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. na_rates covers every one of them; the by_group breakdown is computed for a single indicator – the first – and names it in an indicator column so it cannot be mistaken for the group's overall coverage.

by

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

Value

A list of class countryatlas_coverage, with elements unmatched, na_rates and by_group. It has a print() method, so at the console you see a formatted report rather than the raw list; reach into the elements by name to use the numbers programmatically.

• unmatched – one row per input value that did not resolve to an ISO code. Empty is the good case.

• na_rates – one row per indicator: n is the number of countries considered, n_missing how many of them lack a value, and na_rate is n_missing / n.

• by_group – one row per group: n_countries is how many countries are in that group, and na_rate is the share of those lacking a value. The counts sum to n.

Both n and by_group's n_countries are denominators – everything counted, not everything present. That is the opposite orientation from map_provenance(), whose n_countries is the numerator (countries drawn with a value) and whose n_total is the denominator. The two verbs report the same coverage from opposite ends, so on 215 countries with 24 missing this gives n = 215 where map_provenance() gives n_countries = 191.

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        24  0.112 
#> 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 × 4
#>   region                     n_countries indicator      na_rate
#>   <chr>                            <int> <chr>            <dbl>
#> 1 South Asia                           8 gdp_per_capita  0.25  
#> 2 East Asia & Pacific                 37 gdp_per_capita  0.216 
#> 3 Middle East & North Africa          21 gdp_per_capita  0.143 
#> 4 Latin America & Caribbean           41 gdp_per_capita  0.0976
#> 5 Europe & Central Asia               56 gdp_per_capita  0.0893
#> 6 Sub-Saharan Africa                  48 gdp_per_capita  0.0417
#> 7 North America                        3 gdp_per_capita  0     
#> 8 NA                                   1 gdp_per_capita  0