Coverage / missingness audit

What is missing, before you trust the map: which countries are unmatched, the NA rate per indicator, and which World Bank regions / income groups are under-covered – so a half-empty map is caught before it is published.

Usage

audit_coverage(data, indicator = NULL, by = c("region", "income", "continent"))

Arguments

data

A country-level (or map-ready) data frame.

indicator

Optional character vector of value columns to report NA rates for. If NULL, all numeric columns are used.

by

Grouping for the coverage breakdown: "region" (default), "income" or "continent".

Value

A list with elements unmatched, na_rates and by_group.

Examples

audit_coverage(countryatlas::world_snapshot$countries)
#> 
#> ── Coverage audit ──────────────────────────────────────────────────────────────
#> ✔ All countries matched to an ISO code.
#> 
#> ── Missingness by indicator ──
#> 
#> # A tibble: 4 × 4
#>   indicator           n n_missing na_rate
#>   <chr>           <int>     <int>   <dbl>
#> 1 gdp_per_capita    215         9  0.0419
#> 2 population        215         0  0     
#> 3 life_expectancy   215         0  0     
#> 4 co2_per_capita    215        12  0.0558
#> ── Coverage by group ──
#> 
#> # A tibble: 8 × 3
#>   region                     n_countries na_rate
#>   <chr>                            <int>   <dbl>
#> 1 East Asia & Pacific                 37  0.0541
#> 2 Latin America & Caribbean           41  0.0488
#> 3 Middle East & North Africa          21  0.0476
#> 4 Sub-Saharan Africa                  48  0.0417
#> 5 Europe & Central Asia               56  0.0357
#> 6 North America                        3  0     
#> 7 South Asia                           8  0     
#> 8 NA                                   1  0