step_holiday {recipes} | R Documentation |
step_holiday
creates a a specification of a
recipe step that will convert date data into one or more binary
indicator variables for common holidays.
step_holiday(recipe, ..., role = "predictor", trained = FALSE, holidays = c("LaborDay", "NewYearsDay", "ChristmasDay"), columns = NULL) ## S3 method for class 'step_holiday' tidy(x, ...)
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 will be used to create the new variables. The selected
variables should have class |
role |
For model terms created by this step, what analysis role should they be assigned?. By default, the function assumes that the new variable 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. |
holidays |
A character string that includes at least one
holiday supported by the |
columns |
A character string of variables that will be
used as inputs. This field is a placeholder and will be
populated once |
x |
A |
Unlike other steps, step_holiday
does
not remove the original date variables.
step_rm()
can be used for this purpose.
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 is
the columns that will be affected and holiday
.
step_date()
step_rm()
recipe()
prep.recipe()
bake.recipe()
timeDate::listHolidays()
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, newdata = examples) holiday_values