docstr: test get_preprocessing_mapping with multiple encoding and dictionary
docstr_tok: ["test","get_preprocessing_mapping","with","multiple","encoding","and","dictionary"]
code: def test_get_preprocessing_mapping_1(self):
      """
      test get_preprocessing_mapping with multiple encoding and dictionary
      """
      enc = ColumnTransformer(
          transformers=[
              ("onehot_ce", ce.OneHotEncoder(), ["city", "state"]),
              ("onehot_skp", skp.OneHotEncoder(), ["city", "state"]),
          ],
          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))
  
      input_dict1 = dict()
      input_dict1["col"] = "onehot_ce_city"
      input_dict1["mapping"] = pd.Series(
          data=["chicago", "paris"], index=["CH", "PR"]
      )
      input_dict1["data_type"] = "object"
  
      input_dict2 = dict()
      input_dict2["col"] = "other"
      input_dict2["mapping"] = pd.Series(
          data=["A", "B", "C"], index=["A-B", "A-B", "C"]
      )
      input_dict2["data_type"] = "object"
  
      input_dict3 = dict()
      input_dict3["col"] = "onehot_ce_state"
      input_dict3["mapping"] = pd.Series(
          data=["US", "FR"], index=["US-FR", "US-FR"]
      )
      input_dict3["data_type"] = "object"
      list_dict = [input_dict2, input_dict3]
  
      test_encoded.columns = [
          "col1_0",
          "col1_1",
          "col2_0",
          "col2_1",
          "col3_0",
          "col3_1",
          "col4_0",
          "col4_1",
      ]
  
      mapping = get_preprocessing_mapping(
          test_encoded, [enc, input_dict1, list_dict]
      )
  
      expected_mapping = {
          "onehot_ce_city": ["col1_0", "col1_1"],
          "onehot_ce_state": ["col2_0", "col2_1"],
          "onehot_skp_city": ["col3_0", "col3_1"],
          "onehot_skp_state": ["col4_0", "col4_1"],
      }
      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 1 for calling the TestInverseTransformCaterogyEncoder obj's underlying member method code with example usage: obj.test_get_preprocessing_mapping_1() without return types