Using CountryCodes database and sf package

This vignette is an example of use of the database provided in the Github project Country Codes and International Organizations & Groups by using the sf package in R.

Required R packages

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

Reading the data

The first step consists on reading the database provided (in this example the json file) and extracting 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. It is provided also a function that extract the membership from the json database:

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 sfobject. and replacing the dataframefor the dedicated database.

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

# We add also 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 would try to plot a map resembling the one presented in the Wikipedia page for the Commonwealth.

Wiki

The map we will generate is presented under a Robinson projection and the color palette will be based in 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
)

# By last, 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