code: def get_docs_categories():
      documents = [
          "What art thou that usurp'st this time of night,",
          "Together with that fair and warlike form",
          "In which the majesty of buried Denmark",
          "Did sometimes march? by heaven I charge thee, speak!",
          "Halt! Who goes there?",
          "[Intro]",
          "It is I sire Tone from Brooklyn.",
          "Well, speak up man what is it?",
          "News from the East sire! THE BEST OF BOTH WORLDS HAS RETURNED!",
      ]
      categories = ["hamlet"] * 4 + ["jay-z/r. kelly"] * 5
      return categories, documents
  
imports: import re
  from unittest import TestCase
  import pandas
  from sklearn.feature_extraction.text import TfidfTransformer
  from sklearn.linear_model import PassiveAggressiveClassifier
  from scattertext import CorpusFromParsedDocuments
  from scattertext import FeatsFromSpacyDoc, FeatsFromSpacyDocAndEmpath
  from scattertext import TermDocMatrixFactory
  from scattertext.TermDocMatrixFactory import FeatsFromDoc
  from scattertext.WhitespaceNLP import whitespace_nlp, Doc, Tok
label_desc: Use image node_id 7 for calling a global function with example usage: get_docs_categories() and returns: categories,  documents