R: Convert Numbers to Factors

step_num2factor {recipes}

R Documentation

Convert Numbers to Factors

Description

step_num2factor will convert one or more numeric vectors to factors (ordered or unordered). This can be useful when categories are encoded as integers.

Usage

step_num2factor(recipe, ..., role = NA, transform = function(x) x,
  trained = FALSE, levels = NULL, ordered = FALSE, skip = FALSE)

## S3 method for class 'step_num2factor'
tidy(x, ...)

Arguments

`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 converted to factors. See `selections()` for more details. For the `tidy` method, these are not currently used.
`role`	Not used by this step since no new variables are created.
`transform`	A function taking a single argument `x` that can be used to modify the numeric values prior to determining the levels (perhaps using `base::paste()` or `base::format()`).
`trained`	A logical to indicate if the quantities for preprocessing have been estimated.
`levels`	A list of values that will be used as the levels. These are the numeric data converted to character and ordered. This is `NULL` until computed by `prep.recipe()`.
`ordered`	A single logical value; should the factor(s) be ordered?
`skip`	A logical. Should the step be skipped when the recipe is baked by `bake.recipe()`? While all operations are baked when `prep.recipe()` is run, some operations may not be able to be conducted on new data (e.g. processing the outcome variable(s)). Care should be taken when using `skip = TRUE` as it may affect the computations for subsequent operations
`x`	A `step_num2factor` object.

Value

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 (the selectors or variables selected) and ordered.

Note

If bake is used on a data set where a new value is in the column being converted, bake will silently give values of NA to these rows (see the example below).

Examples

iris2 <- iris
iris2$Species <- as.numeric(iris2$Species)

rec <- recipe(~ ., data = iris2)

make_factor <- rec %>% step_num2factor(Species)
make_factor <- prep(make_factor,
                    training = iris2,
                    retain = TRUE)

# note that `diet` is a factor
juice(make_factor) %>% head
okc %>% head
tidy(make_factor, number = 1)

# When novel values are exposed
with_transform <- rec %>%
  step_num2factor(Species, transform = function(x) paste0("val_", x))

with_transform <- prep(with_transform,
                       training = iris2[1:75,])
new_values <- bake(with_transform, newdata = iris2, Species)
table(new_values[["Species"]], iris2$Species, useNA = "ifany")

[Package recipes version 0.1.3 Index]