section3_xarray.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 1828, lon: 180, lat: 90, nv: 2)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon        (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 352.0 354.0 356.0 358.0\n",
       "  * lat        (lat) float64 -89.0 -87.0 -85.0 -83.0 ... 83.0 85.0 87.0 89.0\n",
       "Dimensions without coordinates: nv\n",
       "Data variables:\n",
       "    time_bnds  (time, nv) float32 ...\n",
       "    sst        (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    CDI:                        Climate Data Interface version 2.0.5 (https:/...\n",
       "    Conventions:                CF-1.0\n",
       "    source:                     HadISST\n",
       "    institution:                Met Office Hadley Centre\n",
       "    Title:                      Monthly version of HadISST sea surface temper...\n",
       "    description:                HadISST 1.1 monthly average sea surface tempe...\n",
       "    reference:                  Rayner, N. A., Parker, D. E., Horton, E. B., ...\n",
       "    history:                    Fri Jul 08 11:42:23 2022: cdo remapbil,r180x9...\n",
       "    supplementary_information:  Updates and supplementary information will be...\n",
       "    comment:                    Data restrictions: for academic research use ...\n",
       "    CDO:                        Climate Data Operators version 2.0.5 (https:/...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-0b0bee71-bc64-47bb-9978-3964db3240e1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0b0bee71-bc64-47bb-9978-3964db3240e1' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1828</li><li><span class='xr-has-index'>lon</span>: 180</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span>nv</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4de8a48c-876a-4177-a4ee-1a2b030e0f98' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4de8a48c-876a-4177-a4ee-1a2b030e0f98' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1870-01-16T12:00:00 ... 2022-04-...</div><input id='attrs-c67acbee-bcf6-45fe-8125-d89d300af497' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c67acbee-bcf6-45fe-8125-d89d300af497' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8e43847-e5e6-4b32-bae4-36c510c07cae' class='xr-var-data-in' type='checkbox'><label for='data-b8e43847-e5e6-4b32-bae4-36c510c07cae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1870-01-16T12:00:00.000000000&#x27;, &#x27;1870-02-14T23:59:59.011230469&#x27;,\n",
       "       &#x27;1870-03-16T11:59:58.681640625&#x27;, ..., &#x27;2022-02-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2022-03-16T12:00:00.000000000&#x27;, &#x27;2022-04-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-820c7b3c-e8e7-4deb-a583-e3b6815ccfaa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-820c7b3c-e8e7-4deb-a583-e3b6815ccfaa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3d32b27-2eaa-4b2e-9931-675c482868b4' class='xr-var-data-in' type='checkbox'><label for='data-b3d32b27-2eaa-4b2e-9931-675c482868b4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-5d5b6535-9ae7-4788-9ae6-2829eae43c36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d5b6535-9ae7-4788-9ae6-2829eae43c36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5dc813ff-8500-41e3-abf8-bfca63377161' class='xr-var-data-in' type='checkbox'><label for='data-5dc813ff-8500-41e3-abf8-bfca63377161' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dd0408fe-310a-4b22-ab2a-b3b4861dc4e1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dd0408fe-310a-4b22-ab2a-b3b4861dc4e1' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nv)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5e70ed95-7a80-4b2e-ad72-b41ad38cfb21' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5e70ed95-7a80-4b2e-ad72-b41ad38cfb21' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79ab3bf6-c6f0-485d-b7a6-b287691ea8ba' class='xr-var-data-in' type='checkbox'><label for='data-79ab3bf6-c6f0-485d-b7a6-b287691ea8ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[3656 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d688bfc2-7795-4da9-a1bb-08faa97be88f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d688bfc2-7795-4da9-a1bb-08faa97be88f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94c82fe1-c618-43bc-b572-baf59564f405' class='xr-var-data-in' type='checkbox'><label for='data-94c82fe1-c618-43bc-b572-baf59564f405' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div><div class='xr-var-data'><pre>[29613600 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2b646618-d109-45b1-b6e6-829b7c53a1c0' class='xr-section-summary-in' type='checkbox'  ><label for='section-2b646618-d109-45b1-b6e6-829b7c53a1c0' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f3ca0191-aa2d-42dd-ae49-d1ee2d771adb' class='xr-index-data-in' type='checkbox'/><label for='index-f3ca0191-aa2d-42dd-ae49-d1ee2d771adb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([          &#x27;1870-01-16 12:00:00&#x27;,\n",
       "               &#x27;1870-02-14 23:59:59.011230469&#x27;,\n",
       "               &#x27;1870-03-16 11:59:58.681640625&#x27;,\n",
       "               &#x27;1870-04-15 23:59:58.681640624&#x27;,\n",
       "                         &#x27;1870-05-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-06-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-07-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-08-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-09-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-10-16 12:00:00&#x27;,\n",
       "               ...\n",
       "                         &#x27;2021-07-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-08-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-09-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-10-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-11-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-12-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-01-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-02-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-03-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-04-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1828, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a4585404-a5e4-4183-b195-0999a9c43d7e' class='xr-index-data-in' type='checkbox'/><label for='index-a4585404-a5e4-4183-b195-0999a9c43d7e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1633c76f-fe82-483e-9c56-a7b1469ac74c' class='xr-index-data-in' type='checkbox'/><label for='index-1633c76f-fe82-483e-9c56-a7b1469ac74c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e24e49e8-b490-4e1c-b27c-c389c475ade5' class='xr-section-summary-in' type='checkbox'  ><label for='section-e24e49e8-b490-4e1c-b27c-c389c475ade5' class='xr-section-summary' >Attributes: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.0</dd><dt><span>source :</span></dt><dd>HadISST</dd><dt><span>institution :</span></dt><dd>Met Office Hadley Centre</dd><dt><span>Title :</span></dt><dd>Monthly version of HadISST sea surface temperature component</dd><dt><span>description :</span></dt><dd>HadISST 1.1 monthly average sea surface temperature</dd><dt><span>reference :</span></dt><dd>Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V., Rowell, D. P., Kent, E. C., Kaplan, A.  Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century J. Geophys. Res.Vol. 108, No. D14, 4407 10.1029/2002JD002670</dd><dt><span>history :</span></dt><dd>Fri Jul 08 11:42:23 2022: cdo remapbil,r180x90 HadISST_sst.nc HadISST_sst_2x2.nc\n",
       "2/6/2022 converted to netcdf from pp format</dd><dt><span>supplementary_information :</span></dt><dd>Updates and supplementary information will be available from http://www.metoffice.gov.uk/hadobs/hadisst</dd><dt><span>comment :</span></dt><dd>Data restrictions: for academic research use only. Data are Crown copyright see (http://www.opsi.gov.uk/advice/crown-copyright/copyright-guidance/index.htm)</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 1828, lon: 180, lat: 90, nv: 2)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon        (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 352.0 354.0 356.0 358.0\n",
       "  * lat        (lat) float64 -89.0 -87.0 -85.0 -83.0 ... 83.0 85.0 87.0 89.0\n",
       "Dimensions without coordinates: nv\n",
       "Data variables:\n",
       "    time_bnds  (time, nv) float32 ...\n",
       "    sst        (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    CDI:                        Climate Data Interface version 2.0.5 (https:/...\n",
       "    Conventions:                CF-1.0\n",
       "    source:                     HadISST\n",
       "    institution:                Met Office Hadley Centre\n",
       "    Title:                      Monthly version of HadISST sea surface temper...\n",
       "    description:                HadISST 1.1 monthly average sea surface tempe...\n",
       "    reference:                  Rayner, N. A., Parker, D. E., Horton, E. B., ...\n",
       "    history:                    Fri Jul 08 11:42:23 2022: cdo remapbil,r180x9...\n",
       "    supplementary_information:  Updates and supplementary information will be...\n",
       "    comment:                    Data restrictions: for academic research use ...\n",
       "    CDO:                        Climate Data Operators version 2.0.5 (https:/..."
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst0 = xr.open_dataset(\"../DATA/HadISST_sst_2x2.nc\")\n",
    "sst0 # data_variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 1828, lat: 90, lon: 180)&gt;\n",
       "[29613600 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1828</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-93799f6e-fad9-4e28-bc7e-9f277be9db19' class='xr-array-in' type='checkbox' checked><label for='section-93799f6e-fad9-4e28-bc7e-9f277be9db19' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[29613600 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-b0796404-0763-4fe6-b7c6-556335e62c9f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b0796404-0763-4fe6-b7c6-556335e62c9f' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1870-01-16T12:00:00 ... 2022-04-...</div><input id='attrs-a8c82968-d203-464f-89d2-29f41e7006fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a8c82968-d203-464f-89d2-29f41e7006fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd8cda61-b592-467d-8b35-da4ca0dfdda4' class='xr-var-data-in' type='checkbox'><label for='data-cd8cda61-b592-467d-8b35-da4ca0dfdda4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1870-01-16T12:00:00.000000000&#x27;, &#x27;1870-02-14T23:59:59.011230469&#x27;,\n",
       "       &#x27;1870-03-16T11:59:58.681640625&#x27;, ..., &#x27;2022-02-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2022-03-16T12:00:00.000000000&#x27;, &#x27;2022-04-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-4eb41910-7b96-4eac-a7f9-afffcdfec913' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4eb41910-7b96-4eac-a7f9-afffcdfec913' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d6c397a-bc93-4adb-89a7-68498d744c48' class='xr-var-data-in' type='checkbox'><label for='data-4d6c397a-bc93-4adb-89a7-68498d744c48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-bcfb9a0c-393f-450d-ad8d-c909df3af1f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bcfb9a0c-393f-450d-ad8d-c909df3af1f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-885f87c4-d26b-41ec-9505-2b9895de7064' class='xr-var-data-in' type='checkbox'><label for='data-885f87c4-d26b-41ec-9505-2b9895de7064' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7c666af7-9d4a-44b1-8d89-3324141d9957' class='xr-section-summary-in' type='checkbox'  ><label for='section-7c666af7-9d4a-44b1-8d89-3324141d9957' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7a8e7225-0cf7-4afa-baef-00ed858f16cf' class='xr-index-data-in' type='checkbox'/><label for='index-7a8e7225-0cf7-4afa-baef-00ed858f16cf' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([          &#x27;1870-01-16 12:00:00&#x27;,\n",
       "               &#x27;1870-02-14 23:59:59.011230469&#x27;,\n",
       "               &#x27;1870-03-16 11:59:58.681640625&#x27;,\n",
       "               &#x27;1870-04-15 23:59:58.681640624&#x27;,\n",
       "                         &#x27;1870-05-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-06-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-07-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-08-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-09-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-10-16 12:00:00&#x27;,\n",
       "               ...\n",
       "                         &#x27;2021-07-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-08-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-09-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-10-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-11-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-12-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-01-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-02-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-03-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-04-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1828, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-12e643b2-71f5-4ca6-8818-249a21ac13c2' class='xr-index-data-in' type='checkbox'/><label for='index-12e643b2-71f5-4ca6-8818-249a21ac13c2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6155f653-6b71-4f03-8f7e-dc046b678d1c' class='xr-index-data-in' type='checkbox'/><label for='index-6155f653-6b71-4f03-8f7e-dc046b678d1c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a2b94647-9bef-4bb6-aa46-898f7761d2c9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a2b94647-9bef-4bb6-aa46-898f7761d2c9' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 1828, lat: 90, lon: 180)>\n",
       "[29613600 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst =sst0['sst']\n",
    "sst"
   ]
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;time&#x27; (time: 1828)&gt;\n",
       "array([&#x27;1870-01-16T12:00:00.000000000&#x27;, &#x27;1870-02-14T23:59:59.011230469&#x27;,\n",
       "       &#x27;1870-03-16T11:59:58.681640625&#x27;, ..., &#x27;2022-02-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2022-03-16T12:00:00.000000000&#x27;, &#x27;2022-04-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "Attributes:\n",
       "    standard_name:  time\n",
       "    long_name:      Time\n",
       "    axis:           T</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'time'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1828</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-c68d5c29-4011-4443-8960-c87847c6b762' class='xr-array-in' type='checkbox' checked><label for='section-c68d5c29-4011-4443-8960-c87847c6b762' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1870-01-16T12:00:00 ... 2022-04-16T12:00:00</span></div><div class='xr-array-data'><pre>array([&#x27;1870-01-16T12:00:00.000000000&#x27;, &#x27;1870-02-14T23:59:59.011230469&#x27;,\n",
       "       &#x27;1870-03-16T11:59:58.681640625&#x27;, ..., &#x27;2022-02-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2022-03-16T12:00:00.000000000&#x27;, &#x27;2022-04-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></div></li><li class='xr-section-item'><input id='section-0822061f-9f45-42e7-a1ae-a70e726a42b6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0822061f-9f45-42e7-a1ae-a70e726a42b6' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1870-01-16T12:00:00 ... 2022-04-...</div><input id='attrs-e7996937-8a37-4a32-9cdd-d7adf8a0884b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7996937-8a37-4a32-9cdd-d7adf8a0884b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65cdc39c-82b3-4ca9-bca8-352f6e9a08b2' class='xr-var-data-in' type='checkbox'><label for='data-65cdc39c-82b3-4ca9-bca8-352f6e9a08b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1870-01-16T12:00:00.000000000&#x27;, &#x27;1870-02-14T23:59:59.011230469&#x27;,\n",
       "       &#x27;1870-03-16T11:59:58.681640625&#x27;, ..., &#x27;2022-02-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2022-03-16T12:00:00.000000000&#x27;, &#x27;2022-04-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7b7ddf0a-8ff7-4f2e-af33-21726dfd79de' class='xr-section-summary-in' type='checkbox'  ><label for='section-7b7ddf0a-8ff7-4f2e-af33-21726dfd79de' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1a81ed3b-615d-40d7-a011-fe71dd2ecdbc' class='xr-index-data-in' type='checkbox'/><label for='index-1a81ed3b-615d-40d7-a011-fe71dd2ecdbc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([          &#x27;1870-01-16 12:00:00&#x27;,\n",
       "               &#x27;1870-02-14 23:59:59.011230469&#x27;,\n",
       "               &#x27;1870-03-16 11:59:58.681640625&#x27;,\n",
       "               &#x27;1870-04-15 23:59:58.681640624&#x27;,\n",
       "                         &#x27;1870-05-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-06-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-07-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-08-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-09-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-10-16 12:00:00&#x27;,\n",
       "               ...\n",
       "                         &#x27;2021-07-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-08-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-09-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-10-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-11-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-12-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-01-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-02-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-03-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-04-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1828, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a00bde39-55e9-4dc1-a64a-84ffe819e443' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a00bde39-55e9-4dc1-a64a-84ffe819e443' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.DataArray 'time' (time: 1828)>\n",
       "array(['1870-01-16T12:00:00.000000000', '1870-02-14T23:59:59.011230469',\n",
       "       '1870-03-16T11:59:58.681640625', ..., '2022-02-16T12:00:00.000000000',\n",
       "       '2022-03-16T12:00:00.000000000', '2022-04-16T12:00:00.000000000'],\n",
       "      dtype='datetime64[ns]')\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "Attributes:\n",
       "    standard_name:  time\n",
       "    long_name:      Time\n",
       "    axis:           T"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst.time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (lon: 180)&gt;\n",
       "[180 values with dtype=float32]\n",
       "Coordinates:\n",
       "    time     datetime64[ns] 1870-01-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -29.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-66310d7c-2450-4734-8f4f-adc1ac8de41f' class='xr-array-in' type='checkbox' checked><label for='section-66310d7c-2450-4734-8f4f-adc1ac8de41f' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[180 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-a19afc5c-ca57-4b21-9414-445339b144ca' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a19afc5c-ca57-4b21-9414-445339b144ca' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1870-01-16T12:00:00</div><input id='attrs-de3a61cf-6546-47a0-b0d6-927ee0914f97' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-de3a61cf-6546-47a0-b0d6-927ee0914f97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e472ce59-3558-4f58-86d9-610cce87b11e' class='xr-var-data-in' type='checkbox'><label for='data-e472ce59-3558-4f58-86d9-610cce87b11e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;1870-01-16T12:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-e04eff8b-51fb-4408-aafe-36660de632d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e04eff8b-51fb-4408-aafe-36660de632d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5063101-21ca-4b72-a62a-0dca187f179b' class='xr-var-data-in' type='checkbox'><label for='data-f5063101-21ca-4b72-a62a-0dca187f179b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-29.0</div><input id='attrs-c897735a-8501-4faa-966e-5761d6b178a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c897735a-8501-4faa-966e-5761d6b178a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b87d605-6720-45e3-bb37-39b6e57acba2' class='xr-var-data-in' type='checkbox'><label for='data-3b87d605-6720-45e3-bb37-39b6e57acba2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array(-29.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-90d0c411-0f49-4c04-b526-1df1148d21d3' class='xr-section-summary-in' type='checkbox'  ><label for='section-90d0c411-0f49-4c04-b526-1df1148d21d3' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-77f55b23-011d-49f5-af27-ecd373916cce' class='xr-index-data-in' type='checkbox'/><label for='index-77f55b23-011d-49f5-af27-ecd373916cce' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-836a6927-8628-4d4f-aada-ed632c0840d8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-836a6927-8628-4d4f-aada-ed632c0840d8' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (lon: 180)>\n",
       "[180 values with dtype=float32]\n",
       "Coordinates:\n",
       "    time     datetime64[ns] 1870-01-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "    lat      float64 -29.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst[0,30] #.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 1, lat: 90, lon: 180)&gt;\n",
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       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-b3e07df8-e4e2-4777-ad54-ebad5032da57' class='xr-array-in' type='checkbox' checked><label for='section-b3e07df8-e4e2-4777-ad54-ebad5032da57' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[16200 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-511dd493-2b0f-4a20-b1aa-a530967d6430' class='xr-section-summary-in' type='checkbox'  checked><label for='section-511dd493-2b0f-4a20-b1aa-a530967d6430' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1990-01-16T12:00:00</div><input id='attrs-cacead3a-b362-40e0-a263-f2020048abc4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cacead3a-b362-40e0-a263-f2020048abc4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2e2819c-57ad-4b56-8e36-0f7cda8168c1' class='xr-var-data-in' type='checkbox'><label for='data-f2e2819c-57ad-4b56-8e36-0f7cda8168c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1990-01-16T12:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-557805a1-d49f-4c10-a8f2-606423cbf14e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-557805a1-d49f-4c10-a8f2-606423cbf14e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79c51df5-cd0e-4824-8599-7a666a2e9def' class='xr-var-data-in' type='checkbox'><label for='data-79c51df5-cd0e-4824-8599-7a666a2e9def' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-e1ff8365-b4ed-4894-a107-6e49c0cfc3f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e1ff8365-b4ed-4894-a107-6e49c0cfc3f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb3ae28f-21a0-412e-abce-9ef3d6aee2a7' class='xr-var-data-in' type='checkbox'><label for='data-cb3ae28f-21a0-412e-abce-9ef3d6aee2a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-63b6d808-a650-490d-b738-06be71b6933a' class='xr-section-summary-in' type='checkbox'  ><label for='section-63b6d808-a650-490d-b738-06be71b6933a' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d6d904e5-eee7-439e-90ed-c5a091fae718' class='xr-index-data-in' type='checkbox'/><label for='index-d6d904e5-eee7-439e-90ed-c5a091fae718' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1990-01-16 12:00:00&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-58283263-13fd-41a5-bcba-d611fe0a8971' class='xr-index-data-in' type='checkbox'/><label for='index-58283263-13fd-41a5-bcba-d611fe0a8971' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7e7835fa-8702-4193-964d-254f4b0a874f' class='xr-index-data-in' type='checkbox'/><label for='index-7e7835fa-8702-4193-964d-254f4b0a874f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-11ff4374-051a-4cba-ad71-7629e8407506' class='xr-section-summary-in' type='checkbox'  checked><label for='section-11ff4374-051a-4cba-ad71-7629e8407506' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 1, lat: 90, lon: 180)>\n",
       "[16200 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1990-01-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst.loc[\"1990-01\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 372, lat: 90, lon: 180)&gt;\n",
       "[6026400 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1990-01-16T12:00:00 ... 2020-12-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 372</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-80c6edd2-51b9-4c3e-83ec-3fc24f348274' class='xr-array-in' type='checkbox' checked><label for='section-80c6edd2-51b9-4c3e-83ec-3fc24f348274' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[6026400 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-1d14f7eb-7b33-4022-b861-dc053bab7b28' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1d14f7eb-7b33-4022-b861-dc053bab7b28' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1990-01-16T12:00:00 ... 2020-12-...</div><input id='attrs-0b4cfde8-fd27-4835-aa19-a177dc8fb432' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b4cfde8-fd27-4835-aa19-a177dc8fb432' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b279e96f-e660-4865-a2f2-4e7abc0e6f8a' class='xr-var-data-in' type='checkbox'><label for='data-b279e96f-e660-4865-a2f2-4e7abc0e6f8a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1990-01-16T12:00:00.000000000&#x27;, &#x27;1990-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-03-16T12:00:00.000000000&#x27;, ..., &#x27;2020-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2020-11-16T12:00:00.000000000&#x27;, &#x27;2020-12-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-edd5963b-9da5-48df-8da1-14dec949158c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-edd5963b-9da5-48df-8da1-14dec949158c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e39abf1-ff8f-4045-919f-0500fed86701' class='xr-var-data-in' type='checkbox'><label for='data-9e39abf1-ff8f-4045-919f-0500fed86701' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-0c36f07f-d817-4039-9d7d-90011e72be13' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c36f07f-d817-4039-9d7d-90011e72be13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-002cc507-d517-496d-9a41-59e017f6a2d0' class='xr-var-data-in' type='checkbox'><label for='data-002cc507-d517-496d-9a41-59e017f6a2d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c544a3c8-ac2a-48b8-a76b-035293a15b85' class='xr-section-summary-in' type='checkbox'  ><label for='section-c544a3c8-ac2a-48b8-a76b-035293a15b85' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e57de9aa-c50d-4ef9-a1a5-97cf8c732f9c' class='xr-index-data-in' type='checkbox'/><label for='index-e57de9aa-c50d-4ef9-a1a5-97cf8c732f9c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1990-01-16 12:00:00&#x27;, &#x27;1990-02-15 00:00:00&#x27;,\n",
       "               &#x27;1990-03-16 12:00:00&#x27;, &#x27;1990-04-16 00:00:00&#x27;,\n",
       "               &#x27;1990-05-16 12:00:00&#x27;, &#x27;1990-06-16 00:00:00&#x27;,\n",
       "               &#x27;1990-07-16 12:00:00&#x27;, &#x27;1990-08-16 12:00:00&#x27;,\n",
       "               &#x27;1990-09-16 00:00:00&#x27;, &#x27;1990-10-16 12:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2020-03-16 12:00:00&#x27;, &#x27;2020-04-16 12:00:00&#x27;,\n",
       "               &#x27;2020-05-16 12:00:00&#x27;, &#x27;2020-06-16 12:00:00&#x27;,\n",
       "               &#x27;2020-07-16 12:00:00&#x27;, &#x27;2020-08-16 12:00:00&#x27;,\n",
       "               &#x27;2020-09-16 12:00:00&#x27;, &#x27;2020-10-16 12:00:00&#x27;,\n",
       "               &#x27;2020-11-16 12:00:00&#x27;, &#x27;2020-12-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=372, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-fdbe915f-32e2-441f-a9f8-77bfe68cb1f6' class='xr-index-data-in' type='checkbox'/><label for='index-fdbe915f-32e2-441f-a9f8-77bfe68cb1f6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a0e968eb-4ad5-4d73-98d6-14b12c3bed71' class='xr-index-data-in' type='checkbox'/><label for='index-a0e968eb-4ad5-4d73-98d6-14b12c3bed71' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9cca686a-83b2-46d1-a449-d5621cdae6ad' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9cca686a-83b2-46d1-a449-d5621cdae6ad' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 372, lat: 90, lon: 180)>\n",
       "[6026400 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1990-01-16T12:00:00 ... 2020-12-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst.loc[\"1990\":\"2020\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
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       "}\n",
       "\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
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       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
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       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 372, lat: 90, lon: 180)&gt;\n",
       "[6026400 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1990-01-16T12:00:00 ... 2020-12-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 372</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-794a46e4-ccdf-4b63-bbc7-bb290d9a177b' class='xr-array-in' type='checkbox' checked><label for='section-794a46e4-ccdf-4b63-bbc7-bb290d9a177b' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[6026400 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-646df32b-7e86-4adb-9ad9-7d57f0fe6dea' class='xr-section-summary-in' type='checkbox'  checked><label for='section-646df32b-7e86-4adb-9ad9-7d57f0fe6dea' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1990-01-16T12:00:00 ... 2020-12-...</div><input id='attrs-d8feed09-3a64-4b28-88c0-13d2a3256e87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8feed09-3a64-4b28-88c0-13d2a3256e87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5201190f-a0d7-4a61-a5c8-684fc848a07f' class='xr-var-data-in' type='checkbox'><label for='data-5201190f-a0d7-4a61-a5c8-684fc848a07f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1990-01-16T12:00:00.000000000&#x27;, &#x27;1990-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-03-16T12:00:00.000000000&#x27;, ..., &#x27;2020-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2020-11-16T12:00:00.000000000&#x27;, &#x27;2020-12-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-07195d9c-acd3-4be8-9687-8d2fa7bdfd0c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07195d9c-acd3-4be8-9687-8d2fa7bdfd0c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8420b92-a6b3-4069-ae12-4d9664db29b0' class='xr-var-data-in' type='checkbox'><label for='data-d8420b92-a6b3-4069-ae12-4d9664db29b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-52d50550-4bac-4e6f-a689-3614a131f973' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52d50550-4bac-4e6f-a689-3614a131f973' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0221453e-055b-465d-9988-456cda009771' class='xr-var-data-in' type='checkbox'><label for='data-0221453e-055b-465d-9988-456cda009771' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f35f7d9c-0d0e-4fd0-b7ec-1821d9093047' class='xr-section-summary-in' type='checkbox'  ><label for='section-f35f7d9c-0d0e-4fd0-b7ec-1821d9093047' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e775146c-9f27-45c1-8c57-d77ef1526953' class='xr-index-data-in' type='checkbox'/><label for='index-e775146c-9f27-45c1-8c57-d77ef1526953' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1990-01-16 12:00:00&#x27;, &#x27;1990-02-15 00:00:00&#x27;,\n",
       "               &#x27;1990-03-16 12:00:00&#x27;, &#x27;1990-04-16 00:00:00&#x27;,\n",
       "               &#x27;1990-05-16 12:00:00&#x27;, &#x27;1990-06-16 00:00:00&#x27;,\n",
       "               &#x27;1990-07-16 12:00:00&#x27;, &#x27;1990-08-16 12:00:00&#x27;,\n",
       "               &#x27;1990-09-16 00:00:00&#x27;, &#x27;1990-10-16 12:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2020-03-16 12:00:00&#x27;, &#x27;2020-04-16 12:00:00&#x27;,\n",
       "               &#x27;2020-05-16 12:00:00&#x27;, &#x27;2020-06-16 12:00:00&#x27;,\n",
       "               &#x27;2020-07-16 12:00:00&#x27;, &#x27;2020-08-16 12:00:00&#x27;,\n",
       "               &#x27;2020-09-16 12:00:00&#x27;, &#x27;2020-10-16 12:00:00&#x27;,\n",
       "               &#x27;2020-11-16 12:00:00&#x27;, &#x27;2020-12-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=372, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4d6eef0a-90d8-4ef5-a60b-b1d61b1cae2f' class='xr-index-data-in' type='checkbox'/><label for='index-4d6eef0a-90d8-4ef5-a60b-b1d61b1cae2f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1a39af28-5ca5-4e16-b7bf-c6cf72a94852' class='xr-index-data-in' type='checkbox'/><label for='index-1a39af28-5ca5-4e16-b7bf-c6cf72a94852' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2dda9227-93d6-4c28-9990-8872b788d95a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2dda9227-93d6-4c28-9990-8872b788d95a' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 372, lat: 90, lon: 180)>\n",
       "[6026400 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1990-01-16T12:00:00 ... 2020-12-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst.loc[{\"time\":slice(\"1990\",\"2020\")}]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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       "  * time     (time) datetime64[ns] 1990-01-16T12:00:00 ... 2020-12-16T12:00:00\n",
       "  * lon      (lon) float64 190.0 192.0 194.0 196.0 ... 234.0 236.0 238.0 240.0\n",
       "  * lat      (lat) float64 -5.0 -3.0 -1.0 1.0 3.0 5.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 372</li><li><span class='xr-has-index'>lat</span>: 6</li><li><span class='xr-has-index'>lon</span>: 26</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-838371fd-0533-418b-a896-d354e5b39a67' class='xr-array-in' type='checkbox' checked><label for='section-838371fd-0533-418b-a896-d354e5b39a67' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[58032 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-cf9e7bc2-ecfa-4da7-9f86-a75a8a531c3a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cf9e7bc2-ecfa-4da7-9f86-a75a8a531c3a' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1990-01-16T12:00:00 ... 2020-12-...</div><input id='attrs-4a11111c-ce01-4631-a7a6-3efe15f6e992' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a11111c-ce01-4631-a7a6-3efe15f6e992' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05e7de8f-9f2d-48ad-bb6d-9968c3f900cc' class='xr-var-data-in' type='checkbox'><label for='data-05e7de8f-9f2d-48ad-bb6d-9968c3f900cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1990-01-16T12:00:00.000000000&#x27;, &#x27;1990-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-03-16T12:00:00.000000000&#x27;, ..., &#x27;2020-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2020-11-16T12:00:00.000000000&#x27;, &#x27;2020-12-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>190.0 192.0 194.0 ... 238.0 240.0</div><input id='attrs-b0817e5f-dee8-41e9-8f56-bcd7a371eb9e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0817e5f-dee8-41e9-8f56-bcd7a371eb9e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46e7702e-2f60-4b91-b5d7-98fd09419e7d' class='xr-var-data-in' type='checkbox'><label for='data-46e7702e-2f60-4b91-b5d7-98fd09419e7d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([190., 192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212.,\n",
       "       214., 216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236.,\n",
       "       238., 240.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.0 -3.0 -1.0 1.0 3.0 5.0</div><input id='attrs-fa20443f-91da-4c11-b7de-110fbea65a4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa20443f-91da-4c11-b7de-110fbea65a4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a299c31f-11f1-42f3-97c5-03b37dfadcda' class='xr-var-data-in' type='checkbox'><label for='data-a299c31f-11f1-42f3-97c5-03b37dfadcda' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-5., -3., -1.,  1.,  3.,  5.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fa0dbf80-b99a-47fd-9e28-82b3a216648d' class='xr-section-summary-in' type='checkbox'  ><label for='section-fa0dbf80-b99a-47fd-9e28-82b3a216648d' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cd803cd2-475a-4b0e-81f5-56a7f448f298' class='xr-index-data-in' type='checkbox'/><label for='index-cd803cd2-475a-4b0e-81f5-56a7f448f298' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1990-01-16 12:00:00&#x27;, &#x27;1990-02-15 00:00:00&#x27;,\n",
       "               &#x27;1990-03-16 12:00:00&#x27;, &#x27;1990-04-16 00:00:00&#x27;,\n",
       "               &#x27;1990-05-16 12:00:00&#x27;, &#x27;1990-06-16 00:00:00&#x27;,\n",
       "               &#x27;1990-07-16 12:00:00&#x27;, &#x27;1990-08-16 12:00:00&#x27;,\n",
       "               &#x27;1990-09-16 00:00:00&#x27;, &#x27;1990-10-16 12:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2020-03-16 12:00:00&#x27;, &#x27;2020-04-16 12:00:00&#x27;,\n",
       "               &#x27;2020-05-16 12:00:00&#x27;, &#x27;2020-06-16 12:00:00&#x27;,\n",
       "               &#x27;2020-07-16 12:00:00&#x27;, &#x27;2020-08-16 12:00:00&#x27;,\n",
       "               &#x27;2020-09-16 12:00:00&#x27;, &#x27;2020-10-16 12:00:00&#x27;,\n",
       "               &#x27;2020-11-16 12:00:00&#x27;, &#x27;2020-12-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=372, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-57d8491e-e418-42b5-88e3-ad860558e497' class='xr-index-data-in' type='checkbox'/><label for='index-57d8491e-e418-42b5-88e3-ad860558e497' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([190.0, 192.0, 194.0, 196.0, 198.0, 200.0, 202.0, 204.0, 206.0,\n",
       "              208.0, 210.0, 212.0, 214.0, 216.0, 218.0, 220.0, 222.0, 224.0,\n",
       "              226.0, 228.0, 230.0, 232.0, 234.0, 236.0, 238.0, 240.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-073eab33-8714-4475-bad4-829e1edfca75' class='xr-index-data-in' type='checkbox'/><label for='index-073eab33-8714-4475-bad4-829e1edfca75' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-5.0, -3.0, -1.0, 1.0, 3.0, 5.0], dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b7b4fb8a-ec02-4a7a-8674-f0bcf7b5a427' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b7b4fb8a-ec02-4a7a-8674-f0bcf7b5a427' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 372, lat: 6, lon: 26)>\n",
       "[58032 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1990-01-16T12:00:00 ... 2020-12-16T12:00:00\n",
       "  * lon      (lon) float64 190.0 192.0 194.0 196.0 ... 234.0 236.0 238.0 240.0\n",
       "  * lat      (lat) float64 -5.0 -3.0 -1.0 1.0 3.0 5.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst.loc[{\"time\":slice(\"1990\",\"2020\"),\"lat\":slice(-5,5),\"lon\":slice(190,240)}]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
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       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 372, lat: 6, lon: 26)&gt;\n",
       "[58032 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1990-01-16T12:00:00 ... 2020-12-16T12:00:00\n",
       "  * lon      (lon) float64 190.0 192.0 194.0 196.0 ... 234.0 236.0 238.0 240.0\n",
       "  * lat      (lat) float64 -5.0 -3.0 -1.0 1.0 3.0 5.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 372</li><li><span class='xr-has-index'>lat</span>: 6</li><li><span class='xr-has-index'>lon</span>: 26</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-57aeb495-2078-46d8-8d70-8efd63e021db' class='xr-array-in' type='checkbox' checked><label for='section-57aeb495-2078-46d8-8d70-8efd63e021db' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[58032 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-95b7f994-01f6-43eb-befb-3a12d68bb54b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-95b7f994-01f6-43eb-befb-3a12d68bb54b' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1990-01-16T12:00:00 ... 2020-12-...</div><input id='attrs-dbd46202-bfb3-4eac-b060-e40c64bd9649' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dbd46202-bfb3-4eac-b060-e40c64bd9649' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d79f21d6-3cec-409d-bdc0-641f6b573ddd' class='xr-var-data-in' type='checkbox'><label for='data-d79f21d6-3cec-409d-bdc0-641f6b573ddd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1990-01-16T12:00:00.000000000&#x27;, &#x27;1990-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-03-16T12:00:00.000000000&#x27;, ..., &#x27;2020-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2020-11-16T12:00:00.000000000&#x27;, &#x27;2020-12-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>190.0 192.0 194.0 ... 238.0 240.0</div><input id='attrs-8608d1f9-146d-47de-b650-77158d787a5b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8608d1f9-146d-47de-b650-77158d787a5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b93c6306-ff25-45df-b91f-5b629920bf21' class='xr-var-data-in' type='checkbox'><label for='data-b93c6306-ff25-45df-b91f-5b629920bf21' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([190., 192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212.,\n",
       "       214., 216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236.,\n",
       "       238., 240.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.0 -3.0 -1.0 1.0 3.0 5.0</div><input id='attrs-5a11c3a4-7112-4585-9b58-12bb92b11191' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a11c3a4-7112-4585-9b58-12bb92b11191' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-368e820d-eefc-41ad-82ee-2e8ddc08919e' class='xr-var-data-in' type='checkbox'><label for='data-368e820d-eefc-41ad-82ee-2e8ddc08919e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-5., -3., -1.,  1.,  3.,  5.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c61757e0-370c-43fc-82f0-c25db29ce692' class='xr-section-summary-in' type='checkbox'  ><label for='section-c61757e0-370c-43fc-82f0-c25db29ce692' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-182ac90c-17a5-4d31-bf18-f6351ec52c95' class='xr-index-data-in' type='checkbox'/><label for='index-182ac90c-17a5-4d31-bf18-f6351ec52c95' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1990-01-16 12:00:00&#x27;, &#x27;1990-02-15 00:00:00&#x27;,\n",
       "               &#x27;1990-03-16 12:00:00&#x27;, &#x27;1990-04-16 00:00:00&#x27;,\n",
       "               &#x27;1990-05-16 12:00:00&#x27;, &#x27;1990-06-16 00:00:00&#x27;,\n",
       "               &#x27;1990-07-16 12:00:00&#x27;, &#x27;1990-08-16 12:00:00&#x27;,\n",
       "               &#x27;1990-09-16 00:00:00&#x27;, &#x27;1990-10-16 12:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2020-03-16 12:00:00&#x27;, &#x27;2020-04-16 12:00:00&#x27;,\n",
       "               &#x27;2020-05-16 12:00:00&#x27;, &#x27;2020-06-16 12:00:00&#x27;,\n",
       "               &#x27;2020-07-16 12:00:00&#x27;, &#x27;2020-08-16 12:00:00&#x27;,\n",
       "               &#x27;2020-09-16 12:00:00&#x27;, &#x27;2020-10-16 12:00:00&#x27;,\n",
       "               &#x27;2020-11-16 12:00:00&#x27;, &#x27;2020-12-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=372, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-29c4ce65-4470-4528-8475-95e3d3ee3ebb' class='xr-index-data-in' type='checkbox'/><label for='index-29c4ce65-4470-4528-8475-95e3d3ee3ebb' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([190.0, 192.0, 194.0, 196.0, 198.0, 200.0, 202.0, 204.0, 206.0,\n",
       "              208.0, 210.0, 212.0, 214.0, 216.0, 218.0, 220.0, 222.0, 224.0,\n",
       "              226.0, 228.0, 230.0, 232.0, 234.0, 236.0, 238.0, 240.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5a9126b6-9e5b-49a4-be83-e565a1537839' class='xr-index-data-in' type='checkbox'/><label for='index-5a9126b6-9e5b-49a4-be83-e565a1537839' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-5.0, -3.0, -1.0, 1.0, 3.0, 5.0], dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ea0e013f-481f-4af2-8b03-2fecc3417bd6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ea0e013f-481f-4af2-8b03-2fecc3417bd6' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 372, lat: 6, lon: 26)>\n",
       "[58032 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1990-01-16T12:00:00 ... 2020-12-16T12:00:00\n",
       "  * lon      (lon) float64 190.0 192.0 194.0 196.0 ... 234.0 236.0 238.0 240.0\n",
       "  * lat      (lat) float64 -5.0 -3.0 -1.0 1.0 3.0 5.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst.loc[\"1990\":\"2020\",-5:5,190:240] # 必须按照顺序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1828, 90, 180)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst.coords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'standard_name': 'sea_surface_temperature',\n",
       " 'long_name': 'sst',\n",
       " 'units': 'C',\n",
       " 'cell_methods': 'time: lat: lon: mean'}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst.attrs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  317991.,        0.,   110274.,        0.,   362321.,        0.,\n",
       "               0.,   256465.,        0., 17869093.]),\n",
       " array([-1000.        ,  -896.48669434,  -792.97338867,  -689.46008301,\n",
       "         -585.94677734,  -482.43347168,  -378.92016602,  -275.40689087,\n",
       "         -171.89356995,   -68.38027191,    35.13303375]),\n",
       " <BarContainer object of 10 artists>)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "sst.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x169c34520>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "sst[0].plot.contourf(levels=np.linspace(1,40,20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x169dcfbb0>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sst[:,50,100].plot()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x17c62de20>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 求平均\n",
    "\n",
    "sst_ave = sst.mean(\"time\")\n",
    "sst_ave.plot.contourf(levels=np.linspace(1,40,20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x17c7b0700>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sst_ave = sst.mean(\"lon\")\n",
    "sst_ave.plot.contourf(levels=np.linspace(1,40,20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x17d2168e0>]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sst_ave = sst.mean((\"lon\",\"lat\"))\n",
    "sst_ave.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
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       "\n",
       "html[theme=dark],\n",
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       "  --xr-border-color: #1F1F1F;\n",
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       "  --xr-background-color: #111111;\n",
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       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
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       "\n",
       ".xr-text-repr-fallback {\n",
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       "\n",
       ".xr-header {\n",
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       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
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       "}\n",
       "\n",
       ".xr-header > div,\n",
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       "\n",
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       "  color: var(--xr-font-color2);\n",
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       ".xr-sections {\n",
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       ".xr-section-item {\n",
       "  display: contents;\n",
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       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
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       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
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       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
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       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
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       "  padding-right: 5px;\n",
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       "\n",
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       "\n",
       ".xr-var-list,\n",
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       "\n",
       ".xr-var-item > div,\n",
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       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
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       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
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       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
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       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
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       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; ()&gt;\n",
       "array(35.13303375)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-688bbe4e-fd9d-409e-8ae6-bc55cb08d5f8' class='xr-array-in' type='checkbox' checked><label for='section-688bbe4e-fd9d-409e-8ae6-bc55cb08d5f8' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>35.13</span></div><div class='xr-array-data'><pre>array(35.13303375)</pre></div></div></li><li class='xr-section-item'><input id='section-f9ff0a74-1cb2-4a09-8aa4-aa035b71102d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f9ff0a74-1cb2-4a09-8aa4-aa035b71102d' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-3da86500-5301-4378-a1a2-c709a6d4f566' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3da86500-5301-4378-a1a2-c709a6d4f566' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-44d4f5d6-4c26-4690-ad8a-19497f88fac3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-44d4f5d6-4c26-4690-ad8a-19497f88fac3' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' ()>\n",
       "array(35.13303375)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
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       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
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       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
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       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
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       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
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       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-var-name,\n",
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       ".xr-var-data,\n",
       ".xr-index-data {\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
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       "\n",
       ".xr-var-data > table {\n",
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       "\n",
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       ".xr-attrs {\n",
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       "\n",
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       ".xr-index-data {\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
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       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; ()&gt;\n",
       "array(-1000.)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-f1897a8c-594b-43fa-8f7e-8a5ad61ddb1c' class='xr-array-in' type='checkbox' checked><label for='section-f1897a8c-594b-43fa-8f7e-8a5ad61ddb1c' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-1e+03</span></div><div class='xr-array-data'><pre>array(-1000.)</pre></div></div></li><li class='xr-section-item'><input id='section-34a2ca06-7934-42a2-8497-de01d0c5bfc1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-34a2ca06-7934-42a2-8497-de01d0c5bfc1' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-9333ac7a-e64e-4c88-a0a7-1bf5c6d1cae6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9333ac7a-e64e-4c88-a0a7-1bf5c6d1cae6' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-cdb02869-bf9a-413b-aa71-61a62e178f7c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cdb02869-bf9a-413b-aa71-61a62e178f7c' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' ()>\n",
       "array(-1000.)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (lat: 90, lon: 180)&gt;\n",
       "array([[        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [-0.3519287 , -0.3121338 , -0.44213867, ...,  0.05297852,\n",
       "         0.06225586, -0.07226562],\n",
       "       [-1.5227051 , -1.4841309 , -1.5607178 , ..., -1.5499268 ,\n",
       "        -1.6201172 , -1.4986572 ],\n",
       "       [-1.8       , -1.8       , -1.8       , ..., -1.8       ,\n",
       "        -1.8       , -1.8       ]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-260dd921-6e78-49ef-b384-729846e1b52b' class='xr-array-in' type='checkbox' checked><label for='section-260dd921-6e78-49ef-b384-729846e1b52b' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan nan nan nan nan nan nan ... -1.8 -1.8 -1.8 -1.8 -1.8 -1.8 -1.8</span></div><div class='xr-array-data'><pre>array([[        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [-0.3519287 , -0.3121338 , -0.44213867, ...,  0.05297852,\n",
       "         0.06225586, -0.07226562],\n",
       "       [-1.5227051 , -1.4841309 , -1.5607178 , ..., -1.5499268 ,\n",
       "        -1.6201172 , -1.4986572 ],\n",
       "       [-1.8       , -1.8       , -1.8       , ..., -1.8       ,\n",
       "        -1.8       , -1.8       ]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-fc9bd17a-1f3d-4516-8822-9e1ebd830440' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fc9bd17a-1f3d-4516-8822-9e1ebd830440' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-e963529b-3d52-401f-b93e-8b4a6c98757d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e963529b-3d52-401f-b93e-8b4a6c98757d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22b83012-a645-42ad-9c67-48ee74ca5c25' class='xr-var-data-in' type='checkbox'><label for='data-22b83012-a645-42ad-9c67-48ee74ca5c25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-5d4996d9-58e3-4b40-bb14-8a140331676f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d4996d9-58e3-4b40-bb14-8a140331676f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a43a89a-1e5b-4c06-9f55-4c4afe6a30ff' class='xr-var-data-in' type='checkbox'><label for='data-4a43a89a-1e5b-4c06-9f55-4c4afe6a30ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fabede69-651d-4cbf-8407-5526c3e93157' class='xr-section-summary-in' type='checkbox'  ><label for='section-fabede69-651d-4cbf-8407-5526c3e93157' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3db905f3-df68-40ac-a494-a1a8fc303f75' class='xr-index-data-in' type='checkbox'/><label for='index-3db905f3-df68-40ac-a494-a1a8fc303f75' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c1243456-f57e-4ad9-86d7-18c2461cbb95' class='xr-index-data-in' type='checkbox'/><label for='index-c1243456-f57e-4ad9-86d7-18c2461cbb95' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ad9cf37e-47c0-4abc-b5a0-4e1920c51f7d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ad9cf37e-47c0-4abc-b5a0-4e1920c51f7d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (lat: 90, lon: 180)>\n",
       "array([[        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [-0.3519287 , -0.3121338 , -0.44213867, ...,  0.05297852,\n",
       "         0.06225586, -0.07226562],\n",
       "       [-1.5227051 , -1.4841309 , -1.5607178 , ..., -1.5499268 ,\n",
       "        -1.6201172 , -1.4986572 ],\n",
       "       [-1.8       , -1.8       , -1.8       , ..., -1.8       ,\n",
       "        -1.8       , -1.8       ]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sst_t_max = sst.max(\"time\")\n",
    "sst_t_max"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
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       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 1828, lat: 90, lon: 180)&gt;\n",
       "array([[[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-0.9738476 , -0.9738476 , -0.9738476 , ..., -0.9738476 ,\n",
       "         -0.9738476 , -0.9738476 ],\n",
       "        [-0.9738476 , -0.9738476 , -0.9738476 , ..., -0.9738476 ,\n",
       "         -0.9738476 , -0.9738476 ],\n",
       "        [ 0.983119  ,  0.983119  ,  0.983119  , ...,  0.983119  ,\n",
       "          0.983119  ,  0.983119  ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "...\n",
       "        [-0.02257664, -0.9738476 ,  0.983119  , ..., -0.02259189,\n",
       "         -0.02257664, -0.9738476 ],\n",
       "        [ 0.983119  , -0.3807729 , -0.82687956, ...,  0.983119  ,\n",
       "          0.983119  ,  0.983119  ],\n",
       "        [-0.3807729 , -0.82687956, -0.82687956, ..., -0.82687956,\n",
       "         -0.82687956, -0.82687956]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [ 0.983119  ,  0.983119  , -0.3807729 , ...,  0.983119  ,\n",
       "          0.983119  , -0.9738476 ],\n",
       "        [-0.82687956, -0.82687956, -0.82687956, ..., -0.82687956,\n",
       "         -0.82687956, -0.82687956],\n",
       "        [-0.3807729 ,  0.9831134 ,  0.9831134 , ..., -0.82687956,\n",
       "         -0.82687956,  0.9831134 ]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1828</li><li><span class='xr-has-index'>lat</span>: 90</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-a49f06ed-5212-4eff-85e7-decc63076c70' class='xr-array-in' type='checkbox' checked><label for='section-a49f06ed-5212-4eff-85e7-decc63076c70' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan nan nan nan nan ... -0.8269 -0.8269 -0.8269 -0.8269 0.9831</span></div><div class='xr-array-data'><pre>array([[[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-0.9738476 , -0.9738476 , -0.9738476 , ..., -0.9738476 ,\n",
       "         -0.9738476 , -0.9738476 ],\n",
       "        [-0.9738476 , -0.9738476 , -0.9738476 , ..., -0.9738476 ,\n",
       "         -0.9738476 , -0.9738476 ],\n",
       "        [ 0.983119  ,  0.983119  ,  0.983119  , ...,  0.983119  ,\n",
       "          0.983119  ,  0.983119  ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "...\n",
       "        [-0.02257664, -0.9738476 ,  0.983119  , ..., -0.02259189,\n",
       "         -0.02257664, -0.9738476 ],\n",
       "        [ 0.983119  , -0.3807729 , -0.82687956, ...,  0.983119  ,\n",
       "          0.983119  ,  0.983119  ],\n",
       "        [-0.3807729 , -0.82687956, -0.82687956, ..., -0.82687956,\n",
       "         -0.82687956, -0.82687956]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [ 0.983119  ,  0.983119  , -0.3807729 , ...,  0.983119  ,\n",
       "          0.983119  , -0.9738476 ],\n",
       "        [-0.82687956, -0.82687956, -0.82687956, ..., -0.82687956,\n",
       "         -0.82687956, -0.82687956],\n",
       "        [-0.3807729 ,  0.9831134 ,  0.9831134 , ..., -0.82687956,\n",
       "         -0.82687956,  0.9831134 ]]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-dce6ef45-6bd0-483a-94b0-1dc395c65c10' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dce6ef45-6bd0-483a-94b0-1dc395c65c10' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1870-01-16T12:00:00 ... 2022-04-...</div><input id='attrs-d3f2d74d-77db-4961-91d1-b60ccb563700' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3f2d74d-77db-4961-91d1-b60ccb563700' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b65877b8-82a7-4e75-9181-a3fb1f6d3e3c' class='xr-var-data-in' type='checkbox'><label for='data-b65877b8-82a7-4e75-9181-a3fb1f6d3e3c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1870-01-16T12:00:00.000000000&#x27;, &#x27;1870-02-14T23:59:59.011230469&#x27;,\n",
       "       &#x27;1870-03-16T11:59:58.681640625&#x27;, ..., &#x27;2022-02-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2022-03-16T12:00:00.000000000&#x27;, &#x27;2022-04-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-182c498d-1af1-4ab0-8869-574e502c3f18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-182c498d-1af1-4ab0-8869-574e502c3f18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-abb4f800-8523-41b4-b593-e149ff1a36c9' class='xr-var-data-in' type='checkbox'><label for='data-abb4f800-8523-41b4-b593-e149ff1a36c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.0 -87.0 -85.0 ... 87.0 89.0</div><input id='attrs-1018aac1-2376-46ec-a4a8-add852d90295' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1018aac1-2376-46ec-a4a8-add852d90295' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26a913a8-aaa2-404f-9408-aeac036f3dc1' class='xr-var-data-in' type='checkbox'><label for='data-26a913a8-aaa2-404f-9408-aeac036f3dc1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-89., -87., -85., -83., -81., -79., -77., -75., -73., -71., -69., -67.,\n",
       "       -65., -63., -61., -59., -57., -55., -53., -51., -49., -47., -45., -43.,\n",
       "       -41., -39., -37., -35., -33., -31., -29., -27., -25., -23., -21., -19.,\n",
       "       -17., -15., -13., -11.,  -9.,  -7.,  -5.,  -3.,  -1.,   1.,   3.,   5.,\n",
       "         7.,   9.,  11.,  13.,  15.,  17.,  19.,  21.,  23.,  25.,  27.,  29.,\n",
       "        31.,  33.,  35.,  37.,  39.,  41.,  43.,  45.,  47.,  49.,  51.,  53.,\n",
       "        55.,  57.,  59.,  61.,  63.,  65.,  67.,  69.,  71.,  73.,  75.,  77.,\n",
       "        79.,  81.,  83.,  85.,  87.,  89.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-90846f28-bbe8-476c-a4a9-239370d55467' class='xr-section-summary-in' type='checkbox'  ><label for='section-90846f28-bbe8-476c-a4a9-239370d55467' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7767c260-1657-4ecc-b282-e3f1094eae79' class='xr-index-data-in' type='checkbox'/><label for='index-7767c260-1657-4ecc-b282-e3f1094eae79' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([          &#x27;1870-01-16 12:00:00&#x27;,\n",
       "               &#x27;1870-02-14 23:59:59.011230469&#x27;,\n",
       "               &#x27;1870-03-16 11:59:58.681640625&#x27;,\n",
       "               &#x27;1870-04-15 23:59:58.681640624&#x27;,\n",
       "                         &#x27;1870-05-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-06-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-07-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-08-16 12:00:00&#x27;,\n",
       "                         &#x27;1870-09-16 00:00:00&#x27;,\n",
       "                         &#x27;1870-10-16 12:00:00&#x27;,\n",
       "               ...\n",
       "                         &#x27;2021-07-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-08-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-09-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-10-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-11-16 12:00:00&#x27;,\n",
       "                         &#x27;2021-12-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-01-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-02-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-03-16 12:00:00&#x27;,\n",
       "                         &#x27;2022-04-16 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1828, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-fe0c0d08-79c8-49cc-996d-45c3469106ab' class='xr-index-data-in' type='checkbox'/><label for='index-fe0c0d08-79c8-49cc-996d-45c3469106ab' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,\n",
       "               18.0,\n",
       "              ...\n",
       "              340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0,\n",
       "              358.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-223765ca-883b-42ed-b48c-990d801796e7' class='xr-index-data-in' type='checkbox'/><label for='index-223765ca-883b-42ed-b48c-990d801796e7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-89.0, -87.0, -85.0, -83.0, -81.0, -79.0, -77.0, -75.0, -73.0,\n",
       "              -71.0, -69.0, -67.0, -65.0, -63.0, -61.0, -59.0, -57.0, -55.0,\n",
       "              -53.0, -51.0, -49.0, -47.0, -45.0, -43.0, -41.0, -39.0, -37.0,\n",
       "              -35.0, -33.0, -31.0, -29.0, -27.0, -25.0, -23.0, -21.0, -19.0,\n",
       "              -17.0, -15.0, -13.0, -11.0,  -9.0,  -7.0,  -5.0,  -3.0,  -1.0,\n",
       "                1.0,   3.0,   5.0,   7.0,   9.0,  11.0,  13.0,  15.0,  17.0,\n",
       "               19.0,  21.0,  23.0,  25.0,  27.0,  29.0,  31.0,  33.0,  35.0,\n",
       "               37.0,  39.0,  41.0,  43.0,  45.0,  47.0,  49.0,  51.0,  53.0,\n",
       "               55.0,  57.0,  59.0,  61.0,  63.0,  65.0,  67.0,  69.0,  71.0,\n",
       "               73.0,  75.0,  77.0,  79.0,  81.0,  83.0,  85.0,  87.0,  89.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b198731e-2b41-4fb2-b291-9eab7bac19c4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b198731e-2b41-4fb2-b291-9eab7bac19c4' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>long_name :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>C</dd><dt><span>cell_methods :</span></dt><dd>time: lat: lon: mean</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (time: 1828, lat: 90, lon: 180)>\n",
       "array([[[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [-0.9738476 , -0.9738476 , -0.9738476 , ..., -0.9738476 ,\n",
       "         -0.9738476 , -0.9738476 ],\n",
       "        [-0.9738476 , -0.9738476 , -0.9738476 , ..., -0.9738476 ,\n",
       "         -0.9738476 , -0.9738476 ],\n",
       "        [ 0.983119  ,  0.983119  ,  0.983119  , ...,  0.983119  ,\n",
       "          0.983119  ,  0.983119  ]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "...\n",
       "        [-0.02257664, -0.9738476 ,  0.983119  , ..., -0.02259189,\n",
       "         -0.02257664, -0.9738476 ],\n",
       "        [ 0.983119  , -0.3807729 , -0.82687956, ...,  0.983119  ,\n",
       "          0.983119  ,  0.983119  ],\n",
       "        [-0.3807729 , -0.82687956, -0.82687956, ..., -0.82687956,\n",
       "         -0.82687956, -0.82687956]],\n",
       "\n",
       "       [[        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        [        nan,         nan,         nan, ...,         nan,\n",
       "                 nan,         nan],\n",
       "        ...,\n",
       "        [ 0.983119  ,  0.983119  , -0.3807729 , ...,  0.983119  ,\n",
       "          0.983119  , -0.9738476 ],\n",
       "        [-0.82687956, -0.82687956, -0.82687956, ..., -0.82687956,\n",
       "         -0.82687956, -0.82687956],\n",
       "        [-0.3807729 ,  0.9831134 ,  0.9831134 , ..., -0.82687956,\n",
       "         -0.82687956,  0.9831134 ]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1870-01-16T12:00:00 ... 2022-04-16T12:00:00\n",
       "  * lon      (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * lat      (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0\n",
       "Attributes:\n",
       "    standard_name:  sea_surface_temperature\n",
       "    long_name:      sst\n",
       "    units:          C\n",
       "    cell_methods:   time: lat: lon: mean"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sin(sst)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 课后作业\n",
    "\n",
    "使用xarray画出全球平均海温的空间分布\n",
    "\n",
    "使用xarray画出Nino3.4区域的海温随时间的变化"
   ]
  }
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