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()`:
  x All columns selected for the step should be double or integer.
  * 1 factor 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`

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.

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