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: Transforms label encoded data back to categorical values
code: def from_label(self, data):
      """Transforms label encoded data back to categorical values"""
      out = data.copy()
      if isinstance(data, pd.DataFrame) or isinstance(data, dict):
          for column in self.categorical_feature_names:
              out[column] = self.labelencoder[column].inverse_transform(
                  out[column].round().astype(int).tolist()
              )
          return out
      elif isinstance(data, list):
          for c in self.categorical_feature_indexes:
              out[c] = self.labelencoder[
                  self.feature_names[c]
              ].inverse_transform([round(out[c])])[0]
          return out
  
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 21 for calling the PublicData obj's underlying member method code with example usage: obj.from_label(data) and returns: out, out