code: def gen_stratified_test_data(draw):
      column_name_strategy = st.text(
          st.characters(whitelist_categories=["Lu", "Ll"]), min_size=3
      )
      all_column_names = draw(
          st.lists(
              column_name_strategy, min_size=3, max_size=6, unique=True
          )
      )
      target_column_name = all_column_names[-1]
  
      column_strategies = columns(all_column_names, dtype=int)
      data_set = draw(
          data_frames(
              column_strategies,
              index=range_indexes(min_size=50, max_size=100),
          )
      )
  
      num_classes = draw(st.integers(min_value=2, max_value=5))
      data_set[target_column_name] = [
          i % num_classes for i in range(len(data_set))
      ]
  
      return data_set, target_column_name, num_classes
  
file_path: fklearn/tests/preprocessing/test_splitting.py
imports: from collections import Counter
  import hypothesis.strategies
  import pandas
  from hypothesis import given
  from hypothesis.extra.pandas import columns, data_frames, range_indexes
  from pandas.testing import assert_frame_equal
  from fklearn.preprocessing.splitting import space_time_split_dataset, time_split_dataset, stratified_split_dataset
label_desc: Use image node_id 3 for calling a global function with example usage: gen_stratified_test_data(draw) and returns: data_set,  target_column_name,  num_classes