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.
code: def fit_label_encoders(self):
      labelencoders = {}
      for column in self.categorical_feature_names:
          labelencoders[column] = LabelEncoder()
          labelencoders[column] = labelencoders[column].fit(
              self.data_df[column]
          )
      return labelencoders
  
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 20 for calling the PublicData obj's underlying member method code with example usage: obj.fit_label_encoders() and returns: labelencoders