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Using the CountryCodes database and sf package

Vignette of the CountryCodes project

This vignette shows how to use the database provided in the GitHub project Country Codes and International Organizations & Groups with the sf package in R.

Required R packages

library(sf)
library(jsonlite)
library(rnaturalearth)
library(dplyr)

Reading the data

The first step is to read the provided database (in this example, the json file) and extract one international organization. In this example, we will plot the Commonwealth of Nations.

df <- fromJSON("https://raw.githubusercontent.com/dieghernan/Country-Codes-and-International-Organizations/master/outputs/Countrycodesfull.json")
# Identify Commonwealth acronym
orgsdb <- read.csv("https://raw.githubusercontent.com/dieghernan/Country-Codes-and-International-Organizations/master/outputs/CountrycodesOrgs.csv") %>%
  distinct(org_id, org_name)

kable(orgsdb[grep("Common", orgsdb$org_name), ], format = "markdown")
  org_name org_id
25 Commonwealth C
26 Central American Common Market CACM
30 Caribbean Community and Common Market CARICOM
42 Commonwealth of Independent States CIS
43 Common Market for Eastern and Southern Africa COMESA
115 Southern Cone Common Market MERCOSUR

In our case, the value to search is C. A function that extracts the membership from the json database is also provided:

ISO_memcol <- function(df,
                       orgtosearch) {
  ind <- match(orgtosearch, unlist(df[1, "org_id"]))
  or <- lapply(1:nrow(df), function(x) {
    unlist(df[x, "org_member"])[ind]
  })
  or <- data.frame(matrix(unlist(or)), stringsAsFactors = F)
  names(or) <- orgtosearch
  df2 <- as.data.frame(cbind(df, or, stringsAsFactors = F))
  return(df2)
}
df_org <- ISO_memcol(df, "C")

Now df_org has a new column, named C, containing the membership status of each country.

df_org %>%
  count(C) %>%
  kable(format = "markdown")
C n
member 53
NA 222 
df_org %>%
  filter(!is.na(C)) %>%
  select(
    ISO_3166_3,
    NAME.EN,
    C
  ) %>%
  head() %>%
  kable(format = "markdown")
ISO_3166_3 NAME.EN C
ATG Antigua & Barbuda member
AUS Australia member
BHS Bahamas member
BGD Bangladesh member
BRB Barbados member
BLZ Belize member

Replacing the data on a map

In this example the rnaturalearth package is used for retrieving an sf object. The code below replaces the data.frame part of the sf object with the dedicated database.

testmap <- ne_countries(50,
  "countries",
  returnclass = "sf"
) %>%
  select(ISO_3166_3 = adm0_a3) %>%
  full_join(df_org)

# We also add tiny countries
tiny <- ne_countries(50,
  "tiny_countries",
  returnclass = "sf"
) %>%
  select(ISO_3166_3 = adm0_a3) %>%
  full_join(df_org)

# Identify dependencies
ISOCommon <- df_org %>%
  filter(!is.na(C)) %>%
  select(
    ISO_3166_3.sov = ISO_3166_3,
    C_sov = C
  )
tiny <- left_join(tiny, ISOCommon)
tiny$C <- coalesce(tiny$C, tiny$C_sov)

Plotting map: Wikipedia style

Now we will try to plot a map resembling the one presented in the Wikipedia page for the Commonwealth.

Wiki

The map we will generate is presented in a Robinson projection, and the color palette will be based on the Wikipedia convention for Orthographic Maps, since it is the one used in the example.

# Projecting the map
testmap_rob <- st_transform(testmap, "+proj=robin")
tiny_rob <- st_transform(tiny, "+proj=robin")

# Bounding box
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")

# Plotting
par(mar = c(0, 0, 0, 0), bg = NA)
plot(bbox,
  col = "#FFFFFF",
  border = "#AAAAAA",
  lwd = 1.5
)
plot(
  st_geometry(testmap_rob),
  col = "#B9B9B9",
  border = "#FFFFFF",
  lwd = 0.1,
  add = T
)

plot(
  st_geometry(testmap_rob %>%
    filter(!is.na(C))),
  col = "#346733",
  border = "#FFFFFF",
  lwd = 0.1,
  add = T
)

# Finally, add tiny countries
# All
plot(
  st_geometry(tiny_rob),
  col = "#000000",
  bg = "#B9B9B9",
  add = T,
  pch = 21
)
# Dependencies
plot(
  st_geometry(tiny_rob %>%
    filter(!is.na(C)) %>%
    filter(!is.na(ISO_3166_3.sov))),
  bg = "#C6DEBD",
  col = "#000000",
  pch = 21,
  add = T
)
# Independent
plot(
  st_geometry(tiny_rob %>%
    filter(!is.na(C)) %>%
    filter(is.na(ISO_3166_3.sov))),
  bg = "#346733",
  col = "#000000",
  pch = 21,
  add = T
)
plot(bbox,
  col = NA,
  border = "#AAAAAA",
  lwd = 1.5,
  add = T
)

plot of chunk 20190427_mapfin

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