recipes: step_date – R documentation

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step_date

Date Feature Generator

Description

step_date creates a specification of a recipe step that will convert date data into one or more factor or numeric variables.

Usage

step_date(
  recipe,
  ...,
  role = "predictor",
  trained = FALSE,
  features = c("dow", "month", "year"),
  abbr = TRUE,
  label = TRUE,
  ordinal = FALSE,
  columns = NULL,
  keep_original_cols = TRUE,
  skip = FALSE,
  id = rand_id("date")
)

## S3 method for class 'step_date'
tidy(x, ...)

Arguments

`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 `Date` or `POSIXct`. See `selections()` for more details. For the `tidy` method, these are not currently used.
`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: `month`, `dow` (day of week), `doy` (day of year), `week`, `month`, `decimal` (decimal date, e.g. 2002.197), `quarter`, `semester`, `year`.
`abbr`	A logical. Only available for features `month` or `dow`. `FALSE` will display the day of the week as an ordered factor of character strings, such as "Sunday". `TRUE` will display an abbreviated version of the label, such as "Sun". `abbr` is disregarded if `label = FALSE`.
`label`	A logical. Only available for features `month` or `dow`. `TRUE` will display the day of the week as an ordered factor of character strings, such as "Sunday." `FALSE` will display the day of the week as a number.
`ordinal`	A logical: should factors be ordered? Only available for features `month` or `dow`.
`columns`	A character string of variables that will be used as inputs. This field is a placeholder and will be populated once `prep.recipe()` is used.
`keep_original_cols`	A logical to keep the original variables in the output. Defaults to `TRUE`.
`skip`	A logical. Should the step be skipped when the recipe is baked by `bake.recipe()`? While all operations are baked when `prep.recipe()` 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
`id`	A character string that is unique to this step to identify it.
`x`	A `step_date` object.

Details

Unlike some other steps, step_date does not remove the original date variables by default. Set keep_original_cols to FALSE to remove them.

Value

For step_date, 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 (the selectors or variables selected), value (the feature names), and ordinal (a logical).

Examples

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())

tidy(date_rec, number = 1)

date_rec <- prep(date_rec, training = examples)

date_values <- bake(date_rec, new_data = examples)
date_values

tidy(date_rec, number = 1)

recipes

Preprocessing Tools to Create Design Matrices

v0.1.16

MIT + file LICENSE

Authors

Max Kuhn [aut, cre], Hadley Wickham [aut], RStudio [cph]

Initial release