docstr: test inverse_transform with multiple ordinal
docstr_tok: ["test","inverse_transform","with","multiple","ordinal"]
code: def test_inverse_transform_10(self):
      """
      test inverse_transform with multiple ordinal
      """
      data = pd.DataFrame(
          {
              "city": ["chicago", "paris"],
              "state": ["US", "FR"],
              "other": ["a", "b"],
          }
      )
      test = pd.DataFrame(
          {
              "city": [1, 2, 2],
              "state": [1, 2, 2],
              "other": ["a", "b", "a"],
          }
      )
      expected = pd.DataFrame(
          {
              "city": ["chicago", "paris", "paris"],
              "state": ["US", "FR", "FR"],
              "other": ["a", "b", "a"],
          }
      )
      enc = ce.OrdinalEncoder(cols=["city", "state"])
      enc.fit(data)
      original = inverse_transform(test, enc)
      pd.testing.assert_frame_equal(original, expected)
  
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 10 for calling the TestInverseTransformCaterogyEncoder obj's underlying member method code with example usage: obj.test_inverse_transform_10() without return types