code: def _generate_categorical_data(num_samples=1000):
      x = np.random.normal(0, 1, num_samples)
      z = []
      for v in x:
          if v > 0:
              z.append(0)
          else:
              z.append(1)
      y = z + np.random.randn(len(z))
      z = np.array(z).astype(str)
      z[z == "0"] = "Class 1"
      z[z == "1"] = "Class 2"
  
      return x, y, z
  
imports: import random
  import numpy
  import pytest
  from flaky import flaky
  from dowhy.gcm.independence_test import approx_kernel_based, kernel_based
label_desc: Use image node_id 22 for calling a global function with example usage: _generate_categorical_data(num_samples) and returns: x,  y,  z