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now interprets empty variables with empty levels attribute as logicals to avoid returning factors with empty levels
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NEWS.md
4
NEWS.md
@ -1,3 +1,7 @@
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# REDCapCAST 25.2.1
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* FIX: `as_factor()` now interprets empty variables with empty levels attribute as logicals to avoid returning factors with empty levels.
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# REDCapCAST 25.1.1
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The newly introduced extension of `forcats::fct_drop()` has been corrected to work as intended as a method.
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@ -7,6 +7,8 @@
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#' Please refer to parent functions for extended documentation.
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#' To avoid redundancy calls and errors, functions are copy-pasted here
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#'
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#' Empty variables with empty levels attribute are interpreted as logicals
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#'
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#' @param x Object to coerce to a factor.
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#' @param ... Other arguments passed down to method.
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#' @param only_labelled Only apply to labelled columns?
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@ -24,7 +26,14 @@
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#' labels = c(Unknown = 9, Refused = 10),
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#' class = "haven_labelled"
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#' ) |>
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#' as_factor()
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#' as_factor() |> class()
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#' structure(rep(NA,10),
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#' class = c("labelled")
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#' ) |>
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#' as_factor() |> summary()
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#'
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#' rep(NA,10) |> as_factor()
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#'
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#' @importFrom forcats as_factor
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#' @export
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#' @name as_factor
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@ -46,8 +55,6 @@ as_factor.logical <- function(x, ...) {
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set_attr(x, labels, overwrite = FALSE)
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}
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#' @rdname as_factor
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#' @export
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as_factor.numeric <- function(x, ...) {
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@ -121,7 +128,13 @@ as_factor.haven_labelled <- function(x, levels = c("default", "labels", "values"
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x <- structure(x, label = label)
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set_attr(x, labels_all, overwrite = FALSE)
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out <- set_attr(x, labels_all, overwrite = FALSE)
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if (all_na(out) & length(levels(out))==0){
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as_factor.logical(out)
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} else {
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out
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}
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}
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#' @export
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@ -63,6 +63,8 @@ ta loss in case of rich formatted and labelled data.
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\details{
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Please refer to parent functions for extended documentation.
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To avoid redundancy calls and errors, functions are copy-pasted here
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Empty variables with empty levels attribute are interpreted as logicals
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}
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\examples{
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# will preserve all attributes
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@ -77,5 +79,12 @@ structure(c(1, 2, 3, 2, 10, 9),
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labels = c(Unknown = 9, Refused = 10),
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class = "haven_labelled"
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) |>
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as_factor()
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as_factor() |> class()
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structure(rep(NA,10),
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class = c("labelled")
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) |>
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as_factor() |> summary()
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rep(NA,10) |> as_factor()
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}
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