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tidymodels recipes: can I use step_dummy() to one-hot encode the categorical variabes *except* booleans which only needs 1 dummy?

If a categorical variable has more than 2 values (like marital status= single/married/widowed/separated/divorced), then I need to create N dummies, one for each of the possible levels. This is done using step_dummy(one_hot = TRUE).

However, if the category is binary (pokemon_fan = "yes"/"no") then I only need to create a single dummy called "pokemon_fan_yes". This is done using step_dummy(one_hot = FALSE).

Is it possible for step_dummy to count the number of levels and proceed differently depending on that number?

thanks.

Solution

  • There is no automatic way to do this within recipes itself, but I think you can create a function that will handle this for you, something like this:

    library(recipes)
#> Loading required package: dplyr
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
#> 
#> Attaching package: 'recipes'
#> The following object is masked from 'package:stats':
#> 
#>     step

data(crickets, package = "modeldata")

levels_more_than <- function(vec, num = 2) {
  n_distinct(levels(vec)) > num
}

recipe(~ ., data = crickets) %>%
  step_dummy(species, one_hot = !! levels_more_than(crickets$species)) %>%
  prep() %>%
  bake(new_data = NULL)
#> # A tibble: 31 × 3
#>     temp  rate species_O..niveus
#>    <dbl> <dbl>             <dbl>
#>  1  20.8  67.9                 0
#>  2  20.8  65.1                 0
#>  3  24    77.3                 0
#>  4  24    78.7                 0
#>  5  24    79.4                 0
#>  6  24    80.4                 0
#>  7  26.2  85.8                 0
#>  8  26.2  86.6                 0
#>  9  26.2  87.5                 0
#> 10  26.2  89.1                 0
#> # … with 21 more rows

recipe(~ ., data = iris) %>%
  step_dummy(Species, one_hot = !! levels_more_than(iris$Species)) %>%
  prep() %>%
  bake(new_data = NULL)
#> # A tibble: 150 × 7
#>    Sepal.Length Sepal.Width Petal.Length Petal.Width Species_setosa
#>           <dbl>       <dbl>        <dbl>       <dbl>          <dbl>
#>  1          5.1         3.5          1.4         0.2              1
#>  2          4.9         3            1.4         0.2              1
#>  3          4.7         3.2          1.3         0.2              1
#>  4          4.6         3.1          1.5         0.2              1
#>  5          5           3.6          1.4         0.2              1
#>  6          5.4         3.9          1.7         0.4              1
#>  7          4.6         3.4          1.4         0.3              1
#>  8          5           3.4          1.5         0.2              1
#>  9          4.4         2.9          1.4         0.2              1
#> 10          4.9         3.1          1.5         0.1              1
#> # … with 140 more rows, and 2 more variables: Species_versicolor <dbl>,
#> #   Species_virginica <dbl>

    Created on 2022-02-23 by the reprex package (v2.0.1)

    Here are some tips for using not-quite-standard selectors in recipes.