code: def test_random_under_sampling_heterogeneous_data():
      X_hetero = np.array(
          [["xxx", 1, 1.0], ["yyy", 2, 2.0], ["zzz", 3, 3.0]],
          dtype=object,
      )
      y = np.array([0, 0, 1])
      rus = RandomUnderSampler(random_state=RND_SEED)
      X_res, y_res = rus.fit_resample(X_hetero, y)
  
      assert X_res.shape[0] == 2
      assert y_res.shape[0] == 2
      assert X_res.dtype == object
  
file_path: imbalanced-learn/imblearn/under_sampling/_prototype_selection/tests/test_random_under_sampler.py
imports: from collections import Counter
  from datetime import datetime
  import numpy
  import pytest
  from sklearn.datasets import make_classification
  from sklearn.utils._testing import assert_array_equal
  from imblearn.under_sampling import RandomUnderSampler
label_desc: Use image node_id 4 for calling a global function with example usage: test_random_under_sampling_heterogeneous_data() without return types