check_cols {recipes} | R Documentation |
Check if all columns are present
Description
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.
Usage
check_cols(
recipe,
...,
role = NA,
trained = FALSE,
skip = FALSE,
id = rand_id("cols")
)
Arguments
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. |
Details
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.
Value
An updated version of recipe
with the new check added to the
sequence of any existing operations.
Tidying
When you tidy()
this check, a tibble with columns
terms
(the selectors or variables selected) and value
(the type)
is returned.
See Also
Other checks:
check_class()
,
check_missing()
,
check_new_values()
,
check_range()
Examples
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)