#' Filtering of Stop Words for Tokens Variables
#'
#' `step_stopwords()` creates a *specification* of a recipe step that will
#' filter a [`token`][tokenlist()] variable for stop words.
#'
#' @template args-recipe
#' @template args-dots
#' @template args-role_no-new
#' @template args-trained
#' @template args-columns
#' @param language A character to indicate the language of stop words by ISO
#' 639-1 coding scheme.
#' @param keep A logical. Specifies whether to keep the stop words or discard
#' them.
#' @param stopword_source A character to indicate the stop words source as
#' listed in `stopwords::stopwords_getsources`.
#' @param custom_stopword_source A character vector to indicate a custom list of
#' words that cater to the users specific problem.
#' @template args-skip
#' @template args-id
#'
#' @template returns
#'
#' @details
#'
#' Stop words are words which sometimes are removed before natural language
#' processing tasks. While stop words usually refers to the most common words in
#' the language there is no universal stop word list.
#'
#' The argument `custom_stopword_source` allows you to pass a character vector
#' to filter against. With the `keep` argument one can specify words to keep
#' instead of removing thus allowing you to select words with a combination of
#' these two arguments.
#'
#' # Tidying
#'
#' When you [`tidy()`][tidy.recipe()] this step, a tibble is returned with
#' columns `terms`, `value`, `keep`, and `id`:
#'
#' \describe{
#' \item{terms}{character, the selectors or variables selected}
#' \item{value}{character, name of stop word list}
#' \item{keep}{logical, whether stop words are removed or kept}
#' \item{id}{character, id of this step}
#' }
#'
#' @template case-weights-not-supported
#'
#' @seealso [step_tokenize()] to turn characters into [`tokens`][tokenlist()]
#' @family Steps for Token Modification
#'
#' @examplesIf rlang::is_installed("stopwords")
#' library(recipes)
#' library(modeldata)
#' data(tate_text)
#' tate_rec <- recipe(~., data = tate_text) %>%
#' step_tokenize(medium) %>%
#' step_stopwords(medium)
#'
#' tate_obj <- tate_rec %>%
#' prep()
#'
#' bake(tate_obj, new_data = NULL, medium) %>%
#' slice(1:2)
#'
#' bake(tate_obj, new_data = NULL) %>%
#' slice(2) %>%
#' pull(medium)
#'
#' tidy(tate_rec, number = 2)
#' tidy(tate_obj, number = 2)
#'
#' # With a custom stop words list
#'
#' tate_rec <- recipe(~., data = tate_text) %>%
#' step_tokenize(medium) %>%
#' step_stopwords(medium, custom_stopword_source = c("twice", "upon"))
#' tate_obj <- tate_rec %>%
#' prep(traimomg = tate_text)
#'
#' bake(tate_obj, new_data = NULL) %>%
#' slice(2) %>%
#' pull(medium)
#' @export
step_stopwords <-
function(recipe,
...,
role = NA,
trained = FALSE,
columns = NULL,
language = "en",
keep = FALSE,
stopword_source = "snowball",
custom_stopword_source = NULL,
skip = FALSE,
id = rand_id("stopwords")) {
add_step(
recipe,
step_stopwords_new(
terms = enquos(...),
role = role,
trained = trained,
columns = columns,
language = language,
keep = keep,
stopword_source = stopword_source,
custom_stopword_source = custom_stopword_source,
skip = skip,
id = id
)
)
}
step_stopwords_new <-
function(terms, role, trained, columns, language, keep,
stopword_source, custom_stopword_source, skip, id) {
step(
subclass = "stopwords",
terms = terms,
role = role,
trained = trained,
columns = columns,
language = language,
keep = keep,
stopword_source = stopword_source,
custom_stopword_source = custom_stopword_source,
skip = skip,
id = id
)
}
#' @export
prep.step_stopwords <- function(x, training, info = NULL, ...) {
col_names <- recipes_eval_select(x$terms, training, info)
check_type(training[, col_names], types = "tokenlist")
step_stopwords_new(
terms = x$terms,
role = x$role,
trained = TRUE,
columns = col_names,
language = x$language,
keep = x$keep,
stopword_source = x$stopword_source,
custom_stopword_source = x$custom_stopword_source,
skip = x$skip,
id = x$id
)
}
#' @export
bake.step_stopwords <- function(object, new_data, ...) {
col_names <- object$columns
check_new_data(col_names, object, new_data)
stopword_list <- object$custom_stopword_source %||%
stopwords::stopwords(
language = object$language,
source = object$stopword_source
)
for (col_name in col_names) {
new_data[[col_name]] <- tokenlist_filter(
new_data[[col_name]],
stopword_list,
object$keep
)
}
new_data <- factor_to_text(new_data, col_names)
new_data
}
#' @export
print.step_stopwords <-
function(x, width = max(20, options()$width - 30), ...) {
title <- "Stop word removal for "
print_step(x$columns, x$terms, x$trained, title, width)
invisible(x)
}
#' @rdname step_stopwords
#' @usage NULL
#' @export
tidy.step_stopwords <- function(x, ...) {
if (is_trained(x)) {
res <- tibble(
terms = unname(x$columns),
value = x$stopword_source,
keep = x$keep
)
} else {
term_names <- sel2char(x$terms)
res <- tibble(
terms = term_names,
value = na_chr,
keep = na_lgl
)
}
res$id <- x$id
res
}
#' @rdname required_pkgs.step
#' @export
required_pkgs.step_stopwords <- function(x, ...) {
c("textrecipes", "stopwords")
}
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