ISO Country Codes

library(tidyverse) # ggplot, lubridate, dplyr, stringr, readr...
library(plotly)
library(praise)

The Data

We’ve referenced countries and country codes in many past datasets, but we’ve never looked closely at the ISO 3166 standard that defines these codes.

Wikipedia says:

ISO 3166 is a standard published by the International Organization for Standardization (ISO) that defines codes for the names of countries, dependent territories, special areas of geographical interest, and their principal subdivisions (e.g., provinces or states). The official name of the standard is Codes for the representation of names of countries and their subdivisions.

The dataset this week comes from the {ISOcodes} R package. It consists of three tables:

• countries: Country codes from ISO 3166-1.
• country_subdivisions: Country subdivision code from ISO 3166-2.
• former_countries: Code for formerly used names of countries from ISO 3166-3.

countries <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2024/2024-11-12/countries.csv')
country_subdivisions <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2024/2024-11-12/country_subdivisions.csv')
former_countries <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2024/2024-11-12/former_countries.csv')

former <- former_countries |> 
  mutate(date = case_when(
    nchar(date_withdrawn) == 4 ~ ymd(paste0(date_withdrawn, "-01-01")),
    TRUE ~ ymd(date_withdrawn)
  )) |> 
  mutate(country = fct_reorder(alpha_3, date))

country_subdivisions |> 
  group_by(type) |> 
  summarize(count_type = n()) |> 
  arrange(desc(count_type))

# A tibble: 109 × 2
   type                    count_type
   <chr>                        <int>
 1 Province                      1181
 2 District                       646
 3 Municipality                   517
 4 Region                         474
 5 State                          279
 6 Department                     221
 7 County                         209
 8 Governorate                    148
 9 Prefecture                     108
10 Metropolitan department         95
# ℹ 99 more rows

p <- former |> 
  ggplot(aes(x = date, y = country)) + 
  geom_segment(aes(xend = min(date), yend = country)) + 
  geom_point(aes(
    text = paste("Country: ", name, "<br>Date: ", date_withdrawn,
                 "<br>Info: ", comment)), 
    size = 3) + 
  theme_minimal() +
  scale_y_discrete(limits=rev) + 
  labs(title = "Date of Country Withdrawn",
       y = "", x = "Date")

ggplotly(p, tooltip = "text")

Thirty-one countries have been withdrawn from the ISO 3166 standard in recent years. Hover on the dot to see the name of the country and the year they were withdrawn.