step_unorder creates a specification of a recipe
step that will transform the data.
step_unorder( recipe, ..., role = NA, trained = FALSE, columns = NULL, skip = FALSE, id = rand_id("unorder") ) # S3 method for step_unorder tidy(x, ...)
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
Not used by this step since no new variables are created.
A logical to indicate if the quantities for preprocessing have been estimated.
A character string of variable names that will
be populated (eventually) by the
A logical. Should the step be skipped when the
recipe is baked by
A character string that is unique to this step to identify it.
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
columns that will be affected).
The factors level order is preserved during the transformation.
lmh <- c("Low", "Med", "High") examples <- data.frame(X1 = factor(rep(letters[1:4], each = 3)), X2 = ordered(rep(lmh, each = 4), levels = lmh)) rec <- recipe(~ X1 + X2, data = examples) factor_trans <- rec %>% step_unorder(all_nominal_predictors()) factor_obj <- prep(factor_trans, training = examples)#> Warning: `step_unorder` requires ordered factors. Variables X1 will be ignored.#> #> Low Med High #> Low 4 0 0 #> Med 0 4 0 #> High 0 0 4tidy(factor_trans, number = 1)#> # A tibble: 1 x 2 #> terms id #> <chr> <chr> #> 1 all_nominal_predictors() unorder_NRDyGtidy(factor_obj, number = 1)#> # A tibble: 1 x 2 #> terms id #> <chr> <chr> #> 1 X2 unorder_NRDyG