check_cols | R Documentation |
check_cols()
creates a specification of a recipe step that will check if
all the columns of the training frame are present in the new data.
check_cols(
recipe,
...,
role = NA,
trained = FALSE,
skip = FALSE,
id = rand_id("cols")
)
recipe |
A recipe object. The check will be added to the sequence of operations for this recipe. |
... |
One or more selector functions to choose variables for this check.
See |
role |
Not used by this check since no new variables are created. |
trained |
A logical for whether the selectors in |
skip |
A logical. Should the check be skipped when the recipe is baked
by |
id |
A character string that is unique to this check to identify it. |
This check will break the bake()
function if any of the specified columns
is not present in the data. If the check passes, nothing is changed to the
data.
An updated version of recipe
with the new check added to the
sequence of any existing operations.
When you tidy()
this check, a tibble with columns terms
(the selectors or variables selected) and value
(the type) is returned.
Other checks:
check_class()
,
check_missing()
,
check_new_values()
,
check_range()
data(biomass, package = "modeldata")
biomass_rec <- recipe(HHV ~ ., data = biomass) %>%
step_rm(sample, dataset) %>%
check_cols(contains("gen")) %>%
step_center(all_numeric_predictors())
## Not run:
bake(biomass_rec, biomass[, c("carbon", "HHV")])
## End(Not run)
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