step_filter {recipes} | R Documentation |
step_filter
creates a specification of a recipe step
that will remove rows using dplyr::filter()
.
step_filter(recipe, ..., role = NA, trained = FALSE, inputs = NULL, skip = FALSE, id = rand_id("filter")) ## S3 method for class 'step_filter' tidy(x, ...)
recipe |
A recipe object. The step will be added to the sequence of operations for this recipe. |
... |
Logical predicates defined in terms of the variables
in the data. Multiple conditions are combined with |
role |
Not used by this step since no new variables are created. |
trained |
A logical to indicate if the quantities for preprocessing have been estimated. |
inputs |
Quosure of values given by |
skip |
A logical. Should the step be skipped when the
recipe is baked by |
id |
A character string that is unique to this step to identify it. |
x |
A |
When an object in the user's global environment is
referenced in the expression defining the new variable(s),
it is a good idea to use quasiquotation (e.g. !!
) to embed
the value of the object in the expression (to be portable
between sessions). See the examples.
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
which
contains the conditional statements. These
expressions are text representations and are not parsable.
rec <- recipe( ~ ., data = iris) %>% step_filter(Sepal.Length > 4.5, Species == "setosa") prepped <- prep(rec, training = iris %>% slice(1:75), retain = TRUE) library(dplyr) dplyr_train <- iris %>% as_tibble() %>% slice(1:75) %>% dplyr::filter(Sepal.Length > 4.5, Species == "setosa") rec_train <- juice(prepped) all.equal(dplyr_train, rec_train) dplyr_test <- iris %>% as_tibble() %>% slice(76:150) %>% dplyr::filter(Sepal.Length > 4.5, Species != "setosa") rec_test <- bake(prepped, iris %>% slice(76:150)) all.equal(dplyr_test, rec_test) values <- c("versicolor", "virginica") qq_rec <- recipe( ~ ., data = iris) %>% # Embed the `values` object in the call using !! step_filter(Sepal.Length > 4.5, Species %in% !!values) tidy(qq_rec, number = 1)