#' Given a dictionary of categories, this function will create a "category" column in the data frame,
#' which enables users color the forest plot not only by its variable name but also pre-defined categories
#'
#' @param df A dataframe containing model results
#' @param x A named list
#'
#' @return A dataframe
#' @export
#'
#' @examples
#' df <- data.frame(variable = 1:12, label = c(rep("RACE",4),rep("FAMINC",5),rep("SEX",2),"COVERAGE"))
#' x <- list(SocioDemographics = c("SEX", "FAMINC"), "Health Care" = c("COVERAGE"), Race = c("RACE"))
#'
#' map_categories(df, x)
map_categories <- function(df, x){
cat <- c()
lab <- c()
for(category in names(x)){
labels <- x[[category]]
cat <- c(cat, rep(category, length(labels)))
lab <- c(lab, labels)
}
dplyr::mutate(df,
category = as.character(.data$label),
category = plyr::mapvalues(category, from=lab, to=cat),
category = factor(category, levels = names(x))
)
}
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