docstr: Test test_get_col_mapping_ce with target BaseNEncoder
docstr_tok: ["Test","test_get_col_mapping_ce","with","target","BaseNEncoder"]
code: def test_get_col_mapping_ce_5(self):
      """
      Test test_get_col_mapping_ce with target BaseNEncoder
      """
      test = pd.DataFrame(
          {
              "city": ["chicago", "paris", "chicago"],
              "state": ["US", "FR", "FR"],
              "other": ["A", np.nan, np.nan],
          }
      )
      y = pd.DataFrame(data=[0, 1, 1], columns=["y"])
  
      enc = ce.OneHotEncoder(cols=["city", "state"], use_cat_names=True)
      enc.fit(test, y)
  
      mapping = get_col_mapping_ce(enc)
      expected_mapping = {
          "city": ["city_chicago", "city_paris"],
          "state": ["state_US", "state_FR"],
      }
  
      self.assertDictEqual(mapping, expected_mapping)
  
imports: import unittest
  import pandas
  import numpy
  import category_encoders
  import catboost
  import lightgbm
  import xgboost
  from shapash.utils.transform import inverse_transform, apply_preprocessing, get_col_mapping_ce
  from sklearn.ensemble import GradientBoostingClassifier
label_desc: Use image node_id 39 for calling the TestInverseTransformCaterogyEncoder obj's underlying member method code with example usage: obj.test_get_col_mapping_ce_5() without return types