recipes: step_mutate_at – R documentation

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step_mutate_at

Mutate multiple columns using dplyr

Description

step_mutate_at creates a specification of a recipe step that will modify the selected variables using a common function via dplyr::mutate_at().

Usage

step_mutate_at(
  recipe,
  ...,
  fn,
  role = "predictor",
  trained = FALSE,
  inputs = NULL,
  skip = FALSE,
  id = rand_id("mutate_at")
)

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 which variables are affected by the step. See `selections()` for more details. For the `tidy` method, these are not currently used.
`fn`	A function fun, a quosure style lambda '~ fun(.)“ or a list of either form. (see `dplyr::mutate_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 function assumes that the new dimension columns created by 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.recipe()`? While all operations are baked when `prep.recipe()` 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.

Value

An updated version of recipe with the new step added to the sequence of existing steps (if any). For the tidy method, a tibble with columns terms which contains the columns being transformed.

Examples

library(dplyr)
recipe(~ ., data = iris) %>%
  step_mutate_at(contains("Length"), fn = ~ 1/.) %>%
  prep() %>%
  bake(new_data = NULL) %>%
  slice(1:10)

recipe(~ ., data = iris) %>%
  # leads to more columns being created.
  step_mutate_at(contains("Length"), fn = list(log = log, sqrt = sqrt)) %>%
  prep() %>%
  bake(new_data = NULL) %>%
  slice(1:10)

recipes

Preprocessing Tools to Create Design Matrices

v0.1.16

MIT + file LICENSE

Authors

Max Kuhn [aut, cre], Hadley Wickham [aut], RStudio [cph]

Initial release