closest_countrycode.R

require(tidyverse)
require(countrycode)

closest_field = function(x){
  map_dbl(codelist, ~ 100 * sum(x %in% .x) / length(x)) %>% as.data.frame %>% 
    tibble::rownames_to_column() %>% `names<-`(c('field','pc_match')) %>% as_tibble() %>% 
    arrange(-pc_match)
}

closest_field(c('CM','AL','PA','MK','HA','CO','ZI','KU','TH','FI'))
#> # A tibble: 677 x 2
#>    field         pc_match
#>    <chr>            <dbl>
#>  1 fips               100
#>  2 ecb                 70
#>  3 eurostat            70
#>  4 genc2c              70
#>  5 iso2c               70
#>  6 wb_api2c            70
#>  7 cldr.name.as        70
#>  8 cldr.name.bem       70
#>  9 cldr.name.bo        70
#> 10 cldr.name.cu        70
#> # … with 667 more rows

closest_field(c('Ivory Coast','Guinea','Iran','Russia','North Korea'))
#> # A tibble: 677 x 2
#>    field           pc_match
#>    <chr>              <dbl>
#>  1 cow.name             100
#>  2 cldr.variant.en      100
#>  3 country.name.en       80
#>  4 eurostat.name         80
#>  5 p4.name               80
#>  6 wvs.name              80
#>  7 cldr.name.en          80
#>  8 cldr.name.nd          80
#>  9 cldr.name.sn          80
#> 10 cldr.short.en         80
#> # … with 667 more rows