docstr: test get_col_mapping_ct with ordinal Encoder sklearn and drop option
docstr_tok: ["test","get_col_mapping_ct","with","ordinal","Encoder","sklearn","and","drop","option"]
code: def test_get_col_mapping_ct_7(self):
      """
      test get_col_mapping_ct with ordinal Encoder sklearn and drop option
      """
      enc = ColumnTransformer(
          transformers=[
              ("ordinal", skp.OrdinalEncoder(), ["city", "state"])
          ],
          remainder="drop",
      )
  
      y = pd.DataFrame(
          data=[0, 1, 1],
          columns=["y"],
          index=["index1", "index2", "index3"],
      )
      test = pd.DataFrame(
          {
              "city": ["chicago", "new york", "paris"],
              "state": ["US", "FR", "FR"],
              "other": ["A", "B", "C"],
          },
          index=["index1", "index2", "index3"],
      )
  
      test_encoded = pd.DataFrame(enc.fit_transform(test, y))
      mapping = get_col_mapping_ct(enc, test_encoded)
      expected_mapping = {"ordinal_city": [0], "ordinal_state": [1]}
  
      self.assertDictEqual(mapping, expected_mapping)
  
imports: import unittest
  import pandas
  import numpy
  import category_encoders
  from sklearn.compose import ColumnTransformer
  import sklearn.preprocessing
  import catboost
  import sklearn
  import lightgbm
  import xgboost
  from shapash.utils.transform import inverse_transform
  from shapash.utils.transform import apply_preprocessing
  from shapash.utils.columntransformer_backend import get_feature_names, get_names, get_list_features_names, get_col_mapping_ct
  from sklearn.ensemble import GradientBoostingClassifier
label_desc: Use image node_id 41 for calling the TestInverseTransformColumnsTransformer obj's underlying member method code with example usage: obj.test_get_col_mapping_ct_7() without return types