class_docstr: A data interface for public data. This class is an interface to DiCE explainers
  and contains methods to transform user-fed raw data into the format a DiCE explainer
  requires, and vice versa.
docstr: Gets the column indexes categorical features after one-hot-encoding.
code: def get_encoded_categorical_feature_indexes(self):
      """Gets the column indexes categorical features after one-hot-encoding."""
      cols = []
      for col_parent in self.categorical_feature_names:
          temp = [
              self.ohe_encoded_feature_names.index(col)
              for col in self.ohe_encoded_feature_names
              if col.startswith(col_parent)
              and col not in self.continuous_feature_names
          ]
          cols.append(temp)
      return cols
  
imports: import logging
  from collections import defaultdict
  import numpy
  import pandas
  from raiutils.exceptions import UserConfigValidationException
  from sklearn.preprocessing import LabelEncoder
  from dice_ml.data_interfaces.base_data_interface import _BaseData
  from dice_ml.utils.exception import SystemException
label_desc: Use image node_id 18 for calling the PublicData obj's underlying member method code with example usage: obj.get_encoded_categorical_feature_indexes() and returns: cols