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.
Usage
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
Examples
# will preserve all attributes
c(1, 4, 3, "A", 7, 8, 1) |> as_factor()
#> [1] 1 4 3 A 7 8 1
#> Levels: 1 4 3 A 7 8
structure(c(1, 2, 3, 2, 10, 9),
labels = c(Unknown = 9, Refused = 10)
) |>
as_factor() |>
dput()
#> structure(c(1L, 2L, 3L, 2L, 5L, 4L), levels = c("1", "2", "3",
#> "9", "10"), class = "factor", labels = c(Unknown = 9, Refused = 10
#> ))
structure(c(1, 2, 3, 2, 10, 9),
labels = c(Unknown = 9, Refused = 10),
class = "haven_labelled"
) |>
as_factor()
#> [1] 1 2 3 2 Refused Unknown
#> attr(,"labels")
#> Unknown Refused
#> 9 10
#> Levels: 1 2 3 Unknown Refused