choropleth_map.R

# A choropleth map displays divided geographical areas or regions that are coloured in relation to a numeric variable. 
# It allows to study how a variable evolutes along a territory. However, its downside is that regions with bigger sizes 
# tend to have a bigger weight in the map interpretation, which includes a bias.

#plot(spdf)

# I need to fortify the data AND keep trace of the commune code! (Takes ~2 minutes)
library(broom)
spdf_fortified <- tidy(spdf, region = "code")
 
# Now I can plot this shape easily as described before:
library(ggplot2)
ggplot() +
  geom_polygon(data = spdf_fortified, aes( x = long, y = lat, group = group), fill="white", color="grey") +
  theme_void() +
  coord_map()
  
ggplot() +
  geom_polygon(data = spdf_fortified, aes(fill = nb_equip, x = long, y = lat, group = group)) +
  theme_void() +
  coord_map()
  
library(viridis)
ggplot() +
  geom_polygon(data = spdf_fortified, aes(fill = POP2005/1000000, x = long, y = lat, group = group) , size=0, alpha=0.9) +
  theme_void() +
  scale_fill_viridis(name="Population (M)", breaks=c(1,50,100, 140), guide = guide_legend( keyheight = unit(3, units = "mm"), keywidth=unit(12, units = "mm"), label.position = "bottom", title.position = 'top', nrow=1)) +
  labs( title = "Africa 2005 Population" ) +
  ylim(-35,35) +
  theme(
    text = element_text(color = "#22211d"), 
    plot.background = element_rect(fill = "#f5f5f4", color = NA), 
    panel.background = element_rect(fill = "#f5f5f4", color = NA), 
    legend.background = element_rect(fill = "#f5f5f4", color = NA),
    plot.title = element_text(size= 22, hjust=0.5, color = "#4e4d47", margin = margin(b = -0.1, t = 0.4, l = 2, unit = "cm")),
    legend.position = c(0.2, 0.26)
  ) +
  coord_map()