docstr: Removes any special columns from dataset added prior to filtering.
  
  :param df: The filtered dataset, converted to a pandas DataFrame.
  :type: pandas.DataFrame
  :param include_original_columns_only: Whether to just include
                                        the original data columns.
  :type include_original_columns_only: bool
  :return: The post-processed pandas DataFrame, with special columns
           removed.
  :rtype: pandas.DataFrame
docstr_tok: ["Removes","any","special","columns","from","dataset","added","prior","to","filtering",".",":","param","df",":","The","filtered","dataset",",","converted","to","a","pandas","DataFrame",".",":","type",":","pandas.DataFrame",":","param","include_original_columns_only",":","Whether","to","just","include","the","original","data","columns",".",":","type","include_original_columns_only",":","bool",":","return",":","The","post-processed","pandas","DataFrame",",","with","special","columns","removed",".",":","rtype",":","pandas.DataFrame"]
code: def _post_process_df(self, df, include_original_columns_only=False):
      """Removes any special columns from dataset added prior to filtering.
  
      :param df: The filtered dataset, converted to a pandas DataFrame.
      :type: pandas.DataFrame
      :param include_original_columns_only: Whether to just include
                                            the original data columns.
      :type include_original_columns_only: bool
      :return: The post-processed pandas DataFrame, with special columns
               removed.
      :rtype: pandas.DataFrame
      """
      if CLASSIFICATION_OUTCOME in list(df.columns):
          df = df.drop(columns=CLASSIFICATION_OUTCOME)
      if REGRESSION_ERROR in list(df.columns):
          df = df.drop(columns=REGRESSION_ERROR)
      if include_original_columns_only:
          if PRED_Y in list(df.columns):
              df = df.drop(columns=PRED_Y)
          if ROW_INDEX in list(df.columns):
              df = df.drop(columns=ROW_INDEX)
          if TRUE_Y in list(df.columns):
              df = df.drop(columns=TRUE_Y)
      return df
  
file_path: responsible-ai-toolbox/erroranalysis/erroranalysis/_internal/cohort_filter.py
imports: from typing import Any, List, Optional
  import numpy
  import pandas
  from erroranalysis._internal.constants import ARG, COLUMN, COMPOSITE_FILTERS, METHOD, OPERATION, PRED_Y, ROW_INDEX, TRUE_Y, CohortFilterMethods, CohortFilterOps, ModelTask
  from erroranalysis._internal.metrics import get_ordered_classes
  from erroranalysis._internal.utils import is_spark
label_desc: Use image node_id 9 for calling the FilterDataWithCohortFilters obj's underlying member method code with example usage: obj._post_process_df(df, include_original_columns_only) and returns: df