[FIXED] Feature names from OneHotEncoder

Issue

I am using OneHotEncoder to encode few categorical variables (eg - Sex and AgeGroup). The resulting feature names from the encoder are like - 'x0_female', 'x0_male', 'x1_0.0', 'x1_15.0' etc.

>>> train_X = pd.DataFrame({'Sex':['male', 'female']*3, 'AgeGroup':[0,15,30,45,60,75]})

>>> from sklearn.preprocessing import OneHotEncoder
>>> encoder = OneHotEncoder()
>>> train_X_encoded = encoder.fit_transform(train_X[['Sex', 'AgeGroup']])

>>> encoder.get_feature_names()
>>> array(['x0_female', 'x0_male', 'x1_0.0', 'x1_15.0', 'x1_30.0', 'x1_45.0',
       'x1_60.0', 'x1_75.0'], dtype=object)

Is there a way to tell OneHotEncoder to create the feature names in such a way that the column name is added at the beginning, something like - Sex_female, AgeGroup_15.0 etc, similar to what Pandas get_dummies() does.

Solution

A list with the original column names can be passed to get_feature_names.

>>> encoder.get_feature_names(['Sex', 'AgeGroup'])

array(['Sex_female', 'Sex_male', 'AgeGroup_0', 'AgeGroup_15',
       'AgeGroup_30', 'AgeGroup_45', 'AgeGroup_60', 'AgeGroup_75'],
      dtype=object)

• DEPRECATED: get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.
  • As per sklearn.preprocessing.OneHotEncoder.

>>> encoder.get_feature_names_out(['Sex', 'AgeGroup'])

array(['Sex_female', 'Sex_male', 'AgeGroup_0', 'AgeGroup_15',
       'AgeGroup_30', 'AgeGroup_45', 'AgeGroup_60', 'AgeGroup_75'],
      dtype=object)

Answered By - kabochkov