class_docstr: Z-scores from Welch's t-test
  
  term_scorer = (ZScores(corpus).set_categories('Positive', ['Negative'], ['Plot']))
  
  html = st.produce_frequency_explorer(
          corpus,
          category='Positive',
          not_categories=['Negative'],
          neutral_categories=['Plot'],
          term_scorer=term_scorer,
          metadata=rdf['movie_name'],
          grey_threshold=0,
          show_neutral=True
  )
  file_name = 'rotten_fresh_fre.html'
  open(file_name, 'wb').write(html.encode('utf-8'))
  IFrame(src=file_name, width=1300, height=700)
code: def get_scores(self, *args):
      return pd.Series(
          self.get_t_statistics()[0], index=self._get_index()
      )
  
imports: import pandas
  from scattertext.termscoring.CorpusBasedTermScorer import CorpusBasedTermScorer
label_desc: Use image node_id 2 for calling the ZScores obj's underlying member method code with example usage: obj.get_scores() and returns: pd