docstr: test inverse_transform having missing and No Unknown
docstr_tok: ["test","inverse_transform","having","missing","and","No","Unknown"]
code: def test_inverse_transform_23(self):
      """
      test inverse_transform having missing and No Unknown
      """
      train = pd.DataFrame({"city": ["chicago", np.nan]})
      test = pd.DataFrame({"city": ["chicago", "los angeles"]})
      enc = ce.OneHotEncoder(
          handle_missing="value", handle_unknown="return_nan"
      )
      enc.fit(train)
      result = enc.transform(test)
      original = inverse_transform(result, enc)
      pd.testing.assert_frame_equal(train, original)
  
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 23 for calling the TestInverseTransformCaterogyEncoder obj's underlying member method code with example usage: obj.test_inverse_transform_23() without return types