Need help with finding the reason why for loop outputs only 1s. When I delete the loop, it works just fine, outputting reasonable data, but within the loop, every row of created df is 1. Why is that?

def bootstrap(x, Nboot):

    x = np.array(x)

    models = []
    resampled_stat = []
    precision = []
    recall = []
    f1 = []

    numb_rows = len(data)

    for k in range(Nboot):
        chosen_rows = np.random.choice(numb_rows, replace=True, size=numb_rows)
        bootstrap_sample = data.iloc[chosen_rows]

        resampled_stat.append(bootstrap_sample)

        X_train, X_test, Y_train, Y_test = train_test_split(x, y, test_size = 0.2, random_state = 1)

        model = tree.DecisionTreeClassifier().fit(X_train, Y_train)

        models.append(model)

        y_pred = model.predict(X_test)

        precision.append(metrics.precision_score(Y_test, y_pred, average="macro"))
        recall.append(metrics.recall_score(Y_test, y_pred, average="macro"))
        f1.append(metrics.f1_score(Y_test, y_pred, average="macro"))

    pred_df = pd.DataFrame(
        {
            "Precision": precision,
            "Recall": recall,
            "F1": f1,
            "Models": models,
        })   
    
    return pred_df