Convert input to a factor.
The base function as.factor() is not a generic, but this variant
is. Methods are provided for factors, character vectors, labelled
vectors, and data frames. By default, when applied to a data frame,
it only affects labelled columns.
## S3 method for class 'data.frame'
as_factor(x, ..., only_labelled = TRUE)
## 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,
...
)x |
Object to coerce to a factor. |
... |
Other arguments passed down to method. |
only_labelled |
Only apply to labelled columns? |
levels |
How to create the levels of the generated factor:
|
ordered |
If |
Includes methods for both class haven_labelled and labelled
for backward compatibility.
x <- labelled(sample(5, 10, replace = TRUE), c(Bad = 1, Good = 5)) # Default method uses values where available as_factor(x) # You can also extract just the labels as_factor(x, levels = "labels") # Or just the values as_factor(x, levels = "values") # Or combine value and label as_factor(x, levels = "both") # as_factor() will preserve SPSS missing values from values and ranges y <- labelled_spss(1:10, na_values = c(2, 4), na_range = c(8, 10)) as_factor(y) # use zap_missing() first to convert to NAs zap_missing(y) as_factor(zap_missing(y))
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