code: def test_multi_label_binarizer(self):
      g = graphistry.nodes(
          bad_df
      )  # can take in a list of lists and convert to multiOutput
      with warnings.catch_warnings():
          warnings.filterwarnings("ignore", category=UserWarning)
          g2 = g.featurize(y=["list_str"], X=["src"], multilabel=True)
      y = g2._get_target("node")
      assert y.shape == (4, 4)
      assert sum(y.sum(1).values - np.array([1.0, 2.0, 1.0, 0.0])) == 0
  
imports: import datetime
  import graphistry
  import logging
  import numpy
  import pandas
  from typing import Any
  import pytest
  import unittest
  import warnings
  from graphistry.feature_utils import process_dirty_dataframes, process_nodes_dataframes, resolve_feature_engine, lazy_import_has_min_dependancy, lazy_import_has_dependancy_text, FastEncoder
  from graphistry.features import topic_model, ngrams_model
  from graphistry.constants import SCALERS
label_desc: Use image node_id 3 for calling the TestFeatureProcessors obj's underlying member method code with example usage: obj.test_multi_label_binarizer() without return types