Converts factors, character vectors, or plain numeric vectors to
haven_labelled class, optionally assigning value labels and a variable
label. This is the reverse of to_label().
Arguments
- data
A data frame, tibble, or a single vector.
- ...
Optional: unquoted variable names (tidyselect supported). If empty on a data frame, converts all factor columns.
- labels
Optional: a named numeric vector of value labels to assign. If
NULLand the input is a factor, factor levels are used as labels.- label
Optional: a variable label string.
Value
The input with variables converted to haven_labelled. For
single vector input, returns a haven_labelled vector.
Details
Factor Conversion
When converting a factor created by to_label(), the original codes
stored in its "codes" attribute are restored (the round trip
to_labelled(to_label(x)) returns the original values and labels).
For other factors, or when labels is supplied, the integer codes
(1, 2, 3, ...) become the numeric values and the factor levels become
the value labels.
See also
to_label() for the reverse operation, val_labels() for
setting labels on existing labelled vectors
Other labels:
copy_labels(),
drop_labels(),
find_var(),
set_na(),
to_character(),
to_label(),
to_numeric(),
unlabel(),
val_labels(),
var_label()
Examples
# Factor -> haven_labelled
x <- factor(c("Male", "Female", "Male"))
to_labelled(x)
#> <labelled<double>[3]>
#> [1] 2 1 2
#>
#> Labels:
#> value label
#> 1 Female
#> 2 Male
# Numeric with custom labels
to_labelled(c(1, 2, 3),
labels = c("Low" = 1, "Medium" = 2, "High" = 3),
label = "Satisfaction level"
)
#> <labelled<double>[3]>: Satisfaction level
#> [1] 1 2 3
#>
#> Labels:
#> value label
#> 1 Low
#> 2 Medium
#> 3 High
# All factors in a data frame
data <- to_labelled(survey_data)