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########################
### SAS Proc Freq ###
########################
#' @title SAS proc freq in R
#'
#' @description This function permits to reproduce the output of the SAS proc freq
#'
#' @param variable vector on which we want to apply the function.
#' @param digits integer that specifies the number of decimals we want to keep in the rounded figures.
#' @return a R data frame of dimension [number of categories x 5].
#' The five columns display the following information:
#' \itemize{
#' \item Category: different categories of the original categorical variable
#' \item Frequency
#' \item Percentage
#' \item Cumulative.Frequency
#' \item Cumulative.Percentage
#' }
#' @author Simon CORDE
#' @keywords proc_freq frequency table categorical variable SAS
#' @references Link to the author's github package repository:
#' \url{https://github.com/Redcart/helda}
#' @export proc_freq
#' @examples
#' data <- iris
#' str(data)
#' result <- proc_freq(data$Species)
#' result
proc_freq <- function(variable, digits = 4)
{
categories <- names(sort(table(variable)))
frequencies <- as.vector(sort(table(variable)))
n <- sum(frequencies)
percentages <- round(frequencies / n, digits)*100
cum_frequencies <- cumsum(frequencies)
cum_percentages <- cumsum(percentages)
result <- data.frame("Category" = categories,
"Frequency" = frequencies,
"Percentage" = percentages,
"Cumulative.Frequency" = cum_frequencies,
"Cumulative.Percentage" = cum_percentages,
stringsAsFactors = TRUE)
return(result)
}
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