Invisible link to canonical for Microformats

Wikipedia Maps (I): Organ donor rates

A choropleth map with R

This is a quick post on how to create a map as per the Wikipedia conventions. In this case I have chosen to plot the international organ donor rates, retrieved on 2019-02-10 although the data refers to 2017 (Source: IRODaT).

Webscrapping

First step is to webscrap Wikipedia in order to get the final table. For doing so, I will use the rvest library. You can get the xpath you want to webscrap as explained here.

library(rvest)
library(dplyr)

Base <-
  read_html("https://en.wikipedia.org/wiki/International_organ_donor_rates") %>%
  html_nodes(xpath = '//*[@id="mw-content-text"]/div/table[3]') %>%
  html_table() %>%
  as.data.frame(
    stringsAsFactors = F,
    fix.empty.names = F
  ) %>%
  select(Country,
    RateDonperMill = Number.of.deceased.donors..per.million.of.population
  )

knitr::kable(head(Base, 10), format = "markdown")
Country RateDonperMill
Argentina 19.60
Armenia 0.00
Australia 21.60
Austria 23.88
Azerbaijan 0.00
Bahrain 4.00
Bangladesh 0.00
Belarus 26.20
Belgium 30.30
Bolivia 0.36

Now we need to choose a good source of maps:

library(sf)
library(giscoR)

# Map import from Eurostat
WorldMap <- gisco_get_countries(resolution = 3, epsg = 3857) %>%
  select(ISO_3166_3 = ISO3_CODE)

Merging all together

Now let’s join and have a look to see what is going on. We use the countrycode package to retrieve the ISO3 codes of our scrapped dataset:

library(countrycode)

Base$ISO_3166_3 <- countrycode(Base$Country, origin = "country.name", destination = "iso3c")


DonorRate <- left_join(
  WorldMap,
  Base
) %>%
  select(
    Country,
    ISO_3166_3,
    RateDonperMill
  )

Make the .svg file

As already explained, I would like to follow the Wikipedia conventions, so some things to bear in mind:

  • Obviously the colors. Wikipedia already provides a good guidance for this. I would make use of the RColorBrewer library, which implements ColorBrewer in R.
  • In terms of projection, Wikipedia recommends the Equirectangular projection but, as in their own sample of a gradient map, I would choose to use the Robinson projection.
  • I should produce an .svg file following also the naming convention.

Some libraries then to use: RColorBrewer, rsvg and specially one of my favourites, cartography:

library(RColorBrewer)
library(cartography)
library(rsvg)

# Create bbox of the world
bbox <- st_linestring(rbind(
  c(-180, 90),
  c(180, 90),
  c(180, -90),
  c(-180, -90),
  c(-180, 90)
)) %>%
  st_segmentize(5) %>%
  st_cast("POLYGON") %>%
  st_sfc(crs = 4326) %>%
  st_transform(crs = "+proj=robin")

# Create SVG
svg(
  "Organ donor rate per million by country gradient map (2017).svg",
  pointsize = 90,
  width =  1600 / 90,
  height = 728 / 90
)

par(mar = c(0.5, 0, 0, 0))
choroLayer(
  DonorRate %>% st_transform("+proj=robin"),
  var = "RateDonperMill",
  breaks = c(0, 5, 10, 20, 30, 40, 50),
  col = brewer.pal(6, "PuBu"),
  border = "#646464",
  lwd = 0.1,
  colNA = "#E0E0E0",
  legend.pos = "left",
  legend.title.txt = "",
  legend.values.cex = 0.25
)

# Bounding box
plot(bbox,
  add = T,
  border = "#646464",
  lwd = 0.2
)

dev.off()

And that’s all. Our .svg file is ready to be included in Wikipedia.

img

Update: The map is already part of the Wikipedia article.

Related