whoville

The goal of whoville is to provide a package country reference data
published by the World Health Organization, United Nations and World
Bank easily accessible in R. At the moment, this is a reference dataset
and set of functions to work with country codes and names, allowing easy
conversion between names and codes as well as easy access to region
codes, WHO member status, and other published country metadata. This is
used to assist the work of the WHO’s Division of Data, Analytics, and
Delivery for Impact’s Global Programme of Work 13.

Functions

Some functions are built to help you turn names or country codes into
ISO3 codes:

• names_to_code() is the workhorse function that helps match country
  names and returns standardized country codes.
• names_to_iso3() is a wrapper around names_to_code() that
  automatically outputs ISO3 code.
• codes_to_iso3() converts other country codes into ISO3 format.
• valid_codes() lets you quickly check which country codes in a
  vector are recognized by the whoville package.

Other functions encourage a tidy R workflow where ISO3 codes are used as
the unique identifier for each country:

• iso3_to_regions() takes in a vector of ISO3 codes and returns
  specified region values.
• iso3_to_codes() takes in a vector of ISO3 codes and returns
  specified country codes.
• iso3_to_names() takes in a vector of ISO3 codes and returns
  specified country names.
• is_who_member() takes in a vector of ISO3 codes and checks if they
  are a WHO member state or not.
• is_oecd_member() takes in a vector of ISO3 codes and checks if
  they are an OECD member state or not.
• is_gbd_high_income() takes in a vector of ISO3 codes and checks if
  they are classified as high-income in the 2019 GBD from IHME.

All of these functions are built on top of the countries data frame
also exported with the package and developed off of public datasets
provided by the World Health Organization and United Nations. Details
available through ?countries.

Installation

You can install whoville from Github with:

devtools::install_github("gpw13/whoville")

Usage

If we have an unclean data frame with country names, we can use
names_to_codes() to match these to ISO3 codes. The function matches
the names vector across all possible names found in the countries data
frame. ISO3 codes for exact matches are always returned, but the user
has specific options for non-exact matches. They can be fuzzy matched
(the default), always made NA, or require user input to confirm fuzzy
matching results. Fuzzy matches always return a message to the user on
the confirmed match. More details available through ?names_to_codes.

library(whoville)

names_to_code(c("Venezuela", "Arentina", "afghanist"))
#> 'arentina' has no exact match. Closest name found was 'argentina'.
#> 'afghanist' has no exact match. Closest name found was 'afghanistan'.
#> [1] "VEN" "ARG" "AFG"

Since these functions are vectorized, we can easily use them in a normal
workflow, especially if we’re using the tidyverse. Below, we can clean
up our tidy names and get the correct UN region and income group for our
countries, as well as its name in Chinese:

library(dplyr)
df <- data.frame(c_names = c("Venezuela", "Arentina", "afghanist"))

df %>%
  mutate(iso3 = names_to_code(c_names),
         un_region = iso3_to_regions(iso3, region = "un_region"),
         wb_ig = iso3_to_regions(iso3, region = "wb_ig"),
         name_zh = iso3_to_names(iso3, org = "un", language = "zh"))
#>     c_names iso3 un_region wb_ig                name_zh
#> 1 Venezuela  VEN        19   UMC 委内瑞拉玻利瓦尔共和国
#> 2  Arentina  ARG        19   UMC                 阿根廷
#> 3 afghanist  AFG       142   LIC                 阿富汗