在 pandas 的多索引级别内按列排序 [英] Sort by column within multi index level in pandas

问题描述

我在下面的每个示例中都有一个排序请求.

I have a sorting request per example below.

我需要reset_index()，然后sort()然后set_index()，还是有一种巧妙的方法呢?

Do i need to reset_index(), then sort() and then set_index() or is there a slick way to do this?

l = [[1,'A',99],[1,'B',102],[1,'C',105],[1,'D',97],[2,'A',19],[2,'B',14],[2,'C',10],[2,'D',17]]
df = pd.DataFrame(l,columns = ['idx1','idx2','col1'])
df.set_index(['idx1','idx2'],inplace=True)

# assume data has been received like this...
print df

           col1
idx1 idx2      
1    A       99
     B      102
     C      105
     D       97
2    A       19
     B       14
     C       10
     D       17

# I'd like to sort descending on col1, partitioning within index level = 'idx2'

           col1
idx1 idx2      
1    C      105
     B      102
     A       99
     D       97

2    A       19
     D       17
     B       14
     C       10

---

谢谢您的回答 请注意，我会略微更改数据:

---

Thank you for the answer Note I change the data slightly:

l = [[1,'A',99],[1,'B',11],[1,'C',105],[1,'D',97],[2,'A',19],[2,'B',14],[2,'C',10],[2,'D',17]]
df = pd.DataFrame(l,columns = ['idx1','idx2','col1'])
df.set_index(['idx1','idx2'],inplace=True)
df = df.sort_index(by='col1', ascending=False)

但是输出是

idx1 idx2      
1    C      105
     A       99
     D       97
2    A       19
     D       17
     B       14
1    B       11
2    C       10

我本来希望成为

idx1 idx2      
1    C      105
     A       99
     D       97
     B       11

2    A       19
     D       17
     B       14
     C       10

推荐答案

您可以使用sort_index:

 df.sort_index(by='col1', ascending=False)

这将输出:

             col1
idx1    idx2    
1       C    105
        B    102
        A    99
        D    97
2       A    19
        D    17
        B    14
        C    10

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