code: def as_dataframe(self, fillna=True, subjects=None):
          
          entries = []
          selected_subjects = self.subjects
          if subjects is not None:
              selected_subjects = subjects
              
          for s in selected_subjects:
              vmap = {}
              for c in self.inferred_types(s):
                  vmap[c] = 1
              entries.append(vmap)
          logging.debug("Creating DataFrame")
          df = pd.DataFrame(entries, index=selected_subjects)
          if fillna:
              logging.debug("Performing fillna...")
              df = df.fillna(0)
          return df
docs: Return association set as pandas DataFrame
  
          Each row is a subject (e.g. gene)
          Each column is the inferred class used to describe the subject