View source: R/factor2string.R
step_factor2string | R Documentation |
step_factor2string()
creates a specification of a recipe step that will
convert one or more factor vectors to strings.
step_factor2string(
recipe,
...,
role = NA,
trained = FALSE,
columns = FALSE,
skip = FALSE,
id = rand_id("factor2string")
)
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 |
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. |
columns |
A character string of the selected variable names. This field
is a placeholder and will be populated once |
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. |
prep
has an option strings_as_factors
that defaults to TRUE
.
If this step is used with the default option, the string(s() produced by
this step will be converted to factors after all of the steps have been
prepped.
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 columns terms
(the columns that will be affected) is returned.
The underlying operation does not allow for case weights.
Other dummy variable and encoding steps:
step_bin2factor()
,
step_count()
,
step_date()
,
step_dummy_extract()
,
step_dummy_multi_choice()
,
step_dummy()
,
step_holiday()
,
step_indicate_na()
,
step_integer()
,
step_novel()
,
step_num2factor()
,
step_ordinalscore()
,
step_other()
,
step_regex()
,
step_relevel()
,
step_string2factor()
,
step_time()
,
step_unknown()
,
step_unorder()
data(Sacramento, package = "modeldata")
rec <- recipe(~ city + zip, data = Sacramento)
make_string <- rec %>%
step_factor2string(city)
make_string <- prep(make_string,
training = Sacramento,
strings_as_factors = FALSE
)
make_string
# note that `city` is a string in recipe output
bake(make_string, new_data = NULL) %>% head()
# ...but remains a factor in the original data
Sacramento %>% head()
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