Which indicators move together across countries? Computes pairwise
correlations between indicator columns (pairwise-complete, so patchy
coverage doesn't shrink every pair to the common subset), with the per-pair
n reported so a headline r computed on 12 countries can't masquerade as
a world fact.
Usage
correlate_indicators(data, ..., method = c("pearson", "spearman"), min_n = 3)Arguments
- data
A country-level (or map-ready) data frame; polygon frames are reduced to one row per country first.
- ...
<
tidy-select> Indicator columns to correlate. If empty, all numeric columns except coordinates,yearand other structural columns are used.- method
"pearson"(default) or"spearman".- min_n
Minimum number of complete pairs for a correlation to be reported (default
3).
Value
A tibble with one row per indicator pair: var_x, var_y, r,
n (complete pairs), sorted by |r| descending.
Examples
correlate_indicators(countryatlas::world_snapshot$countries)
#> # A tibble: 6 × 4
#> var_x var_y r n
#> <chr> <chr> <dbl> <int>
#> 1 gdp_per_capita life_expectancy 0.607 191
#> 2 gdp_per_capita co2_per_capita 0.435 184
#> 3 life_expectancy co2_per_capita 0.307 203
#> 4 gdp_per_capita population -0.0579 191
#> 5 population life_expectancy -0.0188 215
#> 6 population co2_per_capita 0.00660 203