Below you find a code snippet that loads the Iris dataset and splits it into two sets. Insert the code snippet in your code editor, create a classifier with random_state=42 and fit the classifier on the train data and find the score for the test data (by using clf.score()).
from sklearn.model_selection import train_test_split
from sklearn.datasets import load_iris
X, y = load_iris(return_X_y=True)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)