What are standarization and normalization? Test with iris data set in Scikit-learn

decision_boundary.py

from sklearn.model_selection import train_test_split

def decision_boundary(df, clf, ax):
    X = df.iloc[:, [0, 2]] 
    y = df['target']
    X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=39)
    clf.fit(X_train, y_train)
    print('Classifier: {}'.format(clf))
    print('Test set score: {:.2f}'.format(clf.score(X_test, y_test)))
    
    ret = X.to_numpy()
    mglearn.plots.plot_2d_separator(clf, ret, fill=True, eps=0.5, ax=ax, alpha=.4)
    mglearn.discrete_scatter(ret[:, 0], ret[:, 1], y.to_numpy(), ax=ax)