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: De-normalizes continuous features from [0,1] range to original range.
code: def de_normalize_data(self, df):
      """De-normalizes continuous features from [0,1] range to original range."""
      if len(df) == 0:
          return df
      result = df.copy()
      for feature_name in self.continuous_feature_names:
          max_value = self.data_df[feature_name].max()
          min_value = self.data_df[feature_name].min()
          result[feature_name] = (
              df[feature_name] * (max_value - min_value)
          ) + min_value
      return result
  
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 10 for calling the PublicData obj's underlying member method code with example usage: obj.de_normalize_data(df) and returns: result, df