code: def get_rank_freq_df(self) -> pd.DataFrame:
      if self.term_scorer_ is None:
          raise Exception("Ensure the corpus has been set.")
      # freq_df = self.term_ranker_.use_non_text_features(self.non_text_).get_ranks(label_append='')
      freq_df = self.term_ranker_.set_non_text(
          self.non_text_
      ).get_ranks(label_append="")
      if self.non_text_:
          self.term_scorer_ = self.term_scorer_.use_metadata()
      dfs = []
      for category in self.corpus_.get_categories():
          cat_df = pd.DataFrame(
              {
                  "Score": self.term_scorer_.set_categories(
                      str(category)
                  )
                  .get_scores()
                  .sort_values(ascending=False),
                  "Category": category,
              }
          )
          cat_df.index = cat_df.index.rename("Term")
          cat_df = cat_df.reset_index().assign(
              Rank=lambda df: np.arange(len(df), dtype=int),
              Frequency=lambda df: freq_df.loc[
                  df.Term.values, str(category)
              ].values,
          )
          dfs.append(cat_df)
  
      return pd.concat(dfs).reset_index(drop=True)
  
file_path: scattertext/scattertext/all_category_scorers/all_category_term_scorer.py
imports: import abc
  from typing import Dict, Optional
  import pandas
  import numpy
  from scattertext.termscoring.RankDifferenceScorer import RankDifferenceScorer
  from scattertext.termscoring.CorpusBasedTermScorer import CorpusBasedTermScorer
  from scattertext.all_category_scorers.all_category_scorer import AllCategoryScorer
label_desc: Use image node_id 3 for calling the AllCategoryTermScorer obj's underlying member method code with example usage: obj.get_rank_freq_df() and returns: pd