Selected World Development Indicators for 2022

A fixed snapshot of selected economic, demographic, and labour-market indicators for 181 countries, together with World Bank regional, income, and lending classifications. It provides a compact mixed-type dataset for illustrating distance construction and distance-based learning.

Format

A data frame with 181 rows and 9 variables:

country: Country or economy name.
region: World Bank region, as a factor with 7 levels.
income: World Bank income group, as a factor with 5 levels.
lending: World Bank lending category, as a factor with 4 levels.
gdp_pc_kusd: GDP per capita in thousands of current US dollars.
life_exp: Life expectancy at birth, in years.
unemployment: Unemployment as a percentage of the total labour force, based on the modelled ILO estimate.
urban_pop: Urban population as a percentage of the total population.
pop_growth: Annual population growth, in percent.

Source

The World Bank, World Development Indicators, https://datacatalog.worldbank.org/search/dataset/0037712/world-development-indicators.

Details

The reference year is 2022 and the snapshot was retrieved from the World Bank Indicators API on 2026-05-05. Aggregate regions and observations with missing values in any selected field were removed. GDP per capita was divided by 1,000 and rounded to one decimal place; life expectancy, unemployment, and urban population were rounded to one decimal place; and population growth was rounded to two decimal places.

The numerical indicators and their World Bank codes are:

GDP per capita: NY.GDP.PCAP.CD;
life expectancy: SP.DYN.LE00.IN;
unemployment: SL.UEM.TOTL.ZS;
urban population: SP.URB.TOTL.IN.ZS;
population growth: SP.POP.GROW.

License

The original World Development Indicators data are distributed by the World Bank under the Creative Commons Attribution 4.0 International license, subject to the World Bank Dataset Terms. Attribution: The World Bank: World Development Indicators.

References

World Bank Dataset Terms, https://www.worldbank.org/ext/en/legal/terms-conditions/datasets.

Examples

data("wdi_2022", package = "manydist")
dplyr::glimpse(wdi_2022)
#> Rows: 181
#> Columns: 9
#> $ country      <chr> "Afghanistan", "Albania", "Algeria", "Angola", "Argentina…
#> $ region       <fct> "Middle East, North Africa, Afghanistan & Pakistan", "Eur…
#> $ income       <fct> Low income, Upper middle income, Upper middle income, Low…
#> $ lending      <fct> IDA, IBRD, IBRD, IBRD, IBRD, IBRD, Not classified, Not cl…
#> $ gdp_pc_kusd  <dbl> 0.4, 7.8, 5.0, 3.7, 14.0, 6.6, 65.2, 52.3, 7.8, 35.0, 30.…
#> $ life_exp     <dbl> 65.6, 78.8, 76.1, 64.2, 75.8, 74.8, 83.2, 81.3, 74.1, 74.…
#> $ unemployment <dbl> 14.1, 10.8, 12.4, 14.1, 6.8, 13.5, 3.7, 5.0, 5.7, 9.2, 1.…
#> $ urban_pop    <dbl> 25.4, 57.9, 74.2, 69.1, 92.1, 65.6, 87.3, 69.0, 58.4, 81.…
#> $ pop_growth   <dbl> 1.44, -1.54, 1.59, 3.14, 0.21, 0.23, 1.29, 0.96, 0.04, 0.…