code: def remove_single_char_and_spaces(
      text_docs_bow: Iterable[Iterable[str]],
  ) -> Iterable[Iterable[str]]:
      """Removes all words that contain only one character and blank spaces from documents.
  
      Args:
          text_docs_bow: A list of lists of words from a document
  
      Returns:
          A generator expression for all of the processed documents
      """
      new_docs = []
      for doc in text_docs_bow:
          new_doc = []
          for word in doc:
              new_word = word.strip()
              if " " in new_word:
                  new_words = new_word.split()
                  for item in new_words:
                      new_doc.append(item)
              elif len(new_word) > 1:
                  new_doc.append(new_word)
          new_docs.append(new_doc)
      return (doc for doc in new_docs)
  
imports: import re
  import string
  import warnings
  from types import GeneratorType
  from typing import List, Optional, Any, Iterable, TYPE_CHECKING
  import pandas
  from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
  from data_describe.text import text_preprocessing
  from data_describe.compat import _requires, _compat
label_desc: Use image node_id 5 for calling a global function with example usage: remove_single_char_and_spaces(text_docs_bow) and returns: unknown