#' Get full county name
#'
#' This looks at the county code and returns a new column \emph{countyname} of
#' the full county name. Old db, the CNTYCODE is already the full county name.
#' @importFrom stats setNames
#' @param any_df person, crash, or vehicle dataframe
#' @param county_col column that has the county code
#' @param combine_with_old If TRUE, will bring full county name to \emph{countyname}
#'
#' @return A new column called \emph{countyname}
#' @export
#'
#' @examples
#' \dontrun{county_rename(vehicle17)}
county_rename <-
function(any_df,
county_col = "CNTYCODE",
combine_with_old = FALSE) {
if (county_col == "CNTYCODE") {
any_df <-
any_df |> dplyr::mutate(CNTYCODE = as.character(.data[["CNTYCODE"]]))
}
if (combine_with_old == TRUE){
any_df <- dplyr::left_join(any_df, lookup_countycode, by = setNames(nm = county_col, "ctycode"))
dplyr::mutate(any_df, countyname = ifelse(lubridate::year(.data[["CRSHDATE"]]) < 2017,.data[[county_col]], .data[["countyname"]]))
} else {
dplyr::left_join(any_df, lookup_countycode, by = setNames(nm = county_col, "ctycode"))
}
}
#' Find county code and fips
#'
#' @param county_to_find full name of county(ies)
#'
#' @return tibble with county code and fips
#' @export
#'
#' @examples
#' find_countycode_fips("Dane")
find_countycode_fips <- function(county_to_find){
lookup_countycode_and_fips |> dplyr::filter(.data[["countyname"]] %in% county_to_find)
}
#' Find municode by municipality
#'
#' @param municipality_to_find name of municipality (i.e. "Adams")
#' @param ctv c("City", "Town", "Village")
#'
#' @return df with municode and county code
#' @export
#'
#' @examples
#' data(muni)
#' find_municipality_codes("Adams", "Town")
find_municipality_codes <- function(municipality_to_find, ctv){
# data("muni", envir=environment()) #importFrom utils data
get("muni")
muni |> dplyr::filter(.data[["Municipality"]] %in% municipality_to_find, .data[["MuniTownype"]] %in% ctv)
}
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