step_arrange | R Documentation |
step_arrange
creates a specification of a recipe step
that will sort rows using dplyr::arrange()
.
step_arrange( recipe, ..., role = NA, trained = FALSE, inputs = NULL, skip = FALSE, id = rand_id("arrange") )
recipe |
A recipe object. The step will be added to the sequence of operations for this recipe. |
... |
Comma separated list of unquoted variable names.
Use 'desc()“ to sort a variable in descending order. See
|
role |
Not used by this step since no new variables are created. |
trained |
A logical to indicate if the quantities for preprocessing have been estimated. |
inputs |
Quosure of values given by |
skip |
A logical. Should the step be skipped when the
recipe is baked by |
id |
A character string that is unique to this step to identify it. |
When an object in the user's global environment is
referenced in the expression defining the new variable(s),
it is a good idea to use quasiquotation (e.g. !!!
)
to embed the value of the object in the expression (to
be portable between sessions). See the examples.
An updated version of recipe
with the new step added to the
sequence of any existing operations.
When you tidy()
this step, a tibble with column
terms
which contains the sorting variable(s) or expression(s) is
returned. The expressions are text representations and are not
parsable.
The underlying operation does not allow for case weights.
Other row operation steps:
step_filter()
,
step_impute_roll()
,
step_lag()
,
step_naomit()
,
step_sample()
,
step_shuffle()
,
step_slice()
Other dplyr steps:
step_filter()
,
step_mutate_at()
,
step_mutate()
,
step_rename_at()
,
step_rename()
,
step_sample()
,
step_select()
,
step_slice()
rec <- recipe(~., data = iris) %>% step_arrange(desc(Sepal.Length), 1 / Petal.Length) prepped <- prep(rec, training = iris %>% slice(1:75)) tidy(prepped, number = 1) library(dplyr) dplyr_train <- iris %>% as_tibble() %>% slice(1:75) %>% dplyr::arrange(desc(Sepal.Length), 1 / Petal.Length) rec_train <- bake(prepped, new_data = NULL) all.equal(dplyr_train, rec_train) dplyr_test <- iris %>% as_tibble() %>% slice(76:150) %>% dplyr::arrange(desc(Sepal.Length), 1 / Petal.Length) rec_test <- bake(prepped, iris %>% slice(76:150)) all.equal(dplyr_test, rec_test) # When you have variables/expressions, you can create a # list of symbols with `rlang::syms()`` and splice them in # the call with `!!!`. See https://tidyeval.tidyverse.org sort_vars <- c("Sepal.Length", "Petal.Length") qq_rec <- recipe(~., data = iris) %>% # Embed the `values` object in the call using !!! step_arrange(!!!syms(sort_vars)) %>% prep(training = iris) tidy(qq_rec, number = 1)
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