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Pipeable steps for feature engineering and data preprocessing to prepare for modeling
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feature request: `step_cut` does not match results from `dplyr::mutate(var = cut(var,n))` when `n` is an integer #1398

Open jkylearmstrong opened 10 hours ago

jkylearmstrong commented 10 hours ago

feature-request

It took me a minute to realize the behavior of step_cut is different than that of cut.

The functionality of step_cut expects explicit breaks whereas cut will generate intervals when a single integer value is provided in breaks. 

library('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
library('tidymodels')
tidymodels_prefer()

df <- data.frame(x = c(1:10,31:40), y = 1:20)

rec3 <- recipe(df) %>%
  step_mutate(x_cut = x) %>%
  step_cut(x_cut, breaks = 3, include_outside_range = T) %>%
  prep()

tidy(rec3, 2)
#> # A tibble: 3 × 3
#>   terms value id       
#>   <chr> <dbl> <chr>    
#> 1 x_cut     1 cut_5ea2R
#> 2 x_cut     3 cut_5ea2R
#> 3 x_cut    40 cut_5ea2R

bake(rec3, new_data = df) %>%
  mutate(dplyr_cut = cut(x,3, include.lowest = TRUE))
#> # A tibble: 20 × 4
#>        x     y x_cut   dplyr_cut 
#>    <int> <int> <fct>   <fct>     
#>  1     1     1 [min,3] [0.961,14]
#>  2     2     2 [min,3] [0.961,14]
#>  3     3     3 [min,3] [0.961,14]
#>  4     4     4 (3,max] [0.961,14]
#>  5     5     5 (3,max] [0.961,14]
#>  6     6     6 (3,max] [0.961,14]
#>  7     7     7 (3,max] [0.961,14]
#>  8     8     8 (3,max] [0.961,14]
#>  9     9     9 (3,max] [0.961,14]
#> 10    10    10 (3,max] [0.961,14]
#> 11    31    11 (3,max] (27,40]   
#> 12    32    12 (3,max] (27,40]   
#> 13    33    13 (3,max] (27,40]   
#> 14    34    14 (3,max] (27,40]   
#> 15    35    15 (3,max] (27,40]   
#> 16    36    16 (3,max] (27,40]   
#> 17    37    17 (3,max] (27,40]   
#> 18    38    18 (3,max] (27,40]   
#> 19    39    19 (3,max] (27,40]   
#> 20    40    20 (3,max] (27,40]
Created on 2024-11-19 with [reprex v2.1.1](https://reprex.tidyverse.org/)

Perhaps an option for n_breaks to the step_cut option, could also exist for vectors or named lists and just apply the vector, named list to the list of variables 

# psuedo code for step_cut_n_breaks
step_cut_n_breaks <- function(var, n_breaks, include_outside_range) {
  var_min <- min(var)
  var_max <- max(var)

  diff <- (var_max - var_min)/n_cut_breaks 

  res_seq <- seq(
    var_min,
    var_max,
    by = diff
  )

  res_seq <- res_seq[-1]
  res_seq <- res_seq[-length(resl_seq)]

  # Once the ranges have been computed you could still use the existing step_cut functionality: 
  step_cut(force_cuts, breaks = res_seq, include_outside_range  = include_outside_range) 
}