Summarize a recipe

This function prints the current set of variables/features and some of their characteristics.

Usage

# S3 method for recipe
summary(object, original = FALSE, ...)

Arguments

object

A recipe object

original

A logical: show the current set of variables or the original set when the recipe was defined.

...

further arguments passed to or from other methods (not currently used).

Value

A tibble with columns variable, type, role, and source. When original = TRUE, an additional column is included named required_to_bake (based on the results of update_role_requirements()).

Details

Note that, until the recipe has been trained, the current and original variables are the same.

It is possible for variables to have multiple roles by adding them with add_role(). If a variable has multiple roles, it will have more than one row in the summary tibble.

See also

recipe() prep()

Examples

rec <- recipe(~., data = USArrests)
summary(rec)
#> # A tibble: 4 × 4
#>   variable type      role      source  
#>   <chr>    <list>    <chr>     <chr>   
#> 1 Murder   <chr [2]> predictor original
#> 2 Assault  <chr [2]> predictor original
#> 3 UrbanPop <chr [2]> predictor original
#> 4 Rape     <chr [2]> predictor original
rec <- step_pca(rec, all_numeric(), num_comp = 3)
summary(rec) # still the same since not yet trained
#> # A tibble: 4 × 4
#>   variable type      role      source  
#>   <chr>    <list>    <chr>     <chr>   
#> 1 Murder   <chr [2]> predictor original
#> 2 Assault  <chr [2]> predictor original
#> 3 UrbanPop <chr [2]> predictor original
#> 4 Rape     <chr [2]> predictor original
rec <- prep(rec, training = USArrests)
summary(rec)
#> # A tibble: 3 × 4
#>   variable type      role      source 
#>   <chr>    <list>    <chr>     <chr>  
#> 1 PC1      <chr [2]> predictor derived
#> 2 PC2      <chr [2]> predictor derived
#> 3 PC3      <chr [2]> predictor derived