more_mapping2.R

library(rgdal)
library(broom)
library(dplyr)

lad_2016_sg <- readOGR(paste0("data/Local_Authority_Districts_December_2016_Super_Generalised_",
                              "Clipped_Boundaries_in_Great_Britain/Local_Authority_Districts_",
                              "December_2016_Super_Generalised_Clipped_Boundaries_in_Great_",
                              "Britain.shp"))

lad_2016_sg <- spTransform(lad_2016_sg, CRS("+init=epsg:4326"))
lad_2016_sg@data$id <- rownames(lad_2016_sg@data)
lad_2016_sg_ <- tidy(lad_2016_sg)

lad_2016_sg <- lad_2016_sg@data %>%
  transmute(id = id,
            lad16cd = as.character(lad16cd),
            lad16nm = as.character(lad16nm)) %>%
  inner_join(lad_2016_sg_, by = "id")

lad_2016_sg <- readOGR(paste0("data/Local_Authority_Districts_December_2016_Super_Generalised_",
                              "Clipped_Boundaries_in_Great_Britain/Local_Authority_Districts_",
                              "December_2016_Super_Generalised_Clipped_Boundaries_in_Great_",
                              "Britain.shp"))

lad_2016_sg <- spTransform(lad_2016_sg, CRS("+init=epsg:4326"))
lad_2016_sg@data$id <- rownames(lad_2016_sg@data)
lad_2016_sg_ <- tidy(lad_2016_sg)

lad_2016_sg <- lad_2016_sg@data %>%
  transmute(id = id,
            lad16cd = as.character(lad16cd),
            lad16nm = as.character(lad16nm)) %>%
  inner_join(lad_2016_sg_, by = "id")

la_to_ctry_2016 <- read.csv("data/Local_Authority_District_to_Country_December_2016_Lookup_in_the_United_Kingdom.csv", 
                            stringsAsFactors = FALSE)

devtools::use_data(la_to_ctry_2016)

test <- inner_join(lad_2016_sg, la_to_ctry_2016, by = "lad16cd")
test <- test %>% filter(ctry16nm %in% c("England", "Wales"))
ggplot(test, aes(long, lat)) + geom_polygon(aes(group = group), color = "white", size = 0.2) + coord_quickmap()