tests/testthat/_snaps/impute_mean.md

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

non-numeric

Code
  prep(impute_rec, training = credit_tr, verbose = FALSE)
Condition
  Error in `step_impute_mean()`:
  Caused by error in `prep()`:
  x All columns selected for the step should be double or integer.
  * 1 factor variable found: `Job`

case weights

Code
  impute_rec
Message

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

  -- Inputs 
  Number of variables by role
  outcome:       1
  predictor:    12
  case_weights:  1

  -- Training information 
  Training data contained 2000 data points and 186 incomplete rows.

  -- Operations 
  * Mean imputation for: Age, Assets, Income | Trained, weighted

Code
  impute_rec
Message

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

  -- Inputs 
  Number of variables by role
  outcome:       1
  predictor:    12
  case_weights:  1

  -- Training information 
  Training data contained 2000 data points and 186 incomplete rows.

  -- Operations 
  * Mean imputation for: Age, Assets, Income | Trained, ignored weights

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

Code
  bake(imputed, new_data = credit_te[, c(-5)])
Condition
  Error in `step_impute_mean()`:
  ! The following required column is missing from `new_data`: Age.

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * Mean imputation 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 
  * Mean imputation for: <none> | Trained

printing

Code
  print(rec)
Message

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

  -- Inputs 
  Number of variables by role
  outcome:    1
  predictor: 13

  -- Operations 
  * Mean imputation for: Age, Assets, Income

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  outcome:    1
  predictor: 13

  -- Training information 
  Training data contained 2000 data points and 186 incomplete rows.

  -- Operations 
  * Mean imputation for: Age, Assets, Income | Trained

bad args

Code
  recipe(~., data = mtcars) %>% step_impute_mean(all_predictors(), trim = 0.6) %>%
    prep()
Condition
  Error in `step_impute_mean()`:
  Caused by error in `prep()`:
  ! `trim` must be a number between 0 and 0.5, not the number 0.6.

tidymodels/recipes documentation built on Nov. 29, 2024, 3:05 p.m.