count.md
In recipes: Preprocessing and Feature Engineering Steps for Modeling

bad selector(s)

Code
  rec %>% step_count(description, rows, pattern = "(rock|stony)")
Condition
  Error in `step_count()`:
  ! For this step, only a single selector can be used.

Code
  prep(rec2, training = covers)
Condition
  Error in `step_count()`:
  Caused by error in `prep()`:
  ! All columns selected for the step should be string, factor, or ordered.

check_name() is used

Code
  prep(rec, training = dat)
Condition
  Error in `step_count()`:
  Caused by error in `bake()`:
  ! Name collision occured. The following variable names already exists:
  i  Sepal.Width

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * Regular expression counts using: <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 
  * Regular expression counts using: <none> | Trained

keep_original_cols - can prep recipes with it missing

Code
  rec <- prep(rec)
Condition
  Warning:
  'keep_original_cols' was added to `step_count()` after this recipe was created.
  Regenerate your recipe to avoid this warning.

printing

Code
  print(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 3

  -- Operations 
  * Regular expression counts using: description

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 3

  -- Training information 
  Training data contained 40 data points and no incomplete rows.

  -- Operations 
  * Regular expression counts using: description | Trained