ValueError: Number of labels=712 does not match number of samples=713

안녕하세요. 타이타닉 부분 공부하고 있는데요.

교차검증 관련해서 이런 에러가 나네요.

코드는 그대로 작성한거 같은데요.

from sklearn.model_selection import KFold

def exec_kfold(clf, folds=5):

    kfold = KFold(n_splits=folds)

    scores = []

    for iter_count, (train_index, test_index) in enumerate(kfold.split(X_titanic_df)):

        X_train, X_test = X_titanic_df.values[train_index], X_titanic_df.values[test_index]

        Y_train, y_test = y_titanic_df.values[train_index], y_titanic_df.values[test_index]

        clf.fit(X_train, y_train)

        predictions = clf.predict(X_test)

        accuracy = accuracy_score(y_test, predictions)

        scores.append(accuracy)

        print("교차 검증 {0} 정확도: {1:.4f}".format(iter_count, accuracy))

    mean_score = np.mean(scores)

    print("평균 정확도: {0:.4f}".format(mean_score))

exec_kfold(dt_clf, folds=5)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-26-299d8b191409> in <module>
     17     mean_score = np.mean(scores)
     18     print("평균 정확도: {0:.4f}".format(mean_score))
---> 19 exec_kfold(dt_clf, folds=5)

<ipython-input-26-299d8b191409> in exec_kfold(clf, folds)
      9         Y_train, y_test = y_titanic_df.values[train_index], y_titanic_df.values[test_index]
     10 
---> 11         clf.fit(X_train, y_train)
     12         predictions = clf.predict(X_test)
     13         accuracy = accuracy_score(y_test, predictions)

~/opt/anaconda3/lib/python3.7/site-packages/sklearn/tree/_classes.py in fit(self, X, y, sample_weight, check_input, X_idx_sorted)
    875             sample_weight=sample_weight,
    876             check_input=check_input,
--> 877             X_idx_sorted=X_idx_sorted)
    878         return self
    879 

~/opt/anaconda3/lib/python3.7/site-packages/sklearn/tree/_classes.py in fit(self, X, y, sample_weight, check_input, X_idx_sorted)
    263         if len(y) != n_samples:
    264             raise ValueError("Number of labels=%d does not match "
--> 265                              "number of samples=%d" % (len(y), n_samples))
    266         if not 0 <= self.min_weight_fraction_leaf <= 0.5:
    267             raise ValueError("min_weight_fraction_leaf must in [0, 0.5]")

ValueError: Number of labels=712 does not match number of samples=713