sklearn莺尾花数据集洗牌操作报错

问题遇到的现象和发生背景

机器学习，在对莺尾花数据进行洗牌操作时报错

问题相关代码，请勿粘贴截图

from sklearn.datasets import fetch_openml
mnist = fetch_openml('mnist_784')
mnist
X, y = mnist["data"],mnist["target"]

# 构造训练集和测试集，分别取前6万和后1万
X_train, X_test, y_train, y_test = X[:60000], X[60000:], y[:60000], y[60000:]
# 洗牌操作
import numpy as np
shuffle_index = np.random.permutation(60000)
X_train, y_train = X_train[shuffle_index], y_train[shuffle_index]

运行结果及报错内容

C:\Users\ADMINI~1\AppData\Local\Temp/ipykernel_4680/859505846.py in <module>
      3 
      4 shuffle_index = np.random.permutation(60000)
----> 5 X_train, y_train = X_train[shuffle_index], y_train[shuffle_index]

D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\frame.py in __getitem__(self, key)
   3462             if is_iterator(key):
   3463                 key = list(key)
-> 3464             indexer = self.loc._get_listlike_indexer(key, axis=1)[1]
   3465 
   3466         # take() does not accept boolean indexers

D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in _get_listlike_indexer(self, key, axis)
   1312             keyarr, indexer, new_indexer = ax._reindex_non_unique(keyarr)
   1313 
-> 1314         self._validate_read_indexer(keyarr, indexer, axis)
   1315 
   1316         if needs_i8_conversion(ax.dtype) or isinstance(

D:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py in _validate_read_indexer(self, key, indexer, axis)
   1372                 if use_interval_msg:
   1373                     key = list(key)
-> 1374                 raise KeyError(f"None of [{key}] are in the [{axis_name}]")
   1375 
   1376             not_found = list(ensure_index(key)[missing_mask.nonzero()[0]].unique())

KeyError: "None of [Int64Index([30014, 20704, 39358, 59901, 34204, 33490, 47212, 42902, 35485,\n            56263,\n            ...\n            58028, 34403, 33149, 17932, 18264, 29486,  7317, 16650, 46800,\n             7085],\n           dtype='int64', length=60000)] are in the [columns]"

我的解答思路和尝试过的方法

搜索了一下，没有找到理想的解决方法

我想要达到的结果

对数据集进行洗牌操作成功