tests/testthat/_snaps/cut.md

In tidymodels/recipes: Preprocessing and Feature Engineering Steps for Modeling

step_cut throws error on non-numerics

Code
  recipe(x) %>% step_cut(cat_var, breaks = 2) %>% prep()
Condition
  Error in `step_cut()`:
  Caused by error in `prep()`:
  x All columns selected for the step should be double or integer.
  * 1 string variable found: `cat_var`

Code
  recipe(~., x) %>% step_cut(all_predictors(), breaks = 2) %>% prep()
Condition
  Error in `step_cut()`:
  Caused by error in `prep()`:
  x All columns selected for the step should be double or integer.
  * 1 factor variable found: `cat_var`

Code
  recipe(~., x) %>% step_cut(num_var, breaks = 2, include_outside_range = 2) %>%
    prep()
Condition
  Error in `step_cut()`:
  Caused by error in `prep()`:
  ! `include_outside_range` must be `TRUE` or `FALSE`, not the number 2.

full_breaks_check will give warnings

Code
  full_breaks_check(10)
Condition
  Error:
  ! Variable is invariant and equal to break point.

Code
  full_breaks_check(c(10, 20))
Condition
  Warning:
  This will create a factor with one value only.

breaks argument are type checked

Code
  recipe(~., data = mtcars) %>% step_cut(disp, hp, breaks = TRUE) %>% prep()
Condition
  Error in `step_cut()`:
  Caused by error in `prep()`:
  ! `breaks` must be a numeric vector, not `TRUE`.

Code
  recipe(~., data = mtcars) %>% step_cut(disp, hp, breaks = c("100", "200")) %>%
    prep()
Condition
  Error in `step_cut()`:
  Caused by error in `prep()`:
  ! `breaks` must be a numeric vector, not a character vector.

bake method errors when needed non-standard role columns are missing

Code
  bake(prepped, df[, 2, drop = FALSE])
Condition
  Error in `step_cut()`:
  ! The following required column is missing from `new_data`: x.

empty printing

Code
  rec
Message

  -- Recipe ----------------------------------------------------------------------

  -- Inputs 
  Number of variables by role
  outcome:    1
  predictor: 10

  -- Operations 
  * Cut numeric for: <none>

Code
  rec
Message

  -- Recipe ----------------------------------------------------------------------

  -- Inputs 
  Number of variables by role
  outcome:    1
  predictor: 10

  -- Training information 
  Training data contained 32 data points and no incomplete rows.

  -- Operations 
  * Cut numeric for: <none> | Trained

printing

Code
  print(rec)
Message

  -- Recipe ----------------------------------------------------------------------

  -- Inputs 
  Number of variables by role
  outcome:    1
  predictor: 10

  -- Operations 
  * Cut numeric for: disp

Code
  prep(rec)
Message

  -- Recipe ----------------------------------------------------------------------

  -- Inputs 
  Number of variables by role
  outcome:    1
  predictor: 10

  -- Training information 
  Training data contained 32 data points and no incomplete rows.

  -- Operations 
  * Cut numeric for: disp | Trained

tidymodels/recipes documentation built on Jan. 25, 2025, 7:30 a.m.