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

bad values

Code
  sacr_rec %>% step_profile(everything(), profile = vars(sqft)) %>% prep(data = Sacramento)
Condition
  Error in `step_profile()`:
  Caused by error in `prep()`:
  ! The profiled variable cannot be in the list of variables to be fixed.

Code
  sacr_rec %>% step_profile(sqft, beds, price, profile = vars(zip, beds)) %>%
    prep(data = Sacramento)
Condition
  Error in `step_profile()`:
  Caused by error in `prep()`:
  ! Only one variable should be profiled

Code
  sacr_rec %>% step_profile(city, profile = vars(sqft), pct = -1) %>% prep(data = Sacramento)
Condition
  Error in `step_profile()`:
  ! `pct should be on [0, 1]`

Code
  sacr_rec %>% step_profile(city, profile = vars(sqft), grid = 1:3) %>% prep(
    data = Sacramento)
Condition
  Error in `step_profile()`:
  ! `grid` should have two named elements. See ?step_profile

Code
  sacr_rec %>% step_profile(city, profile = vars(sqft), grid = list(pctl = 1,
    len = 2)) %>% prep(data = Sacramento)
Condition
  Error in `step_profile()`:
  ! `grid$pctl should be logical.`

Code
  fixed(rep(c(TRUE, FALSE), each = 5))
Condition
  Error in `error_cnd()`:
  ! Conditions must have named data fields

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * Profiling data set for: mpg

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 
  * Profiling data set for: mpg | Trained

printing

Code
  print(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 10

  -- Operations 
  * Profiling data set for: sqft

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 10

  -- Training information 
  Training data contained 20 data points and no incomplete rows.

  -- Operations 
  * Profiling data set for: sqft | Trained