step_date {recipes} | R Documentation |
step_date
creates a a specification of a recipe step that will
convert date data into one or more factor or numeric variables.
step_date(recipe, ..., role = "predictor", trained = FALSE, features = c("dow", "month", "year"), abbr = TRUE, label = TRUE, ordinal = FALSE, columns = NULL)
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 that
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. |
features |
A character string that includes at least one of the
following values: |
abbr |
A logical. Only available for features |
label |
A logical. Only available for features |
ordinal |
A logical: should factors be ordered? Only available for
features |
columns |
A character string of variables that will be used as
inputs. This field is a placeholder and will be populated once
|
Unlike other steps, step_date
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).
step_holiday
step_rm
recipe
prep.recipe
bake.recipe
library(lubridate) examples <- data.frame(Dan = ymd("2002-03-04") + days(1:10), Stefan = ymd("2006-01-13") + days(1:10)) date_rec <- recipe(~ Dan + Stefan, examples) %>% step_date(all_predictors()) date_rec <- prep(date_rec, training = examples) date_values <- bake(date_rec, newdata = examples) date_values