step_rename_at: Rename multiple columns using dplyr
Description
step_rename_at creates a specification of a recipe step that will rename
the selected variables using a common function via dplyr::rename_at().
Usage
step_rename_at(
recipe,
...,
fn,
role = "predictor",
trained = FALSE,
inputs = NULL,
skip = FALSE,
id = rand_id("rename_at")
)
Value
An updated version of recipe with the new step added to the
sequence of any existing operations.
Arguments
recipe
A recipe object. The step will be added to the
sequence of operations for this recipe.
...
One or more selector functions to choose variables
for this step. See selections() for more details.
fn
A function fun, a quosure style lambda `~ fun(.)`` or a list of
either form (but containing only a single function, see dplyr::rename_at()).
Note that this argument must be named.
role
For model terms created by this step, what analysis role should
they be assigned? By default, the new columns created by this step from
the original variables will be used as predictors in a model.
trained
A logical to indicate if the quantities for
preprocessing have been estimated.
inputs
A vector of column names populated by prep().
skip
A logical. Should the step be skipped when the
recipe is baked by bake()? While all operations are baked
when prep() is run, some operations may not be able to be
conducted on new data (e.g. processing the outcome variable(s)).
Care should be taken when using skip = TRUE as it may affect
the computations for subsequent operations.
id
A character string that is unique to this step to identify it.
Tidying
When you tidy() this step, a tibble with columns
terms which contains the columns being transformed is returned.
Case weights
The underlying operation does not allow for case weights.