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#' General Variable Filter
#'
#' `step_rm` creates a *specification* of a recipe step
#' that will remove variables based on their name, type, or role.
#'
#' @inheritParams step_center
#' @param removals A character string that contains the names of
#' columns that should be removed. These values are not determined
#' until [prep()] is called.
#' @template step-return
#' @template filter-steps
#' @details
#'
#' # Tidying
#'
#' When you [`tidy()`][tidy.recipe()] this step, a tibble with column
#' `terms` (the columns that will be removed) is returned.
#'
#' @template case-weights-not-supported
#'
#' @family variable filter steps
#' @export
#' @examplesIf rlang::is_installed("modeldata")
#' data(biomass, package = "modeldata")
#'
#' biomass_tr <- biomass[biomass$dataset == "Training", ]
#' biomass_te <- biomass[biomass$dataset == "Testing", ]
#'
#' rec <- recipe(
#' HHV ~ carbon + hydrogen + oxygen + nitrogen + sulfur,
#' data = biomass_tr
#' )
#'
#' library(dplyr)
#' smaller_set <- rec %>%
#' step_rm(contains("gen"))
#'
#' smaller_set <- prep(smaller_set, training = biomass_tr)
#'
#' filtered_te <- bake(smaller_set, biomass_te)
#' filtered_te
#'
#' tidy(smaller_set, number = 1)
step_rm <- function(recipe,
...,
role = NA,
trained = FALSE,
removals = NULL,
skip = FALSE,
id = rand_id("rm")) {
add_step(
recipe,
step_rm_new(
terms = enquos(...),
role = role,
trained = trained,
removals = removals,
skip = skip,
id = id
)
)
}
step_rm_new <- function(terms, role, trained, removals, skip, id) {
step(
subclass = "rm",
terms = terms,
role = role,
trained = trained,
removals = removals,
skip = skip,
id = id
)
}
#' @export
prep.step_rm <- function(x, training, info = NULL, ...) {
col_names <- recipes_eval_select(x$terms, training, info)
step_rm_new(
terms = x$terms,
role = x$role,
trained = TRUE,
removals = col_names,
skip = x$skip,
id = x$id
)
}
#' @export
bake.step_rm <- function(object, new_data, ...) {
if (length(object$removals) > 0) {
new_data <- new_data[, !(colnames(new_data) %in% object$removals)]
}
new_data
}
print.step_rm <-
function(x, width = max(20, options()$width - 22), ...) {
title <- "Variables removed "
print_step(x$removals, x$terms, x$trained, title, width)
invisible(x)
}
#' @rdname tidy.recipe
#' @export
tidy.step_rm <- tidy_filter
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