docstr: test get_preprocessing_mapping with multiple encoding and drop option
docstr_tok: ["test","get_preprocessing_mapping","with","multiple","encoding","and","drop","option"]
code: def test_get_preprocessing_mapping_2(self):
      """
      test get_preprocessing_mapping with multiple encoding and drop option
      """
      enc = ColumnTransformer(
          transformers=[
              ("onehot_ce", ce.OneHotEncoder(), ["city", "state"]),
              ("ordinal_skp", skp.OrdinalEncoder(), ["city"]),
          ],
          remainder="drop",
      )
      test = pd.DataFrame(
          {
              "city": ["chicago", "chicago", "paris"],
              "state": ["US", "FR", "FR"],
              "other": ["A", "B", "C"],
          },
          index=["index1", "index2", "index3"],
      )
  
      test_encoded = pd.DataFrame(enc.fit_transform(test))
      test_encoded.columns = [
          "col1_0",
          "col1_1",
          "col2_0",
          "col2_1",
          "col3",
      ]
  
      mapping = get_preprocessing_mapping(test_encoded, enc)
  
      expected_mapping = {
          "onehot_ce_city": ["col1_0", "col1_1"],
          "onehot_ce_state": ["col2_0", "col2_1"],
          "ordinal_skp_city": ["col3"],
      }
      self.assertDictEqual(mapping, expected_mapping)
  
file_path: shapash/tests/unit_tests/utils/test_transform.py
imports: import unittest
  import pandas
  import numpy
  from sklearn.compose import ColumnTransformer
  import sklearn.preprocessing
  import category_encoders
  from shapash.utils.transform import get_preprocessing_mapping, get_features_transform_mapping, handle_categorical_missing
  from pandas.testing import assert_frame_equal
label_desc: Use image node_id 2 for calling the TestInverseTransformCaterogyEncoder obj's underlying member method code with example usage: obj.test_get_preprocessing_mapping_2() without return types