code: def iris_test_data() -> pd.DataFrame:
      """
      Iris dataset to test sklearn wrappers
      """
      iris = load_iris()
      X, y = iris["data"], iris["target"]
      names = iris["feature_names"]
      df = pd.DataFrame(X, columns=names)
      df["type"] = y
      df["sepal length (cm)"] = Discretiser(
          method="quantile", num_buckets=3
      ).fit_transform(df["sepal length (cm)"].values)
      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 25 for calling a global function with example usage: iris_test_data() and returns: df