R/dplyr.R

In skimr: Compact and Flexible Summaries of Data

#' Mutate a skim_df
#'
#' [dplyr::mutate()] currently drops attributes, but we need to keep them around
#' for other skim behaviors. Otherwise the behavior is exactly the same. For
#' more information, see <https://github.com/tidyverse/dplyr/issues/3429>.
#'
#' @param .data A `skim_df`, which behaves like a `tbl.`
#' @param ... Name-value pairs of expressions, each with length 1 or the same
#'   length as the number of rows in the group, if using [dplyr::group_by()], or
#'   in the entire input (if not using groups). The name of each argument will
#'   be the name of a new variable, and the value will be its corresponding
#'   value. Use `NULL` value in [dplyr::mutate()] to drop a variable. New
#'   variables overwrite existing variables of the same name.
#'
#'   The arguments in `...` are automatically quoted with [rlang::quo()] and
#'   evaluated with [rlang::eval_tidy()] in the context of the data frame. They
#'   support unquoting [rlang::quasiquotation] and splicing. See
#'   `vignette("programming", package = "dplyr")` for an introduction to these
#'   concepts.
#' @return A `skim_df` object, which also inherits the class(es) of the input
#'   data. In many ways, the object behaves like a [tibble::tibble()].
#' @seealso [dplyr::mutate()] for the function's expected behavior.
#' @importFrom dplyr mutate
#' @export
mutate.skim_df <- function(.data, ...) {
  mutated <- NextMethod("mutate")
  if (could_be_skim_df(mutated)) {
    reassign_skim_attrs(mutated, .data)
  } else {
    strip_skim_attrs(mutated)
  }
}