ciotat, Lambesc, La Penne et Septeme."}),(0,dc.jsx)("p",{children:"Arles et la Ciotat sont bien connus. Lambesc est entre Aix-en-Provence et Salon-de-Provence. La Penne est sans doute La Penne-sur-Huveaune, aujourd’hui dans la banlieue Est de Marseille. Sur la carte de Cassini, La Penne est très clairement au croisement du grand chemin menant de Marseille à Toulon et sur une frontière indiquée en pointillés. Julliany mentionne d’ailleurs le bureau de la Penne comme lieu d’expédition en direction de la Basse Provence (Juilliany, 1842, tome I, p. 129). Septeme désigne sans doute Septèmes-les-Vallons, au Nord de Marseille sur la route d’Aix-en-Provence, qui était le lieu de passage principal du commerce terrestre de Marseille avec le reste de la France (Julliany, 1842, tome I, p. 129). D’ailleurs, Septèmes et La Penne sont mentionnés parmi les bureaux placés au pourtour de la zone franche suite à un bornage de 1728 (Legay, 2023). Les autres bureaux du pourtour (La Gavotte, La Bourdonnière, Allauch, Aubagne et Cassis) ne sont pas mentionnés par les sources que nous examinons ici."}),(0,dc.jsx)("p",{children:'La Ciotat ne rapporte que des importations coloniales (dans ANOM Col F2/B14, tableau 3). D’ailleurs, cette source (qui provient de la Marine ou de l’Amirauté plutôt que de la Ferme) ne liste que des "Ports de France", sans utiliser les termes "bureau" ni "direction". C’est nous qui par cohérence avec les autres sources avons supposé que La Ciotat était un bureau de la direction de Marseille. Lambesc ne rapporte que des exportations vers Marseille. Arles, La Penne et Septèmes des importations et des exportations surtout avec Marseille, mais aussi avec l’Europe (pas les Colonies ni le Levant). On peut supposer qu’ils regroupaient de lieux périphériques de la direction de Marseille commerçant essentiellement avec le port franc et avec quelques partenaires étrangers.'}),(0,dc.jsxs)("p",{children:["Par ailleurs, Marseille est mentionné comme partenaire commercial par des rapporteurs",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Un «rapporteur» dans ce contexte est un bureau des fermes (ou un port pour les sources issues de l’Amirauté) signalant un flux commercial, que cela soit une exportation ou une importation.",children:"?"}),' français se trouvant hors de la direction de Marseille, y compris dans le Ponant (eg. Saint-Malo, Nantes, Rouen, mais aussi Amiens, Charleville...). Ces rapporteurs français n’indiquent jamais autre chose que "Marseille" (ou "port de Marseille") pour leur commerce avec la direction de Marseille.']}),(0,dc.jsx)("p",{children:'Voyons maintenant le commerce rapporté par Marseille en tant que telle. Pas de difficulté du côté des importations rapportées par Marseille : elles sont toujours déclarées par le bureau de "Marseille".'}),(0,dc.jsx)("p",{children:'Les choses sont plus compliquées pour les exportations. Elles sont rapportées par trois bureaux différents : "Marseille" tout court (2202 flux en 1789), "Marseille - Domaine d\'Occident" (1359 flux) et "Marseille - Poids et Casse" (203 flux, où un flux représente l’enregistrement de l’importation ou de l’exportation d’un produit particulier entre un rapporteur et un partenaire). '}),(0,dc.jsx)("p",{children:'Rambert (1954, t. VI, p. 225), dans son Histoire du Commerce de Marseille, tome IV (consacré à la période de 1660 à 1789) donne les explications suivantes, essentiellement reprises de Jules Julliany (1842, tome 1, p. 86-87, 231 et 292) : "Les plus importants [bureaux] étaient au nombre de trois: le bureau du fameux droit de 20% perçu au profit de la Chambre de Commerce en même temps que le droit de Consulat; le bureau des fermes du domaine d\'Occident qui percevait un droit de 3% sur les marchandises d\'origine coloniale [nous comprenons "importations depuis les colonies"], enfin le bureau du Poids et Casse, où 75 peseurs publics procédaient au pesage des marchandises vendues sur place et percevaient au profit du Roi un droit qui avait été doublé en 1669". Et en note : "Colbert avait pris cette mesure pour donner au Roi une compensation aux pertes subies par l\'application de l\'édit du port franc. [nous comprenons "droit sur toutes les marchandises vendues à Marseille"]. C\'était le bureau le plus actif; il délivrait les acquits-à-caution, recevait les manifestes des capitaines et faisait visiter les colis à leur débarquement, percevait les droits sur les marchandises étrangères envoyées directement de Marseille aux colonies françaises et plombait celles qui étaient expédiées en transit". Nous ne savons pas si Rambert dit "le plus actif" pour dire "celui qui fait plus d\'opérations" ou pour signifier que "toutes les marchandises passent par là", comme il devrait être, vu qu\'il parle de "toutes les marchandises vendues à Marseille". '}),(0,dc.jsx)("p",{children:"Ces textes ne mentionnent que les importations de Marseille : pourtant dans les sources, ces bureaux ne rapportent que des exportations."}),(0,dc.jsxs)("p",{children:["Pour le bureau des Poids et Casse (203 flux), 202 flux (25 M de lt) sont en direction de Marseille. Il ne s’agit que de produits français. Il est donc plausible qu’il s’agisse d’exportations de la France vers le port franc de Marseille pour sa propre consommation, comme suggéré par Julliany et Rambert. Se pose la question d’un double compte éventuel avec les flux d’exportation des autres bureaux français vers Marseille (c. 17 M de lt",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Ce chiffre se décompose sur le graphique en 6,8 M venant des bureaux de France hors direction de Marseille ; 0,3 M venant d’Arles ; 2,8 M venant de La Penne ; 0,4 M venant de Lambesc et 6,6 M venant de Septèmes.",children:"?"}),") : les chiffres sont bien du même ordre de grandeur, mais il ne serait pas logique que l’ensemble des importations de Marseille depuis la France soit plus faible que les importations pour la sa propre consommation. Il nous semble donc plus plausible de penser que les 25 M de lt d’importations pour la consommation de Marseille s’ajoutent aux 16,5 M de lt importés dans le port franc pour ré-exportation. "]}),(0,dc.jsxs)("p",{children:['Le dernier flux issu du bureau des Poids et Casse est en direction des "Etats de l’Inde" (ANOM Col F2/B14, tableau 28) : 0,7 M de livres tournois. Le tableau précise "Marseille, Poids et Casse, Sous Pavillon Étranger" : il s’agit sans doute des envois du commerce privé de Marseille pour contourner le monopole de la Compagnie des Indes re-crée en 1785. Le tableau mentionne le reste du commerce (à la fois privé et par la Compagnie',(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"D’après Conan (1939, note 1 p. 164), il n’y a que deux expéditions de la Compagnie des Indes de 1785 durant toute son existence portà partir de Marseille.",children:"?"}),") lorsqu’il liste 0,8 M de lt d’exportations vers l’Isle de France et de Bourbon",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Soit, respectivement, l’actuelle île Maurice et l’actuelle île de la Réunion.",children:"?"}),', et 0,1 M de lt vers les "Etats de l’Inde issus de "Marseille, domaine d’Occident" (voir Carrière (1973, p. 345) et Dermigny (1959-1960, tome I, p. 155). Les produits ne sont précisés pour aucun de ces flux.']}),(0,dc.jsx)("p",{children:'Laissons de côté le commerce vers l’Asie. Il serait naturel que les exportations du bureau "Marseille, domaine d’Occident" soient formées des produits coloniaux en entrepôt. Les flux recouvrent en fait toutes les catégories de produits, et seulement 37 flux (sur 1 389) sont des produits coloniaux, exportés soit vers la France (hors Marseille) soit vers le Monde (hors colonies). Ces produits coloniaux ne sont que d’une valeur limitée (0,5 M de lt) et semblent ne pas provenir des colonies françaises de l’Amérique (la liste exhaustive en est : Café du Levant, Chocolat, Cannelle, Girofle, Poivre, Sucre candi et Thé). Il pourrait donc s’agir de produits coloniaux issus du commerce non-colonial ou asiatique (en petite quantité). À part les deux flux vers l’Asie déjà mentionnés, tous les flux viennent de la source AN F12 1666, qui est issue du travail de la Ferme.'}),(0,dc.jsx)("p",{children:'Les exportations de "Marseille" (930 flux) sont toutes soit des ré-exportations de produits coloniaux (9 flux et 25 M de lt), soit des exportations vers les colonies françaises de l’Amérique, le Sénégal ou la Guinée (921 flux et 15 M de lt). Ce sont ces flux qu’on s’attendrait à voir attribués au bureau "Marseille, domaine d’Occident". La source pour tous ces flux est ANOM Col F2/B14 (tableaux 5 et 20), qui est probablement issue du travail de l’Amirauté et de la Marine. '}),(0,dc.jsx)("p",{children:'Notre hypothèse est donc que la distinction entre le bureau exportateur "Marseille" et "Marseille, domaine d’Occident" (hors du commerce avec l’Asie) n’est qu’un effet de source. En tous les cas, nous ne trouvons pas d’explication logique à la distinction des deux bureaux. Par contre, le bureau exportateur "Marseille, Poids et Casse" ne porte que sur la consommation propre de la ville de Marseille. C’est surprenant car, d’après Leguay (2023), c’est plutôt le bureau des Poids et Casse qui s’occupait de l’établissement de la balance du commerce.'})]})}function oN(e){return(0,dc.jsx)("div",{id:"part-5",children:(0,dc.jsx)("p",{children:"Coucou"})})}function sN(e){const{Caller:t}=e.components||{};return t||function(){throw new Error("Expected component `Caller` to be defined: you likely forgot to import, pass, or provide it.")}(),(0,dc.jsxs)("div",{id:"part-6",children:[(0,dc.jsxs)("p",{children:["Le présent site a été réalisé dans le cadre du ",(0,dc.jsx)("a",{className:"c9",href:"https://anr.portic.fr/",rel:"noopener noreferrer",target:"_blank",children:"programme de recherche ANR PORTIC"}),". Ce programme porte sur les dynamiques de navigation et du commerce extérieur au dix-huitième siècle, un commerce qui s’effectue largement par voie maritime. Outre la meilleure compréhension de ces dynamiques par le croisement de deux jeux de données, un enjeu fondamental du programme est de chercher des méthodes de qualification et d’appréhension de l’incertitude des données historiques, en expérimentant des modes de visualisation et d’écriture appropriés."]}),(0,dc.jsxs)("p",{children:["Dans ce cadre, le Working Package n°5 de ce programme de recherche consiste à effectuer une série d’études de cas tirant parti de deux corpus existants de sources historiques numérisées : ",(0,dc.jsx)("a",{className:"c9",href:"http://navigocorpus.org/",rel:"noopener noreferrer",target:"_blank",children:"Navigocorpus"}),", une base de données portant sur l’histoire de la navigation pilotée par Silvia Marzagalli et Christine Plumejeaud ; et ",(0,dc.jsx)("a",{className:"c9",href:"http://toflit18.medialab.sciences-po.fr/#/home",rel:"noopener noreferrer",target:"_blank",children:"Toflit18"}),", une base de données portant sur le commerce extérieur de la France, pilotée par Loïc Charles et Guillaume Daudin. À ce titre, cette étude de cas s’inscrit dans un triptyque composé avec deux autres enquêtes publiées au format web : "]}),(0,dc.jsxs)("ul",{children:[(0,dc.jsxs)("li",{children:[(0,dc.jsx)("a",{className:"c9",href:"https://medialab.github.io/portic-storymaps-2021",rel:"noopener noreferrer",target:"_blank",children:"Commerce multi-échelles autour du port de La Rochelle au XVIII"}),(0,dc.jsx)("a",{className:"c9",href:"https://medialab.github.io/portic-storymaps-2021",rel:"noopener noreferrer",target:"_blank",children:"e"}),(0,dc.jsx)("a",{className:"c9",href:"https://medialab.github.io/portic-storymaps-2021",rel:"noopener noreferrer",target:"_blank",children:" siècle"})]}),(0,dc.jsxs)("li",{children:[(0,dc.jsx)("a",{className:"c9",href:"https://medialab.github.io/portic-storymaps-2022",rel:"noopener noreferrer",target:"_blank",children:"Commerce, contrebande et ports francs : le cas de Dunkerque au XVIII"}),(0,dc.jsx)("a",{className:"c9",href:"https://medialab.github.io/portic-storymaps-2022",rel:"noopener noreferrer",target:"_blank",children:"e"}),(0,dc.jsx)("a",{className:"c9",href:"https://medialab.github.io/portic-storymaps-2022",rel:"noopener noreferrer",target:"_blank",children:" siècle"})]})]}),(0,dc.jsx)("p",{children:"Ces réalisations visent à valoriser le travail déjà accompli lors de premières entreprises de numérisation pour chacune des deux bases (navigocorpus et toflit18), via l’étude approfondie de sous-ensembles signifiants dans les données. Ces études éclairent des questions disciplinaires existantes sous un nouveau jour grâce aux nouveaux matériaux et méthodes offerts par les bases de données mobilisées par le programme. Les questions soulevées par une telle initiative sont multiples :"}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"Comment mobiliser ensemble deux sources dont certaines dimensions sont incommensurables ou difficiles à mettre en équivalence ? Comment croiser les données numérisées des deux bases avec des connaissances plus denses et qualitatives sur les phénomènes étudiés, apportées par des historiens spécialistes de la région étudiée ? "}),(0,dc.jsx)("li",{children:"Comment prendre en compte, au moment de l’enquête et du raisonnement, l’importante stratification de transformations, de réductions et de décisions interprétatives constituant la chaîne d’opérations documentaires qui relie les sources initiales avec les données qui en ont été tirées ? "}),(0,dc.jsx)("li",{children:"Comment prendre en compte l’incertitude ou l’incomplétude des données tout en proposant une analyse scientifiquement solide des phénomènes étudiés ? "}),(0,dc.jsx)("li",{children:"Comment faire dialoguer les formes classiques de l’écriture historique - le récit déployé phrase après phrase, l’argument déroulé paragraphe par paragraphe - avec les formes d’écriture diagrammatique et computationnelle qu’implique la composition d’un site web ? "}),(0,dc.jsx)("li",{children:"Comment gérer la collaboration interdisciplinaire et la partition d’expertises qu’implique une telle écriture multimodale ?"})]}),(0,dc.jsx)("p",{children:"Toutes ces questions ont été travaillées lors du processus de collaboration qui a mené à l’élaboration de ce site, dont voici un bref récit à des fins de documentation et de modeste retour d’expérience pratique et méthodologique pour d’autres recherches similaires."}),(0,dc.jsx)("h2",{id:"h.dru36nbx6gy9",children:"D’une série de questionnements à une semaine d’enquête"}),(0,dc.jsxs)("p",{children:["L’étude de cas dont ce site est l’aboutissement a été articulée autour d’un format de collaboration intensive que nous appelons datasprint",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":'Venturini, Tommaso, Anders Munk, and Axel Meunier. "Data-sprinting: A public approach to digital research." Routledge handbook of interdisciplinary research methods. Routledge, 2018. 158-163.',children:"?"})," et qui consiste à faire travailler ensemble des expert.e.s de plusieurs disciplines sur un temps court et avec des questions de recherche déterminées à l’avance, sur la base d’un ou plusieurs jeux de données préparés pour l’occasion."]}),(0,dc.jsx)("p",{children:"En amont du datasprint, nous avons conduit pendant plusieurs mois un double travail de préparation des données, et de préparation des questions de recherche. "}),(0,dc.jsx)("p",{children:"Sur le plan des données, les équipes de Navigocorpus et de Toflit18 ont pu bénéficier de l’important travail de nettoyage et d’affinement concernant les espaces et les périodes étudiées déjà réalisé dans le cadre du datasprint sur la région de La Rochelle et de celui sur Dunkerque. Pour celui-ci, les données navigocorpus relatives à Marseille ont notamment fait l’objet d’une attention particulière et d’un important travail de curation et de vérification par Silvia Marzagalli, Christine Plumejeaud et Pierre Niccolo’ Sofia, chercheur post-doctoral ayant rejoint le programme pour sa dernière année. Différentes sources complémentaires aux deux bases principales ont également été explorées et parfois transcrites en vue de la semaine de travail."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{className:"is-invalid",id:"schemas-generaux"})}),(0,dc.jsx)("p",{children:"Sur le plan de la préparation des questions de recherche, nous avons conduit une série de réunions préliminaires reliées par des documents en ligne rédigés collaborativement, qui nous ont aidé à identifier des questions pertinentes en regard de l’histoire de Marseille et de la littérature existante, mais aussi compatibles avec ce que les données nous permettaient - ou pas - d’explorer et de visualiser. Ce travail d’ajustement et de mise en correspondance entre les questions et les données a ainsi couru sur plusieurs mois et a notamment profité d’un très important travail d’état de l’art bibliographique effectué par Pierre Niccolo’ Sofia. Il nous a permis à la fois d’identifier les activités d’exploration les plus pertinentes à proposer aux participants durant l’atelier, et d’éviter les chausses-trappes qui nous auraient conduit dans des questionnements impossibles à résoudre."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{className:"is-invalid",id:"modules-screencast"})}),(0,dc.jsxs)("p",{children:["La semaine de collaboration intensive a ainsi été préparée pour être structurée autour de modules ou pistes d’enquête, associant pour chacune : les questions historiques et économiques à explorer, la bibliographie pertinente pour ces questions, un balisage technique sur les données à considérer dans les bases de données, et des prémices de questions opérationnalisables à travers l’analyse et la visualisation des données, à développer ensuite avec les ingénieurs et designers mobilisés pour l’atelier. La vidéo ci-dessus présente un aperçu rapide du format de ces documents préparatoires. Contrairement aux années précédentes où les modules se voulaient des pistes d’exploration à réarticuler avec un plan argumentatif à la suite des enquêtes, nous avons fait le choix, pour cette dernière étude de cas, d’établir un plan argumentatif en amont et d’y indexer les différents modules de travail, afin de s’assurer de pouvoir couvrir l’ensemble du travail préparatoire nécessaire à établir la publication finale dans le cadre de la semaine de datasprint. Ce choix, informé par les difficultés rencontrées pour la deuxième étude de cas sur Dunkerque, dues à un trop grand travail exploratoire reporté à l’après-datasprint",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Voir l’étude de cas Commerce, contrebande et ports francs : le cas de Dunkerque au XVIIIe siècle",children:"?"}),", a ancré la semaine de datasprint dans une perspective beaucoup plus opérationnelle que les précédentes, favorisant une plus grande efficacité, mais amoindrissant la dimension exploratoire et expérimentale qui fait d’habitude souvent le plaisir de la participation à un datasprint."]}),(0,dc.jsx)("p",{children:"La semaine de datasprint s’est déroulée en février 2023 au CAES du CNRS La Ville Perrotine, sur l’île d’Oléron. Littéralement isolés, dans un bâtiment de travail situé sur une île au milieu du complexe CNRS lui-même, nous avons passé une semaine en circuit fermé dans un bâtiment nous offrant trois salles de travail nous permettant d’alterner phases de plénières et sessions de travail en petits groupes."}),(0,dc.jsx)("p",{children:'La semaine de travail a été organisée autour d’une infrastructure à la fois spatiale et numérique articulée autour des modules d’enquêtes élaborés pour la préparation de la semaine de travail. Sur le plan spatial, le lieu de travail a été agencé en fonction d’un grand espace d’affichage commun, placé sur l’un des murs de la salle principale, que nous avons utilisé pour nous répartir les tâches à effectuer et pour partager de manière passive les résultats en train d’être produits. Chaque espace du mur s’est vu dédié à l’un des "modules d’enquête" définis avant le datasprint, et les personnes qui ont travaillé à chacun de ces modules y ont progressivement accolé visualisations, post-its d’analyse ou d’avertissement sur des points d’attention relatifs aux données, croquis de visualisations à effectuer, etc. Autour de cette surface d’affichage partagé, différents groupes constitués de 2 à 5 personnes, et toujours mixtes du point de vue des compétences apportées, se sont formés et répartis sur l’ensemble des salles et espaces disponibles dans les locaux du médialab à Sciences Po.'}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{className:"is-invalid",id:"photos-datasprint"})}),(0,dc.jsx)("p",{children:"Sur le plan numérique, le collectif d’enquête a été structuré autour de l’utilisation d’un dossier google drive partagé, organisé en dossiers correspondant aux modules d’enquêtes, et d’un répertoire de code source sur la plateforme github, utilisé par toutes les personnes sachant programmer pour partager des scripts et des fichiers de données utiles."}),(0,dc.jsx)("p",{children:"Le datasprint s’est terminé sous la forme d’une plénière durant laquelle l’ensemble des résultats ont été présentés et discutés, ainsi que d’une discussion générale sur l’expérience des datasprints et des études de cas PORTIC. L’atelier a abouti à la rédaction d’un premier document de rédaction martyre partiellement rédigé, intégrant dans un fil argumentatif déjà très abouti l’ensemble des productions réalisées durant la semaine sous la forme de copies d’écran ou de croquis. Nous avons collectivement convenu que cette expérience, comparée aux deux précédentes, avait été la plus efficace et productive, peut-être du fait du contexte social et géographique de la semaine de travail en vase clos, ou encore de la préparation très dense des modules de travail et de leur articulation a priori à un plan de publication ; mais qu’elle avait également été la plus intense et la plus fatigante, du fait du rythme de production extrêmement soutenu qui a été adopté par les ingénieur·es pour la réalisation des dizaines de visualisations ayant émergé de la semaine, et pour les économistes et historien·nes pour l’élaboration d’un argument commun dans un temps très contraint. "}),(0,dc.jsx)("h2",{id:"h.fxih2baprl8o",children:"La fabrication d’un site web comme pivot pour une collaboration interdisciplinaire"}),(0,dc.jsx)("p",{children:"À la suite du datasprint, nous avons convenu d’une méthodologie de travail consistant à laisser les designers du projet reprendre la main sur la structuration de la publication en se faisant force de proposition pour des visualisations de communication à même d’orienter la rédaction des textes finaux. Pour ce faire, un tandem composé de Paul Girard et Robin de Mourat a effectué pendant plusieurs jours un travail de conception et de synthèse graphique visant à proposer une série de quelques visualisations significatives et à même de porter la structure argumentative esquissée collectivement durant la semaine de travail."}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{className:"is-invalid",id:"maquettes-visualisations"})}),(0,dc.jsx)("p",{children:"Ces dernières propositions ont été discutées et amendées avec les personnes en charge de la rédaction des textes, puis intégrées dans un brouillon de site mis à jour quotidiennement qui a permis aux historiennes et économistes de se projeter et construire un texte directement connecté aux visualisations."}),(0,dc.jsx)("p",{children:'Afin d’élaborer un document propre à être publié et à transmettre un récit et des arguments à partir des données des deux bases, nous avons donc, comme pour les deux études précédentes, tenté d’utiliser la perspective de la fabrication d’un site pour articuler trois types "d’écriture" : la confection de nouveaux fichiers de données correspondant aux enquêtes soulevées par les activités de la semaine (écriture computationnelle) ; la confection de visualisations d’informations (écriture diagrammatique) ; enfin, bien sûr, la mise en récit et en argument historique de l’étude de cas (écriture en prose).'}),(0,dc.jsx)("p",{children:'Dans ce cadre, nous avons mis en place une infrastructure de travail visant à développer progressivement le présent site web alors même que ses "contenus" textuels et graphiques étaient encore en cours d’élaboration. Le site web en construction a ainsi tout autant servi d’objectif que de moyen de rencontre entre les différentes activités qui ont suivi la semaine d’atelier datasprint.'}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{className:"is-invalid",id:"processus-maj"})}),(0,dc.jsxs)("p",{children:["La fabrication du site présenté au public a été articulée autour d’un protocole automatisé qui a permis de mettre le site à jour quotidiennement pendant sa phase d’écriture et de développement, et ainsi de faire progresser conjointement sa structure, son aspect graphique et les divers contenus qui le peuplent (voir son ",(0,dc.jsx)("a",{className:"c9",href:"https://github.com/medialab/portic-storymaps-2022",rel:"noopener noreferrer",target:"_blank",children:"répertoire github"})," pour plus d’informations). Plus précisément, ce protocole automatisé consistait à récupérer les contenus écrits dans un google documents écrit par les historien.ne.s, les données des bases Navigocorpus et Toflit18 sur leurs espaces numériques respectifs, et enfin à produire un ensemble de données optimisées pour le web avant de refabriquer le site."]}),(0,dc.jsx)("p",{children:'Cette méthode de travail sur mesure nous a permis de multiplier les itérations sur les données, les visualisations et les textes, afin de développer progressivement un document ajusté et cohérent pour la lecture. Elle nous a également permis d’échapper à une approche qui voudrait formater la production du site de manière trop séquentielle, c’est-à-dire faisant suivre un premier temps de "conception" puis un deuxième temps "d’exécution", pour plutôt faire place à la découverte et au dialogue avec les différents matériaux en train de se développer. Elle a permis de travailler de manière progressive les rapports entre les différents types d’écriture, en testant par exemple les rapports entre textes et images au moyen de croquis papier directement intégrés dans le site pour permettre aux historiennes et économistes de se projeter dans le résultat final pendant que les visualisations finalisées étaient élaborées.'}),(0,dc.jsx)("p",{children:"Ainsi, la méthode de travail et de montage du site adoptée ici, outre la dimension d’optimisation qu’implique l’automatisation de certaines tâches, a été envisagée comme le moyen de favoriser un dialogue plus organique entre les différentes écritures en jeu dans ce document : en réalisant simultanément le design du site, celui des visualisations, et les textes qui les accompagnent, nous avons tenté de faire profiter chacune de ces activités l’une de l’autre, comme des sources d’invention ou de solidification mutuelle, plutôt que de les considérer comme des tâches spécialisées et/ou articulées selon un régime de subordination (de l’histoire à la technique, ou du visuel au textuel, ou de l’argument à son illustration, etc.). "}),(0,dc.jsx)("h2",{id:"h.ub5q8dkj8ap1",children:"Un document destiné à tisser des liens avec d’autres activités et d’autres publics"}),(0,dc.jsx)("p",{children:'Ce document web est pensé comme un objet autonome déroulant le récit scientifique de l’histoire de Marseille au dix-huitième siècle, mais aussi comme le point de départ d’assemblages scientifiques et didactiques encore à venir. Afin de qualifier le registre d’écriture et le degré de complexité que nous nous autoriserions, nous avons convenu de le fabriquer avec l’idée de l’adresser à un public "intermédiaire" (ni celui d’un "grand public" toujours insaisissable, ni celui de "pairs" avec lesquels nous interagissons via d’autres types de documents), c’est-à-dire un public constitué d’étudiant.e.s en histoire, de professeur.e.s d’histoire du secondaire, ou d’amateur.ice.s avancés passionnés par le commerce et la navigation d’Ancien Régime ou la question de la contrebande. Cependant, le site est également pensé pour pouvoir s’articuler avec deux publics complémentaires :'}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"les personnes spécialisées dans la médiation et/ou la vulgarisation, qui pourront utiliser certaines des visualisations ici présentes pour des initiatives destinées à un plus grand public;"}),(0,dc.jsx)("li",{children:"les historien.ne.s spécialisés, qui pourront citer ces visualisations dans des publications conventionnelles en revues ou monographies et ainsi s’appuyer sur ces dernières pour continuer nos enquêtes ou les faire travailler de manière plus avancée"})]}),(0,dc.jsx)("p",{children:'Pour ce faire, nous avons notamment rendu chacune des visualisations "détachable" du récit proposé via la page Atlas - et plus techniquement en dotant chacune des visualisations d‘une adresse URL propre.'}),(0,dc.jsxs)("p",{children:["Par ailleurs, le ",(0,dc.jsx)("a",{className:"c9",href:"https://github.com/medialab/portic-storymaps-2023",rel:"noopener noreferrer",target:"_blank",children:"code source du site"}),", partagé sous licence libre, a été construit et documenté de manière à pouvoir être dérivé - en tout ou partie - pour d’autres projets à venir. Il est enfin à noter que toutes les données utilisées - et les scripts qui les génèrent à partir des données complètes de Toflit18 et Navigocorpus, accessibles toutes les deux librement - sont également inclus dans le code source du site, rendant nos visualisations et résultats entièrement reproductibles."]}),(0,dc.jsx)("h2",{id:"h.jhdiwhxrxrb0",children:"Coda : un travail de documentation réflexive sur les pratiques de recherche interdisciplinaire en humanités numériques à travers le cas du programme PORTIC"}),(0,dc.jsx)("p",{children:"En parallèle et en complément du travail relatif à l’étude de cas ici présente, nous avons également profité de la dernière année du programme PORTIC pour engager un travail de documentation et de réflexion épistémologique et méthodologique sur l’ensemble de l’expérience qu’ont constitué les nombreuses années sur lesquelles s’est écoulé le programme PORTIC."}),(0,dc.jsxs)("p",{children:["PORTIC",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Ports et Technologies de l’Information et de la Communication. Site du programme : https://anr.portic.fr/",children:"?"})," est un programme de recherche typique des humanités numériques et de l’histoire quantitative contemporaine : il s’inscrit dans la suite de très longues opérations de numérisation de sources historiques conduites sur plusieurs années, pour maintenant, dans un second temps, tenter de les valoriser sur les plans scientifique et social. Après des années passées dans l’ombre des archives et dans l’enfer des bases de données, des arguments commencent à être produits, des outils d’exploration développés, des visualisations réalisées. Ce deuxième souffle du tournant numérique de la recherche historique est également un deuxième souffle de l’interdisciplinarité et de la collaboration. En effet, il demande, pour réfléchir, écrire et publier à partir de ces sources numérisées, d’inventer de nouvelles formes de mise en commun et de dialogue entre des disciplines aussi variées que l’histoire, l’économie, la géomatique et le design."]}),(0,dc.jsx)("p",{children:"Dans ce cadre, le recours à la production de graphiques et à la fabrication de statistiques, bien qu’indispensable pour élaborer des connaissances pertinentes à propos de sources numérisées impliquant des données quantitatives, peut être problématique : il a tendance à donner une impression d’immédiateté et d’évidence à des arguments qui sont pourtant le fruit d’une longue et hétérogène chaîne de pratiques, et l’objet de nombreuses incertitudes avec lesquelles les collectifs de recherche doivent constamment se frotter et composer pour élaborer leur pensée. "}),(0,dc.jsx)("p",{children:"Nous sommes face à un double défi : d’une part, il s’agit de situer davantage les nombres et les images que produisent nos recherches dans la généalogie des pratiques qui leur ont donné naissance, afin de mieux les comprendre, les discuter et se les approprier ; mais il s’agit aussi de déjouer la tendance des formats conventionnels de communication scientifique à occulter la richesse intellectuelle du processus de collaboration interdisciplinaire lui-même. Ces derniers formats conventionnels (articles, communications dans colloques, monographies) se concentrent en effet souvent sur les résultats disciplinaires au détriment des petites découvertes, des avancées faites en cours de route, des déboires et épreuves instructives, etc. "}),(0,dc.jsx)("p",{children:"Dans ce cadre, nous avons essayé de décrire, de qualifier et de valoriser ce que la collaboration interdisciplinaire fait aux disciplines et aux métiers qu’elle met en relation, ainsi que les pratiques et situations multiples - et parfois insolites - par lesquelles se font les découvertes dans ces contextes. Il s’agit aussi de situer et de qualifier épistémologiquement les productions non-discursives (nombres, images, interfaces, ...) générées par PORTIC vis-à-vis de la généalogie des pratiques et procédures qui les ont produites. Il est enfin nécessaire de trouver un mode de mise en discussion du programme PORTIC adapté à ses problématiques centrales : la gestion fine de l’incertitude historique, et la place de la matérialité (numérique) et de la visualité dans l’étude de l’histoire économique et maritime du XVIIIème siècle."}),(0,dc.jsx)("p",{children:'Plutôt que de produire un discours et des images bien lissées, nous voulons donc conclure la série des trois études de cas du programme de recherche PORTIC par un document ouvrant la porte de la "cuisine" de notre recherche en humanités numériques. Il s’agit de produire une description fidèle et ouverte de la collaboration interdisciplinaire dans toute sa complexité et son hétérogénéité, sans préjuger des dimensions ou opérations les plus décisives dans la conduite d’une telle aventure.'}),(0,dc.jsx)("p",{children:'Nous souhaitons donc proposer une restitution des études de cas du programme du point de vue de leur méthodologie et de leur déroulement pratique, sous la forme d’un "making of scientifique" audiovisuel de la dernière étude de cas de PORTIC, portant sur le commerce et la navigation de Marseille au dix-huitième siècle. Il s’agit de donner à voir comment peut se conduire une recherche interdisciplinaire en humanités numériques, depuis les premières réunions de préparation jusqu’à la longue traîne de la finition d’une publication, en passant par les moments décisifs de collaboration face à face.'}),(0,dc.jsx)("h3",{id:"h.roq1lak7f6o",children:'"S’entendre. L’interdisciplinarité en pratique" : un documentaire sur l’étude de cas réalisé par Fabien Luszezyszyn et Aymeric Poidevin'}),(0,dc.jsx)("p",{children:(0,dc.jsx)(t,{className:"is-invalid",id:"documentaire-s-entendre"})}),(0,dc.jsxs)("p",{children:['Le document résultant de notre démarche s’intitule "S’entendre. L’interdisciplinarité en pratique." Il a été réalisé par Fabien Luszezyszyn et Aymeric Poidevin (',(0,dc.jsx)("a",{className:"c9",href:"https://lascopdessalesgosses.com/",rel:"noopener noreferrer",target:"_blank",children:"scop des sales gosses"}),") à la demande de l'équipe de l'ANR PORTIC, qui nous ont suivi et filmé durant l’entièreté de la semaine du datasprint, du 27 février au 3 mars 2023. "]}),(0,dc.jsx)("p",{children:"Ce documentaire permet d’appréhender les motifs et les enjeux de l'engagement de chacun au service du projet commun, la diversité des langages et des pratiques impliquées dans l’enquête collective, l'intensité des échanges qui continuent au-delà des horaires pourtant très intenses des journées de travail, sans masquer les tensions, la fatigue, les frustrations suscitées par la collaboration. Finalement, loin des discours prophétiques, réducteurs ou généralisants à propos de la collaboration entre les disciplines dans des cadres impliquant le travail des données numériques, nous avons voulu partager une description située et réaliste de la fabrique de l'interdisciplinarité."}),(0,dc.jsx)("p",{children:"Ce document a avant tout un objectif scientifique : celui de décrire une trajectoire de collaboration interdisciplinaire à l’œuvre (et peut-être la comparer avec les modèles produits par les écrits positionnels et les demandes de financement en humanités numériques). À partir de ce dernier, que nous allons nous employer à valoriser dans des contextes multiples à venir, nous entendons nourrir une discussion sincère et fructueuse à propos des multiples enjeux qui sous-tendent la collaboration interdisciplinaire, et donner l’envie de prolonger cette expérience réflexive par de nouvelles initiatives."}),(0,dc.jsx)("h3",{id:"h.lnpq3tkc5k0l",children:"Faire l’histoire de PORTIC : vers une archive multimodale d’une rare richesse pour la compréhension des enjeux et dynamiques de collaboration interdisciplinaire"}),(0,dc.jsxs)("p",{children:["En parallèle de la réalisation du documentaire, nous avons engagé un travail (encore) plus ambitieux d’archivage ayant vocation à constituer un fonds numérique multimodal et hétérogène regroupant l’ensemble des traces dont nous disposons pour rendre compte de la conduite de la troisième étude de cas de PORTIC ici présentée. Pour ce faire, nous avons enregistré la plupart des réunions préliminaires au datasprint",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Réalisées pour la plupart via la plateforme Zoom.",children:"?"}),", sauvegardé l’ensemble des documents et codes produits, et envisageons également de faire un travail de sélection et de préparation dans nos échanges mails pertinents pour la compréhension des dynamiques de collaboration en jeu. À partir de ce travail, nous entendons constituer une archive d’une richesse rare qui permettra à des collègues intéressés différents aspects de notre expérience d’y porter un regard et une analyse nouvelle. Cette archive, qui devrait être mise en ligne d’ici l’année 2025, sera limitée en accès mais décrite en détail afin de permettre de nouvelles collaborations impliquant des personnes tierces et des anciens membres du programme PORTIC dans l’analyse commune de ce matériau."]}),(0,dc.jsx)("p",{children:"Les réflexions individuelles et premières discussions nous ont permis d’esquisser une série de questionnements qui permettraient d’interroger le matériau que nous sommes en train d’archiver. En voici quelques uns en guise d’exemple :"}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:'habitus disciplinaires et trajectoires (parfois chaotiques) de coordination : tactiques de traduction et de clarification depuis un jargon disciplinaire vers un autre, rétablissement de situations d’anomie/confusion, "sauts disciplinaires" à négocier pendant les discussions collectives et les phases de travail individuelles de chacun - comment se parle-t-on dans un processus interdisciplinaire ?'}),(0,dc.jsx)("li",{children:"conditions de travail, contexte institutionnel et inscription socio-professionnelle du projet : question des rythmes du travail sur projet/calendrier/milestones, de la multi-activité des personnels (entre plusieurs projets, entre recherche et enseignement, ...), des rapports de domination (disciplinaires, statutaires), des processus de délégation"}),(0,dc.jsx)("li",{children:'interdisciplinarité et spécialisation : dynamiques d’apprentissage (mutuel) ou au contraire de délimitation de frontières ("ce n’est pas de mon ressort") dans le cours des situations - place de la spécialisation/technicité dans ces processus - faut-il essayer de construire un langage commun ou apprendre à devenir l’autre ?'}),(0,dc.jsx)("li",{children:"relation entre sémiologie et épistémologie : processus de traduction hétérogènes depuis les sources jusqu’aux documents produits - comment la circulation générative des hypothèses à travers différents langages et systèmes de signes (texte, code, tableaux, images) produit-elle des arguments et des hypothèses ? et comment la qualifier ? "}),(0,dc.jsx)("li",{children:'place de la matérialité dans le processus de recherche : quel est le rôle de l’espace, de la scénographie, des objets dans ces projets à dominante "numérique" ?'}),(0,dc.jsx)("li",{children:"incertitude et négociation : comment gère-t-on la dimension d’incertitude très forte de notre recherche dans les discussions et les processus de prise de décision à l’intérieur du collectif ?"}),(0,dc.jsx)("li",{children:'intérieur et extérieur - rapport entre écriture (collective) et publication : comment la constitution d’un "nous" au fil du processus du projet et d’un "eux" destinataire de la publication structure-t-elle la formulation des arguments et le choix de ce qui doit être mis en coulisse ou sur le devant de la scène ?'})]}),(0,dc.jsx)("p",{children:"Ces pistes de réflexion sont appelées à évoluer et se préciser au fil du développement de ce projet, mais aussi et surtout par le contact avec des partenaires extérieurs aptes à collaborer avec nous pour tirer le plus d’apprentissages possibles de notre expérience de collaboration. Nous accueillons en ce sens avec le plus vif intérêt d’éventuelles manifestations d’intérêt de la part de personnes versées dans l’anthropologie des sciences et des pratiques savantes, dans l’anthropologie filmique, dans le champ des réflexions méthodologiques et épistémologiques à propos des humanités numériques, ou encore dans le champ de la recherche en design. En parallèle de cet appel et du travail d’archivage susmentionné qui suit son cours, nous envisageons également l’écriture d’un texte à plusieurs voix développant des pistes d’analyse de ce matériau archivistique à partir de nos points de vue de parties prenantes aux sensibilités variées."}),(0,dc.jsx)("h2",{id:"h.bm38bbekxtmz",children:"Une écriture collective : remerciements"}),(0,dc.jsx)("p",{children:"Ce site est le résultat d’un processus d’enquête et d’écriture collective qui a mobilisé des personnes issues de plusieurs disciplines : histoire, économie, informatique, géomatique, design. "}),(0,dc.jsxs)("p",{children:["Les textes de cette publication ont été écrits par ",(0,dc.jsx)("a",{className:"c9",href:"https://cmmc-nice.fr/membres-du-cmmc/silvia-marzagalli/",rel:"noopener noreferrer",target:"_blank",children:"Silvia Marzagalli"})," (professeur d’histoire moderne, Université Côte d’Azur - CMMC, coordinatrice et co-responsable scientifique du programme PORTIC), ",(0,dc.jsx)("a",{className:"c9",href:"https://www.ined.fr/fr/recherche/chercheurs/Charles%252BLo%2525C3%2525AFc",rel:"noopener noreferrer",target:"_blank",children:"Loïc Charles"})," (professeur d’économie, INED, Université Paris 8 Vincennes - LED), ",(0,dc.jsx)("a",{className:"c9",href:"https://leda.dauphine.fr/fr/membre/detail-cv/profile/guillaume-daudin.html",rel:"noopener noreferrer",target:"_blank",children:"Guillaume Daudin"})," (professeur d’économie, Université Paris-Dauphine - LEDa-DIAL), ",(0,dc.jsx)("a",{className:"c9",href:"https://criham.labo.univ-poitiers.fr/membres/thierry-sauzeau/",rel:"noopener noreferrer",target:"_blank",children:"Thierry Sauzeau"})," (professeur d’histoire moderne, Université de Poitiers - Criham) et ",(0,dc.jsx)("a",{className:"c9",href:"https://www.cairn.info/publications-de-Pierre-Niccol%25C3%25B2-Sofia--794286.htm",rel:"noopener noreferrer",target:"_blank",children:"Pierre Niccolo’ Sofia"})," (chercheur post-doctoral du programme PORTIC, Université Côte d’Azur - CMMC)."]}),(0,dc.jsxs)("p",{children:["L’ensemble du processus de médiation et d’articulation technique de la collaboration a été conduit par ",(0,dc.jsx)("a",{className:"c9",href:"https://medialab.sciencespo.fr/equipe/robin-de-mourat/",rel:"noopener noreferrer",target:"_blank",children:"Robin de Mourat"})," (designer de recherche permanent, médialab Sciences Po - co-responsable scientifique du programme PORTIC en charge des études de cas), appuyé par ",(0,dc.jsx)("a",{className:"c9",href:"https://fr.linkedin.com/in/paul-girard-57822118",rel:"noopener noreferrer",target:"_blank",children:"Paul Girard"})," (ingénieur expert en humanités numériques - entreprise ",(0,dc.jsx)("a",{className:"c9",href:"https://www.ouestware.com/",rel:"noopener noreferrer",target:"_blank",children:"Ouestware"}),")."]}),(0,dc.jsxs)("p",{children:["Les visualisations ont été conçues et développées par ",(0,dc.jsx)("a",{className:"c9",href:"https://medialab.sciencespo.fr/equipe/robin-de-mourat/",rel:"noopener noreferrer",target:"_blank",children:"Robin de Mourat"})," et ",(0,dc.jsx)("a",{className:"c9",href:"https://fr.linkedin.com/in/paul-girard-57822118",rel:"noopener noreferrer",target:"_blank",children:"Paul Girard"}),"."]}),(0,dc.jsxs)("p",{children:["Les fonds de carte d’époque ont été constitués par ",(0,dc.jsx)("a",{className:"c9",href:"https://lienss.univ-larochelle.fr/Plumejeaud-Christine-954",rel:"noopener noreferrer",target:"_blank",children:"Christine Plumejeaud"}),"."]}),(0,dc.jsxs)("p",{children:["La préparation et la vérification des données a été effectuée par les équipes de Navigocorpus (",(0,dc.jsx)("a",{className:"c9",href:"https://cmmc-nice.fr/membres-du-cmmc/silvia-marzagalli/",rel:"noopener noreferrer",target:"_blank",children:"Silvia Marzagalli"}),", ",(0,dc.jsx)("a",{className:"c9",href:"https://lienss.univ-larochelle.fr/Plumejeaud-Christine-954",rel:"noopener noreferrer",target:"_blank",children:"Christine Plumejeaud"}),", ",(0,dc.jsx)("a",{className:"c9",href:"https://www.cairn.info/publications-de-Pierre-Niccol%25C3%25B2-Sofia--794286.htm",rel:"noopener noreferrer",target:"_blank",children:"Pierre Niccolo’ Sofia"}),") et de Toflit18 (",(0,dc.jsx)("a",{className:"c9",href:"https://leda.dauphine.fr/fr/membre/detail-cv/profile/guillaume-daudin.html",rel:"noopener noreferrer",target:"_blank",children:"Guillaume Daudin"}),", ",(0,dc.jsx)("a",{className:"c9",href:"https://www.ined.fr/fr/recherche/chercheurs/Charles%2BLo%25C3%25AFc",rel:"noopener noreferrer",target:"_blank",children:"Loïc Charles"}),")."]}),(0,dc.jsxs)("p",{children:["Le site a été développé par ",(0,dc.jsx)("a",{className:"c9",href:"https://medialab.sciencespo.fr/equipe/robin-de-mourat/",rel:"noopener noreferrer",target:"_blank",children:"Robin de Mourat"}),", sur la base technique des deux précédentes expérimentations qui avaient été développées avec ",(0,dc.jsx)("a",{className:"c9",href:"https://fr.linkedin.com/in/c%2525C3%2525A9cile-asselin-3659541b7",rel:"noopener noreferrer",target:"_blank",children:"Cécile Asselin"})," en 2021 puis avec ",(0,dc.jsx)("a",{className:"c9",href:"http://www.myllaume.fr/",rel:"noopener noreferrer",target:"_blank",children:"Guillaume Brioudes"})," en 2022."]}),(0,dc.jsxs)("p",{children:["À ces personnes s’ajoutent celles ayant participé au datasprint qui a conduit à cette publication, sans qui cette étude de cas n’aurait pas été possible, et que nous remercions très chaleureusement : les ingénieurs en méthodes numériques du laboratoire médialab de Sciences Po ",(0,dc.jsx)("a",{className:"c9",href:"https://medialab.sciencespo.fr/equipe/diego-antolinos-basso/",rel:"noopener noreferrer",target:"_blank",children:"Diégo Antolinos-Basso"}),", ",(0,dc.jsx)("a",{className:"c9",href:"https://medialab.sciencespo.fr/equipe/ines-girard/",rel:"noopener noreferrer",target:"_blank",children:"Inès Girard"}),", ",(0,dc.jsx)("a",{className:"c9",href:"https://medialab.sciencespo.fr/equipe/kelly-christensen/",rel:"noopener noreferrer",target:"_blank",children:"Kelly Christensen"}),", ",(0,dc.jsx)("a",{className:"c9",href:"https://bmaz.github.io/",rel:"noopener noreferrer",target:"_blank",children:"Béatrice Mazoyer"})," et ",(0,dc.jsx)("a",{className:"c9",href:"https://medialab.sciencespo.fr/equipe/benjamin-ooghe-tabanou/",rel:"noopener noreferrer",target:"_blank",children:"Benjamin Ooghe-Tabanou"}),"."]})]})}function lN(e){return(0,dc.jsx)("div",{id:"part-6",children:(0,dc.jsx)("p",{children:"."})})}function uN(e){return(0,dc.jsxs)("div",{id:"part-7",children:[(0,dc.jsx)("h2",{id:"h.cbk6c4v18uxg",children:"Sources"}),(0,dc.jsxs)("p",{children:["Base de données Navigocorpus - Portic: voir ",(0,dc.jsx)("a",{className:"c9",href:"https://anr.portic.fr/",rel:"noopener noreferrer",target:"_blank",children:"https://anr.portic.fr/"})," "]}),(0,dc.jsxs)("p",{children:["Toflit18: voir ",(0,dc.jsx)("a",{className:"c9",href:"https://toflit18.medialab.sciences-po.fr/#/home",rel:"noopener noreferrer",target:"_blank",children:"https://toflit18.medialab.sciences-po.fr/#/home"})," "]}),(0,dc.jsx)("p",{children:"Baehrel René, Une croissance : la Basse-Provence rurale de la fin du seizième siècle à 1789 essai d'économie historique statistique, Paris, éditions de l’EHESS, 2 vols, 1988 (1ère édition, 1959)."}),(0,dc.jsx)("p",{children:"Carrière Charles, Négociants marseillais au XVIIIe siècle. Contribution à l'étude des économies maritimes, Marseille, Institut historique de Provence, 1973, 2 tomes."}),(0,dc.jsx)("p",{children:"Carrière Charles et Coudurié Marcel, « L’espace commercial marseillais aux XVIIe et XVIIIe siècles », dans Pierre Léon (dir.), Aires et structures du commerce français au XVIIIe siècle. Colloque national de l’AFHE, Paris, CNRS, 4-6 octobre 1973, Lyon, Centre d'histoire économique et sociale de la région lyonnaise, 1975, p. 75-106."}),(0,dc.jsx)("p",{children:'Federico, G., Schulze, M. S., & Volckart, O. (2021). "European goods market integration in the very long run: from the Black Death to the First World War." The Journal of Economic History, 81(1), 276-308.'}),(0,dc.jsx)("p",{children:"Romano Ruggiero, Commerce et prix du blé à Marseille au XVIIIe siècle, Paris, Armand Colin, 1956."}),(0,dc.jsx)("p",{children:"Les sources archivistiques ont été indiquées directement dans le corps du texte et dans l’annexe."}),(0,dc.jsx)("h2",{id:"h.bxam7tthku9i",children:"Références bibliographiques"}),(0,dc.jsx)("p",{children:"ABÉNON, Lucien-René, « Marseille et les îles au XVIIIe siècle », dans Jean-René Gaborit, Circulation des matières premières en Méditerranée : transferts de savoirs et de techniques. Actes du 128e Congrès national des sociétés historiques et scientifiques, « Relations, échanges et coopération en Méditerranée », Bastia, 2003, Paris, Editions du CTHS, 2009, p. 7-15."}),(0,dc.jsx)("p",{children:"ANDERSEN, Dan, The Danish Flag in the Mediterranean. Shipping and Trade, 1747-1807, Ph.D. thesis, University of Copenhagen, 2000."}),(0,dc.jsx)("p",{children:"BAEHREL, René, Une croissance : la Basse-Provence rurale de la fin du seizième siècle à 1789 essai d'économie historique statistique, Paris, éditions de l’EHESS, 2 vols, 1988 (1ère édition, 1959). "}),(0,dc.jsx)("p",{children:"BOUBAKER, Sadok, La régence de Tunis au XVIIe siècle ses relations commerciales avec les ports de l'Europe méditerranéenne, Marseille et Livourne, Zaghouan, Ceroma, 1987."}),(0,dc.jsx)("p",{children:"BOULANGER, Patrick, « Le commerce maritime des huiles durant les guerres de la seconde moitié du XVIIIe siècle », dans Michel Vergé-Franceschi (dir.), Guerre et commerce en Méditerranée IXe-XXe siècles, Paris, Éditions Veyrier, 1991, p. 235-253."}),(0,dc.jsx)("p",{children:"BOULANGER, Patrick, Marseille, marché international de l'huile d'olive, Marseille, Institut historique de Provence, 1996."}),(0,dc.jsx)("p",{children:"BUTEL, Paul, « France, the Antilles, and Europe in the seventeenth and eighteenth centuries : renewals of foreign trade », dans James D. Tracy (dir.), The Rise of Merchant Empires. Long-Distance Trade in the Early Modern World, 1350-1750, New York, Cambridge University Press, 1990, p. 153-173."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, « Aller en caravane : le cabotage lointain en Méditerranée, XVIIe et XVIIIe siècle », Revue d’histoire moderne et contemporaine, n°52-1, 2005, p. 7-38."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, « Marseille, port négrier au XVIIIe siècle », Cahiers des Anneaux de la Mémoire, n°11, 2007, p. 163-178."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, « Expédier à la côte et aller à la cueillette : le cabotage en Méditerranée aux XVIIe et XVIIIe siècles », Revue d’Histoire maritime, n°8, 2008, p.67-108."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, « Commerce honteux pour négociants vertueux à Marseille au xviiie siècle ? », dans Éric Saunier (dir.), Cahiers de l’histoire et des mémoires de la traite négrière, de l’esclavage et de leurs abolitions, n° 1, 2008, p. 199-219."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert. Les chemins de la mer : Saint-Tropez : petit port méditerranéen (XVIIe-XVIIIe siècles), Rennes, PUR, 2010."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, « Marseille, la péninsule ibérique et les empires américains (1659-1793) : ‘Le soleil des profits se lève aussi à l’Ouest’ », Revue d’Histoire maritime, n° 13, 2011, p. 211-232."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, « Négociants d’expression allemande à Marseille (1750-1793) », Cahiers de la Méditerranée, n°84, 2012, p. 49-64."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, JANIN-THIVOS, Michèle, RAVEUX, Olivier (dir.). Langues et langages du commerce en Méditerranée et en Europe à l’époque moderne, Aix-en-Provence, Presses universitaires de Provence, 2013."}),(0,dc.jsx)("p",{children:"BUTI, Gilbert, « Une maison de négoce à Marseille au xviiie siècle : les Roux frères », Patrimoines du Sud (en ligne), n°13, 2021."}),(0,dc.jsx)("p",{children:"CALCAGNO, Paolo, « Uno dei ‘Tirreni’ di Braudel : scambi commerciali nell’area marittima ligure-provenzale tra XVII e XVIII secolo », Mediterranea-ricerche storiche, n°33, avril 2015, p. 79-106."}),(0,dc.jsx)("p",{children:"CARASSALE, Alessandro, LO BASSO, Luca, Sanremo, giardino di limoni. Produzione e commercio degli agrumi dell’estremo Ponente ligure (secoli XII-XIX), Rome, Carocci, 2008."}),(0,dc.jsx)("p",{children:"CARRIÈRE Charles, Négociants marseillais au XVIIIe siècle. Contribution à l'étude des économies maritimes, Marseille, Institut historique de Provence, 1973, 2 tomes."}),(0,dc.jsx)("p",{children:"CARRIÈRE, Charles, COURDURIÉ, Marcel « L’espace commercial marseillais aux XVIIe et XVIIIe siècles », dans Pierre Leon (dir.), Aires et structures du commerce français au XVIIIe siècle. Colloque national de l’AFHE, Paris, CNRS, 4-6 octobre 1973, Lyon, Centre d'histoire économique et sociale de la région lyonnaise, 1975, p. 75-106."}),(0,dc.jsx)("p",{children:"CARRIÈRE, Charles, Richesse du passé marseillais. Le port mondial au XVIIIe siècle, Marseille, C.C.I.M., 1979."}),(0,dc.jsx)("p",{children:"CARRIÈRE, Charles, COURDURIÉ, Marcel, « Un sophisme économique : Marseille s'enrichit en achetant plus qu'elle ne vend. (Réflexions sur les mécanismes commerciaux levantins au XVIIIème siècle) », Histoire, Économie et Société, vol. 3, 1er trimestre 1984, p. 7-51."}),(0,dc.jsx)("p",{children:"COLLETTA, Teresa (dir.), Città portuali del Mediterraneo. Luoghi dello scambio commerciale e colonie di mercanti stranieri tra Medioevo e età moderna, Milano, Franco Angeli, 2012."}),(0,dc.jsx)("p",{children:'CONAN, J. "La dernière compagnie française des Indes: La compagnie dans l’Inde (suite), Revue d’Histoire Économie et Sociale, 25 n°2, 1939. p. 159–85'}),(0,dc.jsx)("p",{children:'DAUDIN, Guillaume et PIGNEDE, Edouard, "Le commerce de la France au XVIIIe : inflation et révolution", Dialogue, n°62, 2021.'}),(0,dc.jsx)("p",{children:'DERMIGNY, Louis, Cargaisons Indiennes Soliers et Cie, 1781-1793, Série "Affaires et Gens d’Affaires XV", Paris, S.E.V.P.E.N, 1959-1960, 2 tomes'}),(0,dc.jsx)("p",{children:"DUMOND, Lionel, DURAND, Stéphane, THOMAS, Jérôme (dir), Les ports dans l’Europe méditerranéenne : Trafics et circulation, Images et représentations (XVIe-XXe siècle), Actes du colloque tenu à Montpellier les 19 et 20 mars 2004 en hommage à Louis Dermigny (1916-1974), Presses Universitaires de la Méditerranée, Montpellier, 2007."}),(0,dc.jsx)("p",{children:"ELDEM, Edhem, « French Trade and Commercial Policy in the Levant in the Eighteenth-Century », Oriente Moderno, Nuova serie, n°79, 1999, p. 27-47."}),(0,dc.jsx)("p",{children:"ELDEM, Edhem, « Capitulations and Western trade », dans Suraiya Faroqhi (dir.), The Cambridge History of Turkey: The Later Ottoman Empire, 1603-1839, Cambridge, Cambridge University Press, 2006, p. 283-335."}),(0,dc.jsx)("p",{children:"EMMANUELLI, François-Xavier, La Crise marseillaise de 1774 et la chute des courtiers. Contribution à l'histoire du commerce du Levant et de la banque, Marseille, Éditions du Centre national de la recherche scientifique, 1979."}),(0,dc.jsx)("p",{children:"FARGANEL, Jean-Pierre, « Les échelles du Levant dans la tourmente des conflits méditerranéens au XVIIIe siècle : la défense des intérêts français au fil du temps », Cahiers de la Méditerranée, n°70, 2005, p. 61-83."}),(0,dc.jsx)("p",{children:'FEDERICO, G., SCHULZE, M. S., & VOLCKART, O., "European goods market integration in the very long run: from the Black Death to the First World War", The Journal of Economic History, 81(1), 2021, p. 276-308.'}),(0,dc.jsx)("p",{children:"FIGEAC-MONTHUS, Marguerite, LASTÉCOUÈRES, Christophe (dir.), Territoires de l'illicite: ports et îles. De la fraude au contrôle (XVIe-XXe s.), Paris, Armand Colin, 2012."}),(0,dc.jsx)("p",{children:"FILIPPINI, Jean-Pierre, et alii (dir.), Dossier sur le commerce français dans la Méditerranée orientale au XVIIIe siècle, Paris, Presses Universitaires de France, 1976."}),(0,dc.jsx)("p",{children:"FÖLSCH, François Philippe, L'oeil de Stockholm : la correspondance du consul François Philippe Fölsch à Marseille (1780-1807), Pari, Classiques Garnier, 2021, ed. par BEAUREPAIRE, Pierre-Yves, MARZAGALLI, Silvia, THOMASSON, Thomasson."}),(0,dc.jsx)("p",{children:"FRANGAKIS-SYRETT, Elena, The Commerce of Smyrna in the Eighteenth Century (1700-1820), Athens, Center for Asia Minor Studies, 1992."}),(0,dc.jsx)("p",{children:"FUKASAWA, Katsumi, Toilerie et commerce du Levant, d’Alep à Marseille, Paris, Editions du CNRS, 1985."}),(0,dc.jsx)("p",{children:"GALANI, Katerina, British Shipping and Trade in the Mediterranean in the Age of War, 1770-1815, Phd thesis, University of Oxford, 2010."}),(0,dc.jsx)("p",{children:"GODECHOT, Jacques, « La France et les problèmes de l’Atlantique à la veille de la Révolution », Revue du Nord, n°142, 1954, p. 231-244."}),(0,dc.jsx)("p",{children:"HILDESHEIMER, Françoise, Le Bureau de la santé de Marseille sous l'Ancien régime. Le renfermement de la contagion, Marseille, Fédération historique de Provence, 1980."}),(0,dc.jsx)("p",{children:"HORN, Jeff, « Marseille et la Question du mercantilisme : privilège, liberté et économie politique en France, 1650-1750 », Histoire, économie & société, 30e année, 2012, p. 95-111."}),(0,dc.jsx)("p",{children:"JUILLIANY, Essai sur le Commerce de Marseille, 2e édition, 1842,"}),(0,dc.jsx)("p",{children:"LARGUIER, Gilbert (dir.), Les hommes et le littoral autour du golfe du Lion (XVIe-XVIIIe siècle), Presses Universitaires de Perpignan, Perpignan, 2012."}),(0,dc.jsx)("p",{children:"LE BOUËDEC, Gérard, « L’État et le cabotage en France et en Europe aux XVIIe-XVIIIe siècles » dans Le Bouëdec Gérard, Chappé François, Cérino Christophe (dir.), Pouvoirs et littoraux du XVe au XXe siècle, Rennes, PUR, 2000, p. 383-394."}),(0,dc.jsx)("p",{children:"LE GOUIC, Olivier. Lyon et la mer au XVIIIe siècle: Connexions atlantiques et commerce colonial, Rennes, Presses universitaires de Rennes, 2011."}),(0,dc.jsxs)("p",{children:["LEGAY, Marie-Laure, « Marseille » (2023) dans Legay Marie-Laure, Boullu Thomas (dir.), Dictionnaire Numérique de la Ferme générale, ",(0,dc.jsx)("a",{className:"c9",href:"https://fermege.meshs.fr",rel:"noopener noreferrer",target:"_blank",children:"https://fermege.meshs.fr"})]}),(0,dc.jsx)("p",{children:"LOPEZ, Olivier, S'établir et travailler chez l’autre. La Compagnie royale d’Afrique et ses hommes, Paris, Classiques Garnier, 2019."}),(0,dc.jsx)("p",{children:"LO BASSO, Luca, « Il Sud dei Genovesi. Traffici marittimi e pratiche mercantili tra l’Italia meridionale, Genova e Marsiglia nel Settecento », dans Biagio Salvemini (dir.), Lo spazio tirrenico nella « Grande Trasformazione ». Merci, uomini e istituzioni nel Settecento e nel primo Ottocento, Bari, Edipuglia, 2009, p. 239-263."}),(0,dc.jsxs)("p",{children:["MARZAGALLI, Silvia, PFISTER-LANGANAY, Christian, « L",(0,dc.jsx)("a",{className:"c9",href:"https://journals.openedition.org/cdlm/6284?lang%3Dfr",rel:"noopener noreferrer",target:"_blank",children:"a navigation des ports français en"})," Méditerranée au XVIIIe siècle : premiers aperçus à partir d’une source inexploitée », Cahiers de la Méditerranée, n°83, 2011, p. 273-295."]}),(0,dc.jsx)("p",{children:"MARZAGALLI, Silvia, « L’apport des cahiers du petit cabotage à la connaissance du commerce et de la navigation de Marseille à la fin du XVIIIe siècle »,  Cahiers de la Méditerranée, n° 108, juin 2024, p. 33-50. "}),(0,dc.jsx)("p",{children:"MEYER, Jean, « La France maritime au XVIIIe siècle. Aspects chronologiques », dans Jean Bérenger, Jean Meyer (dir.), La France dans le monde au XVIIIe siècle, Paris, Sedes, 1993, p. 269-288."}),(0,dc.jsx)("p",{children:"MIÈGE, Jean-Louis (dir.), Les céréales en Méditerranée, Histoire, Anthropologie, Économie, Paris, CNRS Éditions, 1994."}),(0,dc.jsx)("p",{children:"PANZAC, Daniel, La caravane maritime : marins européens et marchands ottomans en Méditerranée (1680-1830), Paris, CNRS Éditions, 2004"}),(0,dc.jsx)("p",{children:"PARIS, Robert, Histoire du commerce de Marseille. Tome V. De 1660 à 1789. Le Levant, Paris, Plon, 1957."}),(0,dc.jsx)("p",{children:"PAYN-ECHALIER, Patricia, « Entre Rhône et Méditerranée : la marine d’Arles au service d’un petit cabotage polyvalent (XVIe-XVIIIe siècles) », Rives méditerranéennes, n°13, 2003, p. 59-73."}),(0,dc.jsx)("p",{children:"PAYN-ECHALIER, Patricia, « Entre fleuve et mer, le port d’Arles et le delta du Rhône (XVIe-XVIIIe siècle) », Rives méditerranéennes, n°35, 2010, p. 29-44."}),(0,dc.jsx)("p",{children:"RAMBERT, Gaston, Histoire du commerce de Marseille, tomes IV, VI-VII, Paris, Plon, 1954-1966."}),(0,dc.jsx)("p",{children:"ROMANO, Ruggiero, Commerce et prix du blé à Marseille au XVIIIe siècle, Paris, A. Colin, 1956."}),(0,dc.jsx)("p",{children:"SALVEMINI, Biagio (dir.), Lo spazio tirrenico nella ‘grande trasformazione’. Merci, uomini e istituzioni nel Settecento e nel primo Ottocento, Atti del Convegno Internazionale di Bari, 17-18 novembre 2006, Bari, Edipuglia, 2009."}),(0,dc.jsx)("p",{children:'SOFIA, Pierre Niccolò, "C’est toute une question de jauge. Méthode, défis, incertitudes et résultats de l’estimation de la portée des navires du commerce marseillais au xviiie siècle", Cahiers de la Méditerranée, 106, 2024, p. 13-31.'}),(0,dc.jsx)("p",{children:"TAKEDA, Junko Thérése, Between crown and commerce Marseille and the early modern Mediterranean, Baltimore, Johns Hopkins University Press, 2011."}),(0,dc.jsx)("p",{children:"UNGER, Richard W. 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Si la résilience de l’estuaire de la Seine s’explique d’abord par l’importance et le dynamisme du bassin économique et démographique parisien, dans le cas de Marseille les causes sont plus complexes. Charles Carrière, auteur il y a cinquante ans d’une étude incontournable sur le négoce de Marseille au XVIIIe siècle (Carrière, 1973), associait la croissance économique et la force du port à son intégration progressive à l’économie de l’Atlantique. Après la guerre de Succession d’Espagne (1701-1713/14), les ports de la façade atlantique (Bordeaux, La Rochelle et Nantes notamment) connaissent une forte croissance liée au premier empire colonial français. Mais cette croissance est fragile car elle dépend principalement du commerce colonial et de la traite des esclaves. La perte de Saint-Domingue (devenue indépendante sous le nom d'Haïti en 1804) et l’interdiction de la traite Atlantique par le Parlement anglais en 1807 détruisent les bases du commerce colonial antillais. Les ports qui en tiraient leur dynamisme et en particulier le premier d’entre eux, Bordeaux, seront cantonnés au XIXe siècle à un rôle secondaire. À l’inverse, Marseille survit au choc des guerres révolutionnaires et napoléoniennes et à leurs conséquences. Cette résilience repose sur des caractéristiques qui lui sont spécifiques et qui s’inscrivent dans le temps long."}),(0,dc.jsxs)("p",{children:["Port marchand par tradition, Marseille est la première ville française à accueillir une chambre de commerce en 1599. Elle connaît une expansion commerciale régulière à partir de la seconde moitié du XVIIe siècle. Cette expansion se nourrit de l'intensification de ses échanges avec ses partenaires méditerranéens, notamment le Levant",(0,dc.jsx)("dfn",{"data-effect":"solid","data-for":"contents-tooltip","data-tip":"Le terme désigne alors l’Empire ottoman, en particulier sa partie orientale qui comprend la péninsule des Balkans, la Turquie actuelle, le Proche Orient, ainsi que l’Egypte et la Libye. Le Maghreb actuel qui est également sous le contrôle de l’Empire ottoman au XVIIIe siècle est souvent désigné par le terme de «Barbarie».",children:"?"}),". Le privilège obtenu par le port au début du règne personnel de Louis XIV va la renforcer. En effet, l’édit de mars 1669 supprime la plupart des taxes portant sur le commerce marseillais avec le Levant et établit simultanément un droit unique de 20% sur les marchandises du Levant apportées à Marseille par des étrangers. En 1685, le port phocéen obtient une franchise totale, alors que les marchandises levantines débarquées dans tous les autres ports français doivent payer un droit de 20%. Le privilège est ensuite confirmé en 1703 et se maintient jusqu’à la Révolution. Le port phocéen obtient ainsi le monopole de facto sur le commerce français avec le Levant. À partir de 1703, une barrière douanière sépare la ville du reste du royaume, consacrant la franchise du port de Marseille. Malgré le coup d’arrêt de la peste de 1720, il est le premier port français dans la première moitié du XVIIIe siècle. Le statut de port franc de Marseille a ensuite été étendu au commerce colonial par les lettres patentes de 1779 qui lui octroient la liberté du commerce avec les colonies françaises, sous condition d’accepter le régime d’entrepôt. Marseille bénéficie donc tout au long du XVIIIe siècle d’importants privilèges commerciaux qui soutiennent son expansion."]}),(0,dc.jsx)("p",{children:"La situation géographique de Marseille s’est avérée particulièrement avantageuse au XVIIIe siècle. Située à mi-chemin entre Cadix, la côte Atlantique et le Levant, la ville est un centre majeur de transit pour les textiles du Languedoc, ainsi que pour la cochenille et les piastres en provenance de l’Empire espagnol (via Cadix) vers l’Empire ottoman. Vers l’Ouest, le port est un centre de tout premier rang pour l’exportation des produits méditerranéens (huile d’olive, savon, etc.) vers les colonies atlantiques et vers l’Europe du Nord. De plus, Marseille a pu exploiter sa situation à l’embouchure du Rhône, qui en fait le point d’accès non seulement vers la Provence, mais aussi vers la région lyonnaise au Nord et le Languedoc à l’ouest. C’est ainsi que Marseille, importateur structurel de blé pour alimenter son hinterland, est devenu dès les années 1730 le hub céréalier de toute la Méditerranée, symétrique d’Amsterdam pour l’Europe du Nord-Ouest. De manière plus générale, le poids démographique de l’hinterland de Marseille n’a d’équivalent que celui de Rouen-Le Havre, ce dernier étant toutefois plus dynamique dans la seconde moitié du XVIIIe siècle. Outre ces avantages géographiques structurants, d’autres éléments ont pu contribuer à solidifier la place de Marseille dans le temps:"}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"Le statut de port franc et la domination commerciale de Marseille sur l’espace méditerranéen ont favorisé la constitution de communautés marchandes (Arméniens, Suisses, Italiens, etc.) ou la présence des commissionnaires étrangers. "}),(0,dc.jsx)("li",{children:"La plus grande diversité des acteurs (mesurée dans cette étude à partir des pavillons des navires) a pu compenser en partie au moins une conjoncture défavorable."}),(0,dc.jsx)("li",{children:"De même, une plus grande diversité des marchés nationaux et internationaux qui va de pair avec une gamme plus large de productions a pu contribuer à la résilience marseillaise. Ainsi, la non-participation au commerce de la traite a paradoxalement contribué à protéger l’économie marseillaise des effets de sa disparition en 1793. "}),(0,dc.jsx)("li",{children:"Une plus grande résilience aux guerres liée au plus faible contrôle de la Méditerranée par les Anglais et la présence de transporteurs neutres italiens, si elle était avérée, pourrait également être un facteur de continuité de l’activité marchande sur la longue période (voir partie III de cette étude)."}),(0,dc.jsx)("li",{children:"Enfin, la co-présence/superposition des trafics et des logiques différentes (spatiales et temporelles) ont pu donner une plus grande souplesse à l’ensemble."})]})]})}const wN=function(e={}){const{wrapper:t}=e.components||{};return t?(0,dc.jsx)(t,Object.assign({},e,{children:(0,dc.jsx)(xN,e)})):xN()};function _N(e){return(0,dc.jsxs)("div",{id:"part-0",children:[(0,dc.jsx)("p",{children:'Deux ports français qui survivent au XIXe : Marseille et l’ensemble Rouen-Le Havre. La dynamisme de l’estuaire de la Seine s’explique facilement par l’industrialisation et la proximité de Paris. Quelle est l’explication de la force de Marseille ? Vient-elle, comme l’affirme Carrière, de la force de la croissance du XVIIIe tirée par l’intégration à l’économie Atlantique ? (Réponse : non. "Marseille, port traditionnel et méditerranéen).'}),(0,dc.jsx)("h2",{id:"h.o25rt55n14tq",children:"A. Marseille en 1789, un port international"}),(0,dc.jsx)("p",{children:"Marseille en 1789: Les échanges de Marseille en 1789 restent principalement tournés vers l’espace méditerranéen - ses deux partenaires privilégiés étant l’Italie et le Levant (l’empire Ottoman). Toutefois, à la veille de la Révolution, Marseille a développé des liens économiques et commerciaux avec des espaces lointains, les colonies antillaises et, dans une moindre mesure, le Nord de l’Europe, l’océan indien et les Etats-Unis. Le port de Marseille est un port international que les avantages en termes de localisation, ont permis à son personnel négociant et à ses capitalistes de développer leurs activités à l’interconnexion de son espace commercial traditionnel - la Méditerranée - et de la zone la plus dynamique - l’espace Atlantique."}),(0,dc.jsx)("p",{children:"Titre : (carte de Paul&co) Carte de la valeur des importations et des exportations de Marseille en 1789. Légende: La taille du cercle est proportionnelle à la valeur, la couleur indique si la balance commerciale est favorable (vert) ou défavorable (rouge) à Marseille."}),(0,dc.jsx)("p",{children:"Les données relatives aux arrivées de navires confirment pour l’essentiel les données de la balance du commerce: elles montrent la part toujours dominante du trafic méditerranéen issu d’Italie, du Levant et d’Espagne pour Marseille. "}),(0,dc.jsx)("p",{children:"Données Navigo, code : moduleA_navigo_1789 "}),(0,dc.jsx)("p",{children:"Titre : Arrivées de navires à Marseille en 1789 (santé + cabotages, en excluant les doublons Q) "}),(0,dc.jsx)("h2",{id:"h.qb9ge46p8sqw",children:"B. Marseille premier (ou presque) port de France"}),(0,dc.jsx)("p",{children:"En 1789, Marseille est le deuxième port français en termes de valeur de commerce derrière Bordeaux. Il lui est même légèrement supérieur en ce qui concerne les importations, mais Bordeaux le dépasse largement en ce qui concerne les exportations. "}),(0,dc.jsx)("p",{children:"Toutefois, la supériorité de Bordeaux est fragile puisqu’elle dépend largement de sa spécialisation dans le commerce colonial et la traite des esclaves; ce qui apparaît lorsqu’on considère la balance à l’exclusion de ces deux commerces (voir graphiques ci-dessous). De ce fait, la fermeture de ces deux commerces à partir de de 1793 sera une véritable catastrophe pour Bordeaux, alors que Marseille fait partie des rares ports français à survivre au choc révolutionnaire. "}),(0,dc.jsx)("p",{children:"En nombre de congés, c’est-à-dire des autorisations obligatoires de sortie de tout port français (parfois valables pour une année quelque soit le nombre d’allers-retours), Marseille vient largement en tête en 1789. "}),(0,dc.jsx)("p",{children:"Le nombre des congés étant un indicateur très approximatif car il additionne des navires de portée très différente, il serait souhaitable de comparer les tonnages. Or, ceux-ci sont connus en 1787 dans la plupart des ports français grâce aux congés. Nous ne disposons en revanche pas de l’indication des tonnages sortis de Marseille. Nous avons donc procédé à une estimation des tonnages entrés à partir du type de navire signalés par les registres des dépositions des capitaines et des cahiers du petit cabotage en 1787, afin de pouvoir la comparer avec les tonnages agrégés des autres ports français. Comme le nombre d’entrées à Marseille est supérieur de 17.6% au nombre des congés, une fois ôtés les navires en relâche, nous avons déflaté le tonnage estimé de ce même facteur, puis refait le calcul en supposant que les navires dépourvus de congés soient ceux qui effectuent du cabotage de port en port au sein de la Provence [voir Chardon]. La comparaison entre les tonnages estimés supposés entrés à Marseille montre encore une fois la primauté de la navigation de ce port."}),(0,dc.jsx)("p",{children:"Si on se penche sur la valeur du commerce, Marseille vient en tête. "}),(0,dc.jsx)("p",{children:"Marseille est donc un des deux ports les plus importants en 1789. Sa participation dans le système colonial est moins forte que celle de Bordeaux : il est le premier port européen (et levantin) français."}),(0,dc.jsx)("h2",{id:"h.9aefnfi0kgry",children:"C. La croissance marseillaise (À déplacer I.A )"}),(0,dc.jsx)("p",{children:"Objectif : Montrer l'évolution au XVIIIe siècle, voir quels sont les points de flexion par rapport aux autres grands ports. "}),(0,dc.jsx)("p",{children:"Carrière affirme que cette importance de Marseille en 1789 vient d’une croissance soutenue durant le siècle. Nous montrons ici que cette croissance n’est pas exceptionnelle : Marseille est important en 1789 parcequ’il était déjà important en 1740."}),(0,dc.jsx)("p",{children:"La situation de Marseille à l’aube de la révolution française s’inscrit dans une tendance de long-terme. Ville marchande par tradition, elle est la première à accueillir une chambre de commerce, dès 1599, elle connaît une expansion commerciale régulière à partir de la fin du XVIIe siècle. Elle se nourrit, dans un premier temps, de l'approfondissement de ses échanges avec la Méditerranée, notamment le Levant pour lequel elle obtient un privilège en 1700. Marseille devient, malgré le coup d’arrêt de la peste de 1720, le premier port français dans la première moitié du XVIIIe siècle. Les exportations de textile à destination du Levant connaissant une certaine stagnation à partir des années 1750, puis une baisse sensible dans les années 1770, la place relative de Marseille recule au profit de Bordeaux. Toutefois, le trafic de Marseille continue de progresser, tiré par les exportations coloniales. On remarque que la baisse relative de Marseille est plus marquée pour les exportations que pour les importations - Marseille approvisionnant un hinterland important (la Provence, la Vallée du Rhône et le sud-est)."}),(0,dc.jsx)("p",{children:"Titre: Comparaison du commerce total par direction de ferme pour les années dispos dans TOFLIT18."}),(0,dc.jsx)("p",{children:"Titre: Comparaison du montant des importations par direction de ferme "}),(0,dc.jsx)("p",{children:"comparaison des exports"}),(0,dc.jsx)("p",{children:"L’analyse de la tendance de la croissance des principales régions française vient renforcer l’idée que Marseille était un port important au début de la période et que sa position s’est légèrement dégradée au cours du siècle au bénéfice de Bordeaux."}),(0,dc.jsx)("p",{children:"Nous ne disposons pas de l’indication des tonnages sortis de Marseille. Nous avons donc procédé à une estimation des tonnages entrés à partir du type de navire signalés par les registres des dépositions des capitaines et des cahiers du petit cabotage en 1787, afin de pouvoir la comparer avec les tonnages agrégés des autres ports français. Comme le nombre d’entrées à Marseille est supérieur de 17.6% au nombre des congés, une fois ôtés les navires en relâche, nous avons déflaté le tonnage estimé de ce même facteur, puis refait le calcul en supposant que les navires dépourvus de congés soient ceux qui effectuent du cabotage de port en port au sein de la Provence [voir enquête Chardon]. La comparaison entre les tonnages estimés supposés entrés à Marseille montre encore une fois la primauté de la navigation de ce port."}),(0,dc.jsx)("p",{children:"Les données de la navigation reposent sur deux sources de nature différente: pour ce qui est de sorties, nous disposons du nombre des congés délivrés. Pour les entrées, il s’agit des dépositions des capitaines au bureau de la Santé qui ne comprennent pas toutes les entrées. La navigation dite du petit cabotage - celle provenant d’une aire comprise entre la Catalogne et la Toscane, Corse incluse, ne transportant pas de passagers ou d’autres produits spécifiques, et n’ayant pas fait de rencontres en mer avec des corsaires - est en effet enregistrée à part. En dépit de ces différences, la corrélation de deux courbes est la même (taux de corrélation = 0.89) entre 1732 et 1780."}),(0,dc.jsx)("p",{children:"Le nombre des congés délivrés à Marseille montre une nette croissance dans les années 1740 (et ce, en dépit de la guerre de succession d’Autriche) et une reprise au lendemain de la guerre de Sept Ans sur des niveaux nettement plus élevés qu’avant ce conflit. La crise financière liée aux faillites en chaîne des courtiers en 1774, très visible, est de courte durée. "}),(0,dc.jsx)("p",{children:"Le port accroît son commerce au XVIIIe siècle en élargissant sa géographie commerciale vers l’Atlantique et l’océan Indien, tout en gardant une position de force dans les marchés méditerranéens et notamment levantins. "}),(0,dc.jsx)("p",{children:"Ce succès marseillais a été traditionnellement attribué soit à une série de privilèges octroyés au port depuis le règne de Louis XIV, soit au dynamisme de son négoce. Marseille a en effet obtenu le statut de port franc (expliquer). "}),(0,dc.jsx)("p",{children:"Nous explorons ici les hypothèses suivantes : "}),(0,dc.jsxs)("ul",{children:[(0,dc.jsx)("li",{children:"des avantages institutionnels (monopole sur le Levant) qui se combinent avec des avantages géographiques (présence des textiles du Languedoc, liens avec Cadix- cochenille, argent) ? "}),(0,dc.jsx)("li",{children:"des avantages économiques liés à son hinterland: importateur structurel de blé, Lyon/Rhone (marché bancaire/monétaire pour l’argent espagnol/capitaux marseillais-Cadix, soieries et dentelles du Puy, textiles du Languedoc, industrie pharmaceutique, produits méditerranéens) "}),(0,dc.jsx)("li",{children:"une plus grande diversité des marchés nationaux et internationaux qui va de pair avec une gamme plus large de productions ?"}),(0,dc.jsx)("li",{children:"une plus grande participation d’acteurs (pavillons) différents occupant des secteurs du marché différenciés en compensant ainsi des conjonctures défavorables (crises productives, guerre)."}),(0,dc.jsx)("li",{children:"une plus grande résilience aux guerres liée au manque de contrôle de la Méditerranée par les anglais et la présence de neutres italiens ? définir résilience"}),(0,dc.jsx)("li",{children:"une co-présence/superposition des trafics et des logiques différentes (spatiales et temporelles) qui donnent in fine une plus grande souplesse à l’ensemble"})]}),(0,dc.jsx)("p",{children:"Conclusion de l’introduction."})]})}const MN=function(e={}){const{wrapper:t}=e.components||{};return t?(0,dc.jsx)(t,Object.assign({},e,{children:(0,dc.jsx)(_N,e)})):_N()},VN=JSON.parse('{"fr":{"title":"Prospérité et résilience du port de Marseille au XVIIIe siècle"},"en":{"title":"Case study Marseille - document de rédaction en anglais"}}');var kN=i(7902),jN={};jN.styleTagTransform=_v(),jN.setAttributes=yv(),jN.insert=gv().bind(null,"head"),jN.domAPI=Cv(),jN.insertStyleElement=xv(),fv()(kN.A,jN),kN.A&&kN.A.locals&&kN.A.locals;const HN=({width:e,height:t,hourOfTime:n,hourDuration:r})=>{const i=.7*e,a=.05*e,o=ln().domain([0,12]).range(["darkgrey","black"])(Math.abs(12-n)),{fill:s}=Im({to:{fill:o},config:{duration:r}});return(0,dc.jsx)(ig.path,{className:"hull",style:{fill:s},d:`M 0 0 L ${e/3} 0 L ${e/3} ${t/4} L ${.6*e} ${t/4} L ${.6*e} 0 L ${e} 0 L ${i} ${t} L ${a} ${t} 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