Plot of Europe (choropleth) in R/ggplot, using NUTS data

europe_choropleth_ggplot.r

# install necessary packages
library(dplyr)
library(maptools)
library(ggplot2)
#library(ggmap)  # only for superimposing with Google maps
library(doBy)

# to make fortify possible without errors
library(gpclib)
gpclibPermit()

# requires downloading and unzipping NUTS_2013_01M_SH.zip from
# http://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units
eurMap <- readShapeSpatial("NUTS_2013_SHP/data/NUTS_RG_01M_2013.shp")

# only main adm level
eurMap <- subset(eurMap, nchar(as.character(NUTS_ID)) == 2)

# EL for Grece, UK for United Kingdom
eurMapDf <- fortify(eurMap, region='NUTS_ID')

# we assume two columns: CountryCode and NGA_Coverage
eurData <- read.csv("./NGA_coverage-ISO2.csv", stringsAsFactors = F)

# merge map and data
eurMapDataDf <- merge(eurMapDf, eurData, by.x="id", by.y="CountryCode")
# sort, so that polygons are drawn correctly
eurMapDataDf <- eurMapDataDf[order(eurMapDataDf$order),]

# limit data to main Europe
eurMapDataDf <- subset(eurMapDataDf, long > -15 & long < 32 & lat > 34 & lat < 75)

# add text; instead of mean I do middle (not to be to biased towards detailed coastlines)
middle = function (x) {
  (max(x) + min(x)) / 2
}  
txtVal <- summaryBy(long + lat + NGA_Coverage ~ id, data=eurMapDataDf, FUN=middle, keep.names=T)

# inverse order (to have visible borders)
p <- ggplot(data=eurMapDataDf) +
  geom_polygon(aes(x=long, y=lat, group=group, fill=NGA_Coverage)) +
  geom_path(aes(x=long, y=lat, group=group), color='black', alpha=.5) +
  geom_text(aes(x=long, y=lat, label=sprintf("%.0f%%", NGA_Coverage)), data=txtVal, col="gray", cex=3) +
  scale_fill_gradient2(low = "red", mid = "white", high = "blue") +
  theme_bw() +
  coord_equal()

ggsave("NGA_Coverage.png")

NGA_coverage-ISO2.csv

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