How to write for loop?

[scidam]

model = XGBClassifier()
np.random.seed(32) # this makes results reproducible; comment this line if needed
accuracies = []
for counter in range(100):
    X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.3) # if random_state parameter is removed, train_test_split will use random seed value from the numpy package
    model.fit(X_train, y_train)
    y_pred = model.predict(X_test)
    accuracy = accuracy_score(y_test, y_pred.round())
    accuracies.append(accuracy)
print('Total number of splittings: ', len(accuracies), 'Mean accuracy score: ', np.mean(accuracies), 'std.dev.: ', np.std(accuracies))