Latest development merge

.gitignore

@@ -2,3 +2,4 @@
 .Rhistory
 .RData
 .Ruserdata
+README.html

R/knownVariables.r

@@ -38,7 +38,6 @@ gssRndcode <- "low"
 gss_symbols <- c(gssNApcode, gssNAvcode, gssSupcode, gssRndcode)
 legacy_gss_symbols <- c("~", ":")
 
-
 geography_matrix <- matrix(
   c(
     "National", "country_code", "country_name", NA,
@@ -47,6 +46,7 @@ geography_matrix <- matrix(
     "Local authority district", "lad_code", "lad_name", NA,
     "RSC region", "rsc_region_lead_name", NA, NA,
     "Parliamentary constituency", "pcon_code", "pcon_name", NA,
+    "Local skills improvement plan area", "lsip_code", "lsip_name", NA,
     "Local enterprise partnership", "local_enterprise_partnership_code", "local_enterprise_partnership_name", NA,
     "English devolved area", "english_devolved_area_code", "english_devolved_area_name", NA,
     "Opportunity area", "opportunity_area_code", "opportunity_area_name", NA,
@@ -62,8 +62,20 @@ geography_matrix <- matrix(
   byrow = TRUE
 )
 
+geography_dataframe <- geography_matrix %>%
+  as.data.frame() %>%
+  select(geographic_level = V1, code_field = V2, name_field = V3, code_field_secondary = V4)
+
+# Pull out lower level geographies that we don't have standardised lists for (and excluding school-provider etc levels)
+lower_level_geog_levels <- c("Opportunity area", "Ward", "MAT", "Sponsor")
+lower_level_geog_names <- geography_dataframe %>%
+  filter(geographic_level %in% lower_level_geog_levels) %>%
+  pivot_longer(c(code_field, name_field)) %>%
+  pull(value)
+
 countries <- suppressMessages(read_csv("data/country.csv")) # change this to database eventually
 regions <- suppressMessages(read_csv("data/regions.csv")) # change this to database eventually
+lsips <- suppressMessages(read_csv("data/lsips.csv")) # change this to database eventually
 las <- suppressMessages(read_csv("data/las.csv")) # change this to database eventually
 lads <- suppressMessages(read_csv("data/lads.csv")) # change this to database eventually
 pcons <- suppressMessages(read_csv("data/pcons.csv")) # change this to database eventually
@@ -74,6 +86,8 @@ expected_country_combinations <- unique(paste(countries$country_code, countries$
 
 expected_region_combinations <- unique(paste(regions$region_code, regions$region_name))
 
+expected_lsip_combinations <- unique(paste(lsips$lsip_code, lsips$lsip_name))
+
 expected_la_combinations <- unique(paste(las$old_la_code, las$new_la_code, las$la_name))
 
 expected_lad_combinations <- unique(paste(lads$lad_code, lads$lad_name))

README.md

@@ -10,6 +10,7 @@
   <a href="#introduction">Introduction</a> |
   <a href="#requirements">Requirements</a> |
   <a href="#how-to-use">How to use</a> |
+  <a href="#data-sources">Data sources</a> |
   <a href="#contact">Contact</a>
 </p>
 
@@ -104,6 +105,18 @@ The function `tidy_code()` is created in the Rprofile script and therefore is al
 
 ---
 
+## Data sources
+
+### Geographies
+
+The standard geographies used in this tool are sourced from (or developed with) the Office for National Statistics (ONS). As such, they are maintained in line with the ONS's [open geography portal](https://geoportal.statistics.gov.uk/). Some further details on specific geographic levels are provided below.
+
+#### Local skills improvement plan area (LSIP)
+
+These were developed in direct communications with the ONS ([ONS Geography e-mail](mailto:[email protected])) and they provided the basis for the code and name file used in this tool. At the time of writing, this has not been added to the open geography portal, although boundary files have been ([LSIP boundary map files](https://geoportal.statistics.gov.uk/search?collection=Dataset&sort=name&tags=all(BDY_LSIP%2CAUG_2023))).
+
+---
+
 ## Contact
 
 

data/lsips.csv

@@ -0,0 +1,39 @@
+lsip_code,lsip_name
+E69000001,"Brighton and Hove, East Sussex, West Sussex"
+E69000002,Buckinghamshire 
+E69000003,Cambridgeshire and Peterborough 
+E69000004,Cheshire and Warrington 
+E69000005,Cornwall and the Isles of Scilly 
+E69000006,Cumbria 
+E69000007,Derbyshire and Nottinghamshire 
+E69000008,Dorset 
+E69000009,Enterprise M3 
+E69000010,"Essex, Southend-on-Sea and Thurrock "
+E69000011,G First (Gloucestershire) 
+E69000012,Greater Lincolnshire 
+E69000013,Greater London 
+E69000014,Greater Manchester 
+E69000015,Heart of the South-West 
+E69000016,Hertfordshire 
+E69000017,Hull and East Yorkshire 
+E69000018,Kent and Medway 
+E69000019,Lancashire 
+E69000020,Leicester and Leicestershire 
+E69000021,Liverpool City Region 
+E69000022,New Anglia 
+E69000023,North East 
+E69000024,North of Tyne 
+E69000025,Oxfordshire 
+E69000026,Solent 
+E69000027,South-East Midlands 
+E69000028,South Yorkshire 
+E69000029,Stoke-on-Trent and Staffordshire 
+E69000030,Swindon and Wiltshire 
+E69000031,Tees Valley 
+E69000032,Thames Valley Berkshire 
+E69000033,The Marches 
+E69000034,West Midlands and Warwickshire 
+E69000035,Worcestershire 
+E69000036,West of England and North Somerset 
+E69000037,West Yorkshire 
+E69000038,York and North Yorkshire 

global.R

@@ -19,7 +19,7 @@ shhh(library(shinyjs))
 shhh(library(tools))
 shhh(library(readr))
 shhh(library(testthat))
-shhh(library(shinytest))
+# shhh(library(shinytest))
 shhh(library(styler))
 shhh(library(tidyr))
 shhh(library(ggplot2))
@@ -29,7 +29,7 @@ shhh(library(shinyWidgets))
 shhh(library(shinycssloaders))
 shhh(library(sparkline))
 shhh(library(config))
-shhh(library(rsconnect))
+# shhh(library(rsconnect))
 shhh(library(shinyalert))
 shhh(library(shinydisconnect))