R/model_prep.R

Defines functions add_dummy_variables

Documented in add_dummy_variables

#' Creates dummy variables
#'
#' It uses 'tidyeval' and 'dplyr' to create dummy variables based for
#' categorical variables.
#'
#' @param df A Local or remote data frame
#' @param x Categorical variable
#' @param values Possible known values of the categorical variable. If not passed
#' then the function will take an additional step to figure the unique values of
#' the variable.
#' @param auto_values Safeguard argument to prevent the function from figuring the
#' unique values if the values argument is empty.  If it is ok for this function
#' to obtain the unique values, set to TRUE.  Defaults to FALSE.
#' @param remove_original It removes the original variable from the returned table.
#' Defaults to TRUE.
#'
#' @examples
#' library(dplyr)
#' 
#' mtcars %>%
#'   add_dummy_variables(cyl, values = c(4, 6, 8))
#' 
#' mtcars %>%
#'   add_dummy_variables(cyl, auto_values = TRUE)
#' @export
add_dummy_variables <- function(df, x, values = c(),
                                auto_values = FALSE, remove_original = TRUE) {
  x <- enquo(x)
  var_found <- as_label(x) %in% tbl_vars(df)
  if (!var_found) stop("Variable not found")
  if (length(values) == 0) {
    if (auto_values == TRUE) {
      values <- group_by(df, !!x)
      values <- summarise(values)
      values <- pull(values)
    } else {
      stop("No values provided and auto_values is set to FALSE")
    }
  }
  vals <- map(values, ~ expr(ifelse(!!x == !!.x, 1, 0)))
  names <- map(values, ~ paste0(as_label(x), "_", .x))
  vals <- set_names(vals, names)
  vals <- vals[2:length(vals)]
  df <- mutate(df, !!!vals)
  if (remove_original) df <- select(df, -!!x)
  df
}

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modeldb documentation built on March 26, 2020, 6:31 p.m.