code: def df_discretise():
      np.random.seed(42)
      mu1, sigma1 = 0, 3
      s1 = np.random.normal(mu1, sigma1, 20)
      mu2, sigma2 = 3, 5
      s2 = np.random.normal(mu2, sigma2, 20)
      data = {
          "var_A": s1,
          "var_B": s2,
          "target": [
              0,
              1,
              1,
              0,
              1,
              0,
              0,
              0,
              0,
              1,
              1,
              1,
              1,
              1,
              1,
              0,
              1,
              1,
              1,
              1,
          ],
      }
  
      df = pd.DataFrame(data)
  
      return df
  
file_path: feature_engine/tests/test_discretisation/test_decision_tree_discretiser.py
imports: import numpy
  import pandas
  import pytest
  from sklearn.exceptions import NotFittedError
  from feature_engine.discretisation import DecisionTreeDiscretiser, EqualWidthDiscretiser
label_desc: Use image node_id 6 for calling a global function with example usage: df_discretise() and returns: df