code: def test_discretize_uniform():
      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,
          ],
      }
      example_df = pd.DataFrame(example_data)
  
      expected_labels = {
          "height": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
          "weight": [0, 3, 3, 6, 6, 6, 9, 9, 9, 9],
      }
      expected_labels_df = pd.DataFrame(expected_labels)
      discretizer = Discretizer(
          method=DiscretizationType.QUANTILE, 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 2 for calling a global function with example usage: test_discretize_uniform() without return types