epiCleanr (version 0.2.0)

clean_admin_names: Clean and Match Administrative Names

Description

This function takes administrative names and cleans them using various matching and string distance algorithms. It can also match the cleaned names with a base list provided by the user or fetched from `GeoNames`, which is a official repository of standard spellings of all foreign geographic names.

Usage

clean_admin_names(
  admin_names_to_clean,
  country_code,
  admin_level = "adm2",
  user_base_admin_names = NULL,
  user_base_only = FALSE,
  report_mode = FALSE
)

Value

If `report_mode` is set to TRUE, a data frame containing the original admin names and the matched and cleaned admin names with inormation of the source of data used to clean including the algorithm used, else a cleaned list of names is returned.

Arguments

admin_names_to_clean

A character vector of administrative names to clean.

country_code

sed if `use_get_admin_names` is TRUE. A character string or numerical value of the country code (e.g., "KE"). This can be in various formats such as country name, ISO codes, UN codes, etc., see countrycode::codelist() for the full list of codes and naming conventions used.

admin_level

A character string indicating the administrative level (e.g., "adm2").

user_base_admin_names

A character of of administrative names that the use would like to use as reference. This is no necessary, downloaded `GeoNames` will be used if missing.

user_base_only

A logical indicating whether to use only the user-provided base administrative names (`user_base_admin_names`) for matching. If TRUE, `country_code` and `admin_names_to_clean` are not required. Default is FALSE.

report_mode

A logical indicating whether to return a detailed report. Default is FALSE.

See Also

countrycode::codelist() for the full list of codes and naming conventions.

Examples

 # \donttest{
# Example with country code
base_names <- c(
  "Paris", "Marseille", "Lyon",
  "Toulouse", "Nice", "Nantes", "Strasbourg",
  "Montpellier", "Bordeaux", "Lille"
)

unclean_names <- c(
  "Pariis", "Marseill", "Lyone",
  "Toulous", "Niice", "Nantees", "Strasbourgh",
  "Montpeelier", "Bordeuax", "Lilie"
)

france_new <- clean_admin_names(
  country_code = "Fr",
  user_base_admin_names = base_names,
  admin_names_to_clean = unclean_names
)

print(france_new)
# }