code: def get_score_df(self):
      data = {}
      X = self._get_X() > 0
      y = self.corpus_.get_category_ids()
      for cat_i, cat in enumerate(self.corpus_.get_categories()):
          n_cat_is = [
              x
              for x in range(len(self.corpus_.get_categories()))
              if x != cat_i
          ]
          (
              tp,
              fp,
              pos,
              neg,
              tpr,
              fpr,
              invn_tpr,
              invn_fpr,
          ) = self._get_bns_score_for_category_index(
              cat_i, n_cat_is, X, y
          )
          data[cat + " BNS"] = invn_tpr - invn_fpr
          data[cat + " TP"] = tp
          data[cat + " FP"] = fp
          data[cat + " POS"] = pos
          data[cat + " NEG"] = neg
          data[cat + " TPR"] = tpr
          data[cat + " FPR"] = fpr
          data[cat + " INTPR"] = invn_tpr
          data[cat + " INFPR"] = invn_fpr
      return pd.DataFrame(data, index=self._get_index())
  
file_path: scattertext/scattertext/termscoring/BNSScorer.py
imports: import pandas
  import numpy
  from scipy.stats import norm
  from scattertext.termscoring.CorpusBasedTermScorer import CorpusBasedTermScorer
label_desc: Use image node_id 2 for calling the BNSScorer obj's underlying member method code with example usage: obj.get_score_df() and returns: pd