A toolset that allows you to easily import and tidy data sheets retrieved from Gapminder data web tools. It will therefore contribute to reduce the time used in data cleaning of Gapminder indicator data sheets as they are very messy.

Gapminder data, minus the mess.
Gapminder is a goldmine of global development data — life expectancy, income, CO₂ emissions, literacy rates, and hundreds more indicators spanning centuries. The catch? Every sheet looks like this:
life expectancy years | 1800 | 1801 | 1802 | ...
----------------------|------|------|------|----
Afghanistan | 28.2 | 28.2 | 28.2 | ...
Albania | 35.4 | 35.4 | 35.4 | ...
...
Countries as rows, years as columns, the indicator name hiding in cell A1. Great for a spreadsheet. Terrible for R.
tidygapminder fixes that in one function call.
# From CRAN
install.packages("tidygapminder")
# Development version
pak::pak("ebedthan/tidygapminder")
tidy_index(): one file at a timePoint it at a Gapminder .csv, .xlsx, or .xls file and get back a clean
tibble:
library(tidygapminder)
csv_path <- system.file("extdata/life_expectancy_years.csv", package = "tidygapminder")
tidy_index(csv_path)
Three columns: country, year, and the indicator, ready to filter, plot,
or model.
tidy_bunch(): a whole folder at onceDownloaded ten indicators? No problem. Point tidy_bunch() at the folder:
dir_path <- system.file("extdata", package = "tidygapminder")
# Returns a named list of tibbles, one per file
result <- tidy_bunch(dir_path)
names(result)
Want everything in one data frame joined by country and year?
tidy_bunch(dir_path, combine = TRUE)
readxl and tibble)vignette("tidygapminder")