class_docstr: Cohen's d scores
  
  term_scorer = (CohensD(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)
class_docstr_tok: ["Cohen","'s","d","scores","term_scorer","=","(","CohensD","(","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",")"]
docstr: :param correction_method: str or None, correction method from statsmodels.stats.multitest.multipletests
   'fdr_bh' is recommended.
  :return: pd.DataFrame
docstr_tok: [":","param","correction_method",":","str","or","None",",","correction","method","from","statsmodels.stats.multitest.multipletests","'fdr_bh","'","is","recommended",".",":","return",":","pd.DataFrame"]
code: def get_score_df(self, correction_method=None):
      """
  
      :param correction_method: str or None, correction method from statsmodels.stats.multitest.multipletests
       'fdr_bh' is recommended.
      :return: pd.DataFrame
      """
      # From https://people.kth.se/~lang/Effect_size.pdf
      # Shinichi Nakagawa1 and Innes C. Cuthill. Effect size, confidence interval and statistical
      # significance: a practical guide for biologists. 2007. In Biological Reviews 82.
      #
      # Modification: when calculating variance, an empty document is added to each set
      X = self._get_X().astype(np.float64)
      X_doc_len_norm = X / X.sum(axis=1)
      X_doc_len_norm[np.isnan(X_doc_len_norm)] = 0
      cat_X, ncat_X = self._get_cat_and_ncat(X_doc_len_norm)
      orig_cat_X, orig_ncat_X = self._get_cat_and_ncat(X)
      score_df = self.get_cohens_d_df(
          cat_X, ncat_X, orig_cat_X, orig_ncat_X, correction_method
      ).set_index(np.array(self._get_index()))
      score_df.index.name = "term"
      return score_df
  
file_path: scattertext/scattertext/termscoring/CohensD.py
imports: import numpy
  from scattertext.termscoring.CohensDCalculator import CohensDCalculator
  from scattertext.termscoring.CorpusBasedTermScorer import CorpusBasedTermScorer
label_desc: Use image node_id 3 for calling the CohensD obj's underlying member method code with example usage: obj.get_score_df(correction_method) and returns: score_df