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#' Retreive Wage Decomposition
#'
#' Wage inequality data shows the overall wage inequality and the within-group and
#' between-group wage inequality over time. These measures allow an examination of how
#' much of the change in overall wage inequality in particular periods was due to changes
#' in within-group and between-group wage inequality.
#'
#' Population sample: Wage and salary workers age 18–64
#'
#' @param by \code{NULL} or character string of \code{g} (Gender)
#' @return \code{tbl_df} with data filtered by the selected criteria.
#' @references \href{https://www.epi.org/data/}{Economic Policy Institute Data Library}
#' @note Data source: CPS ORG
#' @return data frame
#' @export
#' @examples
#' get_wages_by_percentile()
#'
#' get_wages_by_percentile("g")
get_wage_decomposition <- function(by=NULL) {
params <- list(subject="wageineq")
if (!is.null(by)) {
params <- make_params(params, by, "g")
}
res <- epi_query(params)
if (is.null(res)) return(data.frame())
cols <- stringi::stri_trans_tolower(res$columns$name)
cols <- stringi::stri_replace_all_regex(cols, "[\\('\\)]", "")
cols <- stringi::stri_replace_all_regex(cols, "[[:space:]" %s+%
rawToChar(as.raw(c(0xe2, 0x80, 0x93))) %s+% "-]+",
"_")
out <- setNames(as_data_frame(res$data), cols)
out <- dplyr::mutate_all(out, "clean_cols")
out <- suppressMessages(readr::type_convert(out))
show_citation(res)
out
}
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