as_factor function

Convert labelled vectors to factors while preserving attributes

This extends as_factor as well as 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.

as_factor(x, ...)

## S3 method for class 'factor'
as_factor(x, ...)

## S3 method for class 'logical'
as_factor(x, ...)

## S3 method for class 'numeric'
as_factor(x, ...)

## S3 method for class 'character'
as_factor(x, ...)

## S3 method for class 'haven_labelled'
as_factor(
  x,
  levels = c("default", "labels", "values", "both"),
  ordered = FALSE,
  ...
)

## S3 method for class 'labelled'
as_factor(
  x,
  levels = c("default", "labels", "values", "both"),
  ordered = FALSE,
  ...
)

## S3 method for class 'data.frame'
as_factor(x, ..., only_labelled = TRUE)

Arguments

• x: Object to coerce to a factor.

• ...: Other arguments passed down to method.

• levels: How to create the levels of the generated factor:

  • "default": uses labels where available, otherwise the values. Labels are sorted by value. * "both": like "default", but pastes together the level and value * "label": use only the labels; unlabelled values become NA * "values": use only the values

• ordered: If TRUE create an ordered (ordinal) factor, if FALSE (the default) create a regular (nominal) factor.

• only_labelled: Only apply to labelled columns?

Details

Please refer to parent functions for extended documentation. To avoid redundancy calls and errors, functions are copy-pasted here

Empty variables with empty levels attribute are interpreted as logicals

Examples

# will preserve all attributes
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() |>
  dput()

structure(c(1, 2, 3, 2, 10, 9),
  labels = c(Unknown = 9, Refused = 10),
  class = "haven_labelled"
) |>
  as_factor() |> class()
structure(rep(NA,10),
  class = c("labelled")
) |>
  as_factor() |> summary()

rep(NA,10) |> as_factor()