Python 如何在pandas中将一列拆分为两列？

我有一个像这样的数据集，我想把它转换成两列

df1 

    x   y   z
house           
0   4.907   1.416   0.663
0   2.114   1.368   0.681
0   1.261   1.374   0.724
1   1.382   1.480   0.767
1   2.764   1.390   0.661
1   1.410   0.941   0.665
2   1.362   1.498   0.775
2   1.303   0.786   0.682
2   2.687   1.445   0.675
3   1.341   0.932   0.685
3   1.436   1.450   0.748
3   2.466   1.272   0.686
4   1.299   1.072   0.692
4   1.457   1.504   0.748
4   2.296   1.246   0.663
5   1.390   0.918   0.700
5   1.405   1.587   0.817
5   2.482   1.394   0.656
6   1.445   1.116   0.746
6   2.184   1.474   0.710
6   1.319   1.524   0.722

我想换成这个

House   cluster x   y   z
summer  0   4.907   1.416   0.663
        0   2.114   1.368   0.681
        0   1.261   1.374   0.724
Autumn  1   1.382   1.480   0.767
        1   2.764   1.390   0.661
        1   1.410   0.941   0.665
Winter  2   1.362   1.498   0.775
        2   1.303   0.786   0.682
        2   2.687   1.445   0.675

我试图引用此代码，但它显示了一个错误。我想知道我应该找哪个关键字来查找这个案例

 Length mismatch: Expected axis has 15 elements, new values have 3 elements

我相信您需要按列表索引，按列表长度进行模除：

names = ['Summer', 'Autumn', 'Winter', 'Spring']
arr = np.asarray(names)
A.index = pd.MultiIndex.from_arrays([arr[A.index % len(names)], A.index], names=['a','b'])
print (A)
              x      y      z
a      b                     
Summer 0  4.907  1.416  0.663
       0  2.114  1.368  0.681
       0  1.261  1.374  0.724
Autumn 1  1.382  1.480  0.767
       1  2.764  1.390  0.661
       1  1.410  0.941  0.665
Winter 2  1.362  1.498  0.775
       2  1.303  0.786  0.682
       2  2.687  1.445  0.675
Spring 3  1.341  0.932  0.685
       3  1.436  1.450  0.748
       3  2.466  1.272  0.686
Summer 4  1.299  1.072  0.692
       4  1.457  1.504  0.748
       4  2.296  1.246  0.663
Autumn 5  1.390  0.918  0.700
       5  1.405  1.587  0.817
       5  2.482  1.394  0.656
Winter 6  1.445  1.116  0.746
       6  2.184  1.474  0.710
       6  1.319  1.524  0.722

---

季节从哪里来？

names = ['Summer', 'Autumn', 'Winter', 'Spring']
arr = np.asarray(names)
A.index = pd.MultiIndex.from_arrays([arr[A.index % len(names)], A.index], names=['a','b'])
print (A)
              x      y      z
a      b                     
Summer 0  4.907  1.416  0.663
       0  2.114  1.368  0.681
       0  1.261  1.374  0.724
Autumn 1  1.382  1.480  0.767
       1  2.764  1.390  0.661
       1  1.410  0.941  0.665
Winter 2  1.362  1.498  0.775
       2  1.303  0.786  0.682
       2  2.687  1.445  0.675
Spring 3  1.341  0.932  0.685
       3  1.436  1.450  0.748
       3  2.466  1.272  0.686
Summer 4  1.299  1.072  0.692
       4  1.457  1.504  0.748
       4  2.296  1.246  0.663
Autumn 5  1.390  0.918  0.700
       5  1.405  1.587  0.817
       5  2.482  1.394  0.656
Winter 6  1.445  1.116  0.746
       6  2.184  1.474  0.710
       6  1.319  1.524  0.722