code: def _make_political_corpus(self):
      clean = clean_function_factory()
      data = []
      for party, speech in iter_party_speech_pairs():
          cleaned_speech = clean(speech)
          if cleaned_speech and cleaned_speech != "":
              parsed_speech = whitespace_nlp(cleaned_speech)
              data.append({"party": party, "text": parsed_speech})
      corpus = CorpusFromParsedDocuments(
          pd.DataFrame(data), category_col="party", parsed_col="text"
      ).build()
      return corpus
  
imports: import json
  import os
  import pkgutil
  import re
  from unittest import TestCase
  import numpy
  import pandas
  from scattertext.ParsedCorpus import ParsedCorpus
  from scattertext.CorpusFromParsedDocuments import CorpusFromParsedDocuments
  from scattertext.WhitespaceNLP import whitespace_nlp
  from scattertext.TermDocMatrixFactory import TermDocMatrixFactory
  from scattertext.test.test_TermDocMat import get_hamlet_docs, get_hamlet_snippet_binary_category
  from scattertext.test.test_corpusFromPandas import get_docs_categories
label_desc: Use image node_id 3 for calling the TestCorpusFromParsedDocuments obj's underlying member method code with example usage: obj._make_political_corpus() and returns: corpus