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countryatlas

Country data from any source, joined on ISO codes and drawn as equal-area maps that state their coverage and source.

🔑 One key for every spelling, in a dozen languages:

library(countryatlas)
d <- data.frame(country = c("Cote d'Ivoire", "Korea, Rep.", "Deutschland", "U.K."))
standardize_country(d, country, add = "iso3c")
#> # A tibble: 4 × 2
#>   country       iso3c
#>   <chr>         <chr>
#> 1 Cote d'Ivoire CIV  
#> 2 Korea, Rep.   KOR  
#> 3 Deutschland   DEU  
#> 4 U.K.          GBR

🗺️ An equal-area map with its coverage and source in the caption:

world_map(attach_geometry(world_snapshot$countries), gdp_per_capita)

World map of GDP per capita in five quantile classes, Equal Earth projection, with a caption giving coverage and source.

🕰️ Memberships and income groups as of any date, row by row:

in_group(c("GBR", "GBR"), "EU", origin = "iso3c", as_of = c(2016, 2021))
#> [1]  TRUE FALSE
classify_countries(data.frame(iso3c = "VNM", year = c(2026, 2027)), "income")
#>   iso3c year              income
#> 1   VNM 2026 Lower middle income
#> 2   VNM 2027 Upper middle income

🚀 Setup

install.packages("countryatlas")
library(countryatlas): the bundled world_snapshot and every map work offline, in Equal Earth.
For the sf backend and every other projection: install.packages(c("sf", "rnaturalearth", "rnaturalearthdata"))
Live data: world_data(2020) from the World Bank, or any provider in country_sources() through fetch_indicator().

💡 To reproduce a figure exactly, pin the World Bank release: world_data(2020, vintage = "2024-07").
💡 Downloads are cached in tools::R_user_dir("countryatlas", "cache"); clear_country_cache() empties it.
💡 Fetching through a proxy: point CURL_CA_BUNDLE at your organisation’s certificate bundle.

📚 Learn more

The Gallery shows every map verb; the articles cover panels, tracing data to its source and honest maps.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.