from sklearn.model_selection import train_test_split

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33)

"""Étape facultative (mais souvent utile) : normaliser les données"""

#from sklearn.preprocessing import MinMaxScaler
#scaler = MinMaxScaler()

#scaler.fit(X_train)
#X_train = scaler.transform(X_train)

#scaler.fit(X_test)
#X_test = scaler.transform(X_test)