#' Rural-Urban Commuting Area Codes
#'
#' Given a postal code, will determine the urbanicity of that region based upon
#' Rural Health Research Center's Rural-Urban Commuting Area Codes (RUCAs).
#'
#' @name ruca-package
#' @aliases ruca
#' @docType package
#' @title Rural-Urban Commuting Area Codes
#' @author \email{jason@@bryer.org}
#' @keywords package urbanization ruca
NULL
#' RUCA classifications.
#'
#' Data frame containing the RUCA classifications.
#'
#' @name classifications
#' @docType data
#' @format a data frame 34 observations of 7 variables.
#' @source Rural Health Research Center
#' @keywords datasets
NULL
#' Mappings of zip codes to RUCA codes.
#'
#' This data frames provides a mapping between zip codes and RUCA codes.
#'
#' @name classifications
#' @docType data
#' @format a data frame 41,901 observations of 3 variables.
#' @source Rural Health Research Center
#' @keywords datasets
NULL
#' Return RUCA codes for the given zip codes.
#'
#' This function will return the Rural-Ruban Commuting Area Codes (RUCAs) based on the given
#' vector of postal codes. See the contents of \code{data(classifications)} for all the possible
#' rural-urban classifications available.
#'
#' @param df data frame
#' @param zipCol name of the zip code column.
#' @export
getruca <- function(df, zipCol) {
data(ruca)
data(classifications)
ruca$zip = as.character(ruca$zip)
while(nrow(ruca[which(nchar(ruca$zip) < 5),]) > 0) {
ruca[which(nchar(ruca$zip) < 5),'zip'] = paste('0', ruca[which(nchar(ruca$zip) < 5),'zip'], sep='')
}
ans = merge(df, ruca, by.x=zipCol, by.y='zip', all.x=TRUE, sort=FALSE)
ans = merge(ans, classifications, by='ruca', all.x=TRUE, sort=FALSE)
ans$state = NULL
ans
}
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