| as_factor | R Documentation | 
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)
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?  | 
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
# 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()
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