code: def word_summary_vc(
      vc: pd.Series, stop_words: List[str] = []
  ) -> dict:
      """Count the number of occurrences of each individual word across
      all lines of the data Series, then sort from the word with the most
      occurrences to the word with the least occurrences. If a list of
      stop words is given, they will be ignored.
  
      Args:
          vc: Series containing all unique categories as index and their
              frequency as value. Sorted from the most frequent down.
          stop_words: List of stop words to ignore, empty by default.
  
      Returns:
          A dict containing the results as a Series with unique words as
          index and the computed frequency as value
      """
      # TODO: configurable lowercase/punctuation etc.
      # TODO: remove punctuation in words
  
      series = pd.Series(vc.index, index=vc)
      word_lists = series.str.lower().str.split()
      words = word_lists.explode().str.strip(
          string.punctuation + string.whitespace
      )
      word_counts = pd.Series(words.index, index=words)
      # fix for pandas 1.0.5
      word_counts = word_counts[word_counts.index.notnull()]
      word_counts = word_counts.groupby(level=0, sort=False).sum()
      word_counts = word_counts.sort_values(ascending=False)
  
      # Remove stop words
      if len(stop_words) > 0:
          stop_words = [x.lower() for x in stop_words]
          word_counts = word_counts.loc[
              ~word_counts.index.isin(stop_words)
          ]
  
      return (
          {"word_counts": word_counts} if not word_counts.empty else {}
      )
  
file_path: ydata-profiling/src/ydata_profiling/model/pandas/describe_categorical_pandas.py
imports: import contextlib
  import string
  from collections import Counter
  from typing import List, Tuple
  import numpy
  import pandas
  from ydata_profiling.config import Settings
  from ydata_profiling.model.pandas.imbalance_pandas import column_imbalance_score
  from ydata_profiling.model.pandas.utils_pandas import weighted_median
  from ydata_profiling.model.summary_algorithms import chi_square, describe_categorical_1d, histogram_compute, series_handle_nulls, series_hashable
label_desc: Use image node_id 5 for calling a global function with example usage: word_summary_vc(vc, stop_words) and returns: unknown