Converts long country names into one of many different coding schemes. Translates from one scheme to another. Converts country name or coding scheme to the official short English country name. Creates a new variable with the name of the continent or region to which each country belongs.
countrycode( sourcevar, origin, destination, warn = TRUE, nomatch = NA, custom_dict = NULL, custom_match = NULL, origin_regex = FALSE )
Vector which contains the codes or country names to be converted (character or factor)
Coding scheme of origin (string such as "iso3c" enclosed in quotes ""): type "?codelist" for a list of available codes.
Coding scheme of destination (string such as "iso3c" enclosed in quotes ""): type `?codelist` for a list of available codes.
Prints unique elements from sourcevar for which no match was found
When countrycode fails to find a match for the code of origin, it fills-in the destination vector with nomatch. The default behavior is to fill non-matching codes with NA. If nomatch = NULL, countrycode tries to use the origin vector to fill-in missing values in the destination vector. nomatch must be either NULL, of length 1, or of the same length as sourcevar.
A data frame which supplies a new dictionary to replace the built-in country code dictionary. Each column contains a different code and must include no duplicates. The data frame format should resemble `countrycode::codelist`. Warning: when `custom_dict` is used, no sanity checks are conducted.
A named vector which supplies custom origin and destination matches that will supercede any matching default result. The name of each element will be used as the origin code, and the value of each element will be used as the destination code.
Logical: When using a custom dictionary, if TRUE then the origin codes will be matched as regex, if FALSE they will be matched exactly. When using the default dictionary (dictionary = NULL), origin_regex will be ignored.
For a complete description of available country codes and languages,
please read the documentation for the
Panel data (i.e., country-year) can pose particular problems when converting codes. For instance, some countries like Vietnam or Serbia go through political transitions that justify changing codes over time. This can pose problems when using codes from organizations like CoW or Polity IV, which produce codes in country-year format. Instead of converting codes using the `countrycode` function, we recommend that users use the ``countrycode::codelist_panel`` data.frame as a base into which they can merge their other data. This data.frame includes most relevant code, and is already "reconciled" to ensure that each political unit is only represented by one row in any given year. From there, it is just a matter of using `R`'s `merge` function to combine different datasets which use different codes.