code: def create_iris_data(append_special_characters=False):
      """Create Iris dataset for classification.
  
      param append_special_characters: Whether to append special characters
          to feature names.
      type append_special_characters: bool
      return: Tuple of X_train, X_test, y_train, y_test, feature_names, classes.
      rtype: Tuple of pandas.DataFrame, pandas.DataFrame, numpy.ndarray,
             numpy.ndarray, list, list
      """
      # Import Iris dataset
      iris = load_iris()
      # Split data into train and test
      X_train, X_test, y_train, y_test = train_test_split(
          iris.data, iris.target, test_size=0.2, random_state=0
      )
      feature_names = [
          name.replace(
              " (cm)", "-" if append_special_characters else ""
          )
          for name in iris.feature_names
      ]
  
      X_train = pd.DataFrame(X_train, columns=feature_names)
      X_test = pd.DataFrame(X_test, columns=feature_names)
      classes = iris.target_names
      return X_train, X_test, y_train, y_test, feature_names, classes
  
file_path: responsible-ai-toolbox/rai_test_utils/rai_test_utils/datasets/tabular/classification_data_utils.py
imports: import numpy
  import pandas
  import shap
  from pandas import read_csv
  from sklearn.datasets import load_breast_cancer, load_iris, load_wine, make_classification
  from sklearn.model_selection import train_test_split
  from rai_test_utils.utilities import retrieve_dataset
label_desc: Use image node_id 1 for calling a global function with example usage: create_iris_data(append_special_characters) and returns: X_train,  X_test,  y_train,  y_test,  feature_names,  classes