get_levels()
extracts the levels from any factor columns in data
. It is
mainly useful for extracting the original factor levels from the predictors
in the training set. get_outcome_levels()
is a small wrapper around
get_levels()
for extracting levels from a factor outcome
that first calls standardize()
on y
.
Arguments
- data
A data.frame to extract levels from.
- y
The outcome. This can be:
A factor vector
A numeric vector
A 1D numeric array
A numeric matrix with column names
A 2D numeric array with column names
A data frame with numeric or factor columns
Value
A named list with as many elements as there are factor columns in data
or y
. The names are the names of the factor columns, and the values
are character vectors of the levels.
If there are no factor columns, NULL
is returned.
Examples
# Factor columns are returned with their levels
get_levels(iris)
#> $Species
#> [1] "setosa" "versicolor" "virginica"
#>
# No factor columns
get_levels(mtcars)
#> NULL
# standardize() is first run on `y`
# which converts the input to a data frame
# with an automatically named column, `".outcome"`
get_outcome_levels(y = factor(letters[1:5]))
#> $.outcome
#> [1] "a" "b" "c" "d" "e"
#>