code: def test_data_c_discrete(test_data_c) -> pd.DataFrame:
      """Test data C that has been discretised (see train_data_discrete)"""
      df = test_data_c.copy(deep=True)  # type: pd.DataFrame
      df["c"] = df["c"].apply(
          lambda c: 0
          if c < 20
          else 1
          if c < 40
          else 2
          if c < 60
          else 3
          if c < 80
          else 4
      )
      return df
  
imports: import itertools
  from typing import Dict
  import numpy
  import pandas
  import pytest
  from pgmpy.models import BayesianNetwork
  from sklearn.datasets import load_iris
  from causalnex.discretiser import Discretiser
  from causalnex.network import BayesianNetwork
  from causalnex.structure import StructureModel
  from causalnex.structure.notears import from_pandas
label_desc: Use image node_id 14 for calling a global function with example usage: test_data_c_discrete(test_data_c) and returns: df