R script that uses Lattice to plot a Choropleth map.

density.R

#!/usr/bin/Rscript --vanilla

library(sp)
#library(RColorBrewer)

colorPalette <- colorRampPalette(c("white", "orange"))(32)

spain <- readRDS("ESP_adm1.rds")

# Datos de Informe Anual del Sector TIC y de los Contenidos en España 2016. ONTSI
data = read.table(text="
      'Comunidad' 'density' 'population'
      'Andalucía' 96 8409657
      'Aragón' 28 1317076
      'Cantabria' 109 581477
      'Castilla-La Mancha' 26 2040379
      'Castilla y León' 26 2435797
      'Cataluña' 232 7441176
      'Ceuta y Melilla' 0 170000 
      'Comunidad de Madrid' 807 6475872
      'Comunidad Foral de Navarra' 62 640502
      'Comunidad Valenciana' 212 4934993
      'Extremadura' 26 1077715
      'Galicia' 92 2710607
      'Islas Baleares' 231 1150839 
      'Islas Canarias' 289 2154905
      'La Rioja' 62 312647
      'País Vasco' 300 2167707
      'Principado de Asturias' 98 1034449
      'Región de Murcia' 130 1472949", header=TRUE)

spain$density = as.numeric(data$density)
spain$population = as.numeric(data$population)

# Change these parameters
scale.parameter = 0.65  # scaling paramter. less than 1 is zooming in, more than 1 zooming out. 
xshift = 4.5  # Shift to right in map units. 
yshift = 4  # Shift to left in map units. 
original.bbox = spain@bbox  # Pass bbox of your Spatial* Object. 

# Just copy-paste the following
edges = original.bbox

edges[1, ] <- (edges[1, ] - mean(edges[1, ])) * scale.parameter + mean(edges[1,]) + xshift
edges[2, ] <- (edges[2, ] - mean(edges[2, ])) * scale.parameter + mean(edges[2,]) + yshift
###

spplot(spain, "density", col.regions = colorPalette, col = "black", 
       xlim = edges[1, ], ylim = edges[2, ],
       main="Densidad de población por comunidad autónoma")