step_lag {recipes} | R Documentation |
step_lag
creates a specification of a recipe step that
will add new columns of lagged data. Lagged data will
by default include NA values where the lag was induced.
These can be removed with step_naomit()
, or you may
specify an alternative filler value with the default
argument.
step_lag(recipe, ..., role = "predictor", trained = FALSE, lag = 1, prefix = "lag_", default = NA, skip = FALSE)
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 are
affected by the step. See |
role |
Defaults to "predictor" |
trained |
A logical to indicate if the quantities for preprocessing have been estimated. |
lag |
A vector of positive integers. Each specified column will be lagged for each value in the vector. |
prefix |
A prefix for generated column names, default to "lag_". |
default |
Passed to |
skip |
A logical. Should the step be skipped when the
recipe is baked by |
The step assumes that the data are already in the proper sequential order for lagging.
An updated version of recipe
with the
new step added to the sequence of existing steps (if any).
recipe()
prep.recipe()
bake.recipe()
step_naomit()
n <- 10 start <- as.Date('1999/01/01') end <- as.Date('1999/01/10') df <- data.frame(x = runif(n), index = 1:n, day = seq(start, end, by = "day")) recipe(~ ., data = df) %>% step_lag(index, day, lag = 2:3) %>% prep(df) %>% bake(df)