tests/testthat/_snaps/dummy_extract.md

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

error when neither sep or pattern is specified

Code
  recipe(~medium, data = tate_text) %>% step_dummy_extract(medium) %>% prep()
Condition
  Error in `step_dummy_extract()`:
  Caused by error in `prep()`:
  ! `sep` or `pattern` must be specified.

check_name() is used

Code
  prep(rec, training = dat)
Condition
  Error in `step_dummy_extract()`:
  Caused by error in `bake()`:
  ! Name collision occurred. The following variable names already exist:
  * `Species_setosa`

case weights

Code
  dummy_prepped
Message

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

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

  -- Training information 
  Training data contained 4 data points and no incomplete rows.

  -- Operations 
  * Extract patterns from: medium | Trained, weighted

Code
  dummy_prepped
Message

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

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

  -- Training information 
  Training data contained 4 data points and no incomplete rows.

  -- Operations 
  * Extract patterns from: medium | Trained, ignored weights

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

Code
  bake(dummy_prepped, new_data = mini_tate[, 1:3])
Condition
  Error in `step_dummy_extract()`:
  ! The following required column is missing from `new_data`: medium.

empty printing

Code
  rec
Message

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

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

  -- Operations 
  * Extract patterns from: <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 
  * Extract patterns from: <none> | Trained

keep_original_cols - can prep recipes with it missing

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

printing

Code
  print(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 1

  -- Operations 
  * Extract patterns from: all_predictors()

Code
  prep(rec)
Message

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

  -- Inputs 
  Number of variables by role
  predictor: 1

  -- Training information 
  Training data contained 4284 data points and no incomplete rows.

  -- Operations 
  * Extract patterns from: medium | Trained

bad args

Code
  recipe(~colors, data = color_examples) %>% step_dummy_extract(colors, pattern = "(?<=')[^',]+(?=')",
    other = 2) %>% prep()
Condition
  Error in `step_dummy_extract()`:
  Caused by error in `prep()`:
  ! `other` must be a single string or `NULL`, not the number 2.

Code
  recipe(~colors, data = color_examples) %>% step_dummy_extract(colors, pattern = "(?<=')[^',]+(?=')",
    other = 2) %>% prep()
Condition
  Error in `step_dummy_extract()`:
  Caused by error in `prep()`:
  ! `other` must be a single string or `NULL`, not the number 2.

Code
  recipe(~colors, data = color_examples) %>% step_dummy_extract(colors, pattern = "(?<=')[^',]+(?=')",
    sep = 2) %>% prep()
Condition
  Error in `step_dummy_extract()`:
  Caused by error in `prep()`:
  ! `sep` must be a single string or `NULL`, not the number 2.

Code
  recipe(~colors, data = color_examples) %>% step_dummy_extract(colors, pattern = 2) %>%
    prep()
Condition
  Error in `step_dummy_extract()`:
  Caused by error in `prep()`:
  ! `pattern` must be a single string or `NULL`, not the number 2.

Code
  recipe(~colors, data = color_examples) %>% step_dummy_extract(colors, pattern = "(?<=')[^',]+(?=')",
    naming = NULL) %>% prep()
Condition
  Error in `step_dummy_extract()`:
  Caused by error in `prep()`:
  ! `naming` must be a function, not `NULL`.

tidymodels/recipes documentation built on Jan. 25, 2025, 7:30 a.m.