docstr: :return: dict, maps category to count of tokens of all documents in that category
docstr_tok: [":","return",":","dict",",","maps","category","to","count","of","tokens","of","all","documents","in","that","category"]
code: def get_category_token_counts(self) -> Dict[str, int]:
      """
  
      :return: dict, maps category to count of tokens of all documents in that category
      """
  
      return dict(
          self.get_df()
          .groupby(self.get_category_column())
          .apply(
              lambda gdf: gdf[self.get_parsed_column()]
              .apply(
                  lambda doc: sum([t.orth_.strip() != "" for t in doc])
              )
              .sum()
          )
      )
  
imports: import sys
  from typing import Dict, Hashable
  import pandas
  from scattertext.DataFrameCorpus import DataFrameCorpus
  from scattertext.indexstore.IndexStore import IndexStore
label_desc: Use image node_id 4 for calling the ParsedDataFrameCorpus obj's underlying member method code with example usage: obj.get_category_token_counts() and returns: dict