cut.md
In 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()`:
  ! All columns selected for the step should be double, or integer.

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

full_breaks_check will give warnings

Code
  full_breaks_check(10)
Condition
  Error in `full_breaks_check()`:
  ! In step_cut: variable is invariant and equal to break point.

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

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