step_dummy {recipes} | R Documentation |
step_dummy
creates a a specification of a recipe step that
will convert nominal data (e.g. character or factors) into one or more
numeric binary model terms for the levels of the original data.
step_dummy(recipe, ..., role = "predictor", trained = FALSE, contrast = options("contrasts"), naming = function(var, lvl) paste(var, make.names(lvl), sep = "_"), levels = NULL)
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 will
be used to create the dummy variables. See |
role |
For model terms created by this step, what analysis role should they be assigned?. By default, the function assumes that the binary dummy 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. |
contrast |
A specification for which type of contrast should be used
to make a set of full rank dummy variables. See
|
naming |
A function that defines the naming convention for new binary columns. See Details below. |
levels |
A list that contains the information needed to create dummy
variables for each variable contained in |
step_dummy
will create a set of binary dummy variables
from a factor variable. For example, if a factor column in the data set
has levels of "red", "green", "blue", the dummy variable bake will
create two additional columns of 0/1 data for two of those three values
(and remove the original column).
By default, the missing dummy variable will correspond to the first level of the factor being converted.
The function allows for non-standard naming of the resulting variables. For
a factor named x
, with levels "a"
and "b"
, the
default naming convention would be to create a new variable called
x_b
. Note that if the factor levels are not valid variable names
(e.g. "some text with spaces"), it will be changed by
make.names
to be valid (see the example below). The
naming format can be changed using the naming
argument.
An updated version of recipe
with the
new step added to the sequence of existing steps (if any).
data(okc) okc <- okc[complete.cases(okc),] rec <- recipe(~ diet + age + height, data = okc) dummies <- rec %>% step_dummy(diet) dummies <- prep(dummies, training = okc) dummy_data <- bake(dummies, newdata = okc) unique(okc$diet) grep("^diet", names(dummy_data), value = TRUE)