code: def test_mixed_discretization():
      example_data = {
          "height": [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0],
          "weight": [
              60.0,
              70.0,
              70.0,
              80.0,
              80.0,
              80.0,
              90.0,
              90.0,
              90.0,
              90.0,
          ],
          "char": ["a", "b", "c", "d", "e", "f", "g", "h", "i", "j"],
      }
      example_df = pd.DataFrame(example_data)
  
      expected_labels = {
          "height": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
          "weight": [0, 1, 1, 3, 3, 3, 5, 5, 5, 5],
          "char": ["a", "b", "c", "d", "e", "f", "g", "h", "i", "j"],
      }
      expected_labels_df = pd.DataFrame(expected_labels)
      discretizer = Discretizer(
          method=DiscretizationType.UNIFORM, n_bins=10
      )
  
      cut_bins = discretizer.discretize_dataframe(example_df)
  
      assert (
          expected_labels_df.to_numpy().all()
          == cut_bins.to_numpy().all()
      )
  
imports: import pandas
  from ydata_profiling.model.pandas.discretize_pandas import DiscretizationType, Discretizer
label_desc: Use image node_id 3 for calling a global function with example usage: test_mixed_discretization() without return types