step_holiday()
creates a specification of a recipe step that will convert
date data into one or more binary indicator variables for common holidays.
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. The selected variables should have class Date
or
POSIXct
. See selections()
for more details.
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.
A logical to indicate if the quantities for preprocessing have been estimated.
A character string that includes at least one
holiday supported by the timeDate
package. See
timeDate::listHolidays()
for a complete list.
A character string of the selected variable names. This field
is a placeholder and will be populated once prep()
is used.
A logical to keep the original variables in the
output. Defaults to TRUE
.
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.
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 any existing operations.
Unlike some other steps, step_holiday
does not
remove the original date variables by default. Set keep_original_cols
to FALSE
to remove them.
When you tidy()
this step, a tibble is returned with
columns terms
, holiday
, and id
:
character, the selectors or variables selected
character, name of holidays
character, id of this step
The underlying operation does not allow for case weights.
Other dummy variable and encoding steps:
step_bin2factor()
,
step_count()
,
step_date()
,
step_dummy()
,
step_dummy_extract()
,
step_dummy_multi_choice()
,
step_factor2string()
,
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()
library(lubridate)
examples <- data.frame(someday = ymd("2000-12-20") + days(0:40))
holiday_rec <- recipe(~someday, examples) %>%
step_holiday(all_predictors())
holiday_rec <- prep(holiday_rec, training = examples)
holiday_values <- bake(holiday_rec, new_data = examples)
holiday_values
#> # A tibble: 41 × 4
#> someday someday_LaborDay someday_NewYearsDay someday_ChristmasDay
#> <date> <int> <int> <int>
#> 1 2000-12-20 0 0 0
#> 2 2000-12-21 0 0 0
#> 3 2000-12-22 0 0 0
#> 4 2000-12-23 0 0 0
#> 5 2000-12-24 0 0 0
#> 6 2000-12-25 0 0 1
#> 7 2000-12-26 0 0 0
#> 8 2000-12-27 0 0 0
#> 9 2000-12-28 0 0 0
#> 10 2000-12-29 0 0 0
#> # ℹ 31 more rows