REDCapCAST/R/as_factor.R

255 lines
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R

#' Convert labelled vectors to factors while preserving attributes
#'
#' This extends [forcats::as_factor()] as well as [haven::as_factor()], by appending
#' original attributes except for "class" after converting to factor to avoid
#' ta loss in case of rich formatted and labelled data.
#'
#' Please refer to parent functions for extended documentation.
#'
#' @param x Object to coerce to a factor.
#' @param ... Other arguments passed down to method.
#' @export
#' @examples
#' # will preserve all attributes but class
#' \dontrun{
#' c(1, 4, 3, "A", 7, 8, 1) |> as_factor()
#' structure(c(1, 2, 3, 2, 10, 9),
#' labels = c(Unknown = 9, Refused = 10)
#' ) |>
#' as_factor()
#'
#' structure(c(1, 2, 3, 2, 10, 9),
#' labels = c(Unknown = 9, Refused = 10),
#' class = "haven_labelled"
#' ) |>
#' as_factor()
#' }
#' @importFrom forcats as_factor
#' @importFrom rlang check_dots_used
#' @export
#' @name as_factor
as_factor <- function(x, ...) {
rlang::check_dots_used()
UseMethod("as_factor")
}
#' @rdname as_factor
#' @export
as_factor.logical <- function(x, ...) {
labels <- get_attr(x)
x <- forcats::as_factor(x, ...)
set_attr(x, labels[-match("class", names(labels))])
}
#' @rdname as_factor
#' @export
as_factor.numeric <- function(x, ...) {
labels <- get_attr(x)
x <- forcats::as_factor(x, ...)
set_attr(x, labels[-match("class", names(labels))])
}
#' @rdname as_factor
#' @export
as_factor.character <- function(x, ...) {
labels <- get_attr(x)
x <- forcats::as_factor(x, ...)
set_attr(x, labels[-match("class", names(labels))])
}
#' @rdname as_factor
#' @export
as_factor.haven_labelled <- function(x, ...) {
labels <- get_attr(x)
x <- haven::as_factor(x, ...)
set_attr(x, labels[-match("class", names(labels))])
}
#' @export
#' @rdname as_factor
as_factor.labelled <- as_factor.haven_labelled
#' Get named vector of factor levels and values
#'
#' @param data factor
#' @param label character string of attribute with named vector of factor labels
#' @param na.label character string to refactor NA values. Default is NULL.
#' @param na.value new value for NA strings. Ignored if na.label is NULL.
#' Default is 99.
#'
#' @return named vector
#' @export
#'
#' @examples
#' \dontrun{
#' structure(c(1, 2, 3, 2, 10, 9),
#' labels = c(Unknown = 9, Refused = 10),
#' class = "haven_labelled"
#' ) |> as_factor() |> named_levels()
#' }
named_levels <- function(data, label = "labels",na.label=NULL, na.value=99) {
stopifnot(is.factor(data))
if (!is.null(na.label)){
attrs <- attributes(data)
lvls <- as.character(data)
lvls[is.na(lvls)] <- na.label
vals <- as.numeric(data)
vals[is.na(vals)] <- na.value
lbls <- data.frame(
name = lvls,
value = vals
) |> unique() |>
(\(d){
stats::setNames(d$value, d$name)
})() |>
sort()
data <- do.call(structure,
c(list(.Data=match(vals,lbls)),
attrs[-match("levels", names(attrs))],
list(levels=names(lbls),
labels=lbls)))
}
d <- data.frame(
name = levels(data)[data],
value = as.numeric(data)
) |>
unique()
## Applying labels
attr_l <- attr(x = data, which = label, exact = TRUE)
if (length(attr_l) != 0) {
d$value[match(names(attr_l), d$name)] <- unname(attr_l)
}
out <- stats::setNames(d$value, d$name)
## Sort if levels are numeric
## Else, they appear in order of appearance
if (identical(
levels(data),
suppressWarnings(as.character(as.numeric(levels(data))))
)) {
out <- out |> sort()
}
out
}
#' Allows conversion of factor to numeric values preserving original levels
#'
#' @param data vector
#'
#' @return numeric vector
#' @export
#'
#' @examples
#' \dontrun{
#' c(1, 4, 3, "A", 7, 8, 1) |>
#' as_factor() |> fct2num()
#'
#' structure(c(1, 2, 3, 2, 10, 9),
#' labels = c(Unknown = 9, Refused = 10),
#' class = "haven_labelled"
#' ) |>
#' as_factor() |>
#' fct2num()
#'
#' structure(c(1, 2, 3, 2, 10, 9),
#' labels = c(Unknown = 9, Refused = 10)
#' ) |>
#' as_factor() |>
#' fct2num()
#' }
fct2num <- function(data) {
stopifnot(is.factor(data))
as.numeric(named_levels(data))[match(data, names(named_levels(data)))]
}
#' Extract attribute. Returns NA if none
#'
#' @param data vector
#' @param attr attribute name
#'
#' @return character vector
#' @export
#'
#' @examples
#' attr(mtcars$mpg, "label") <- "testing"
#' do.call(c,sapply(mtcars, get_attr))
#' \dontrun{
#' mtcars |>
#' numchar2fct(numeric.threshold = 6) |>
#' ds2dd_detailed()
#' }
get_attr <- function(data, attr = NULL) {
if (is.null(attr)) {
attributes(data)
} else {
a <- attr(data, attr, exact = TRUE)
if (is.null(a)) {
NA
} else {
a
}
}
}
#' Set attributes for named attribute. Appends if attr is NULL
#'
#' @param data vector
#' @param label label
#' @param attr attribute name
#' @param overwrite overwrite existing attributes. Default is FALSE.
#'
#' @return vector with attribute
#' @export
#'
set_attr <- function(data, label, attr = NULL, overwrite=FALSE) {
if (is.null(attr)) {
## Has to be list...
stopifnot(is.list(label))
## ... with names
stopifnot(length(label)==length(names(label)))
if (!overwrite){
label <- label[!names(label) %in% names(attributes(data))]
}
attributes(data) <- c(attributes(data),label)
} else {
attr(data, attr) <- label
}
data
}
#' Finish incomplete haven attributes substituting missings with values
#'
#' @param data haven labelled variable
#'
#' @return named vector
#' @export
#'
#' @examples
#' ds <- structure(c(1, 2, 3, 2, 10, 9),
#' labels = c(Unknown = 9, Refused = 10),
#' class = "haven_labelled"
#' )
#' haven::is.labelled(ds)
#' attributes(ds)
#' ds |> haven_all_levels()
haven_all_levels <- function(data) {
stopifnot(haven::is.labelled(data))
if (length(attributes(data)$labels) == length(unique(data))) {
out <- attributes(data)$labels
} else {
att <- attributes(data)$labels
out <- c(unique(data[!data %in% att]), att) |>
stats::setNames(c(unique(data[!data %in% att]), names(att)))
}
out
}