pandas 如何按一列分组并对另一列的值进行排序？
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How to group by one column and sort the values of another column?
提问by user1700890
Here is my dataframe
这是我的数据框
import pandas as pd
df = pd.DataFrame({'A': ['one', 'one', 'two', 'two', 'one'] ,
'B': ['Ar', 'Br', 'Cr', 'Ar','Ar'] ,
'C': ['12/15/2011', '11/11/2001', '08/30/2015', '07/3/1999','03/03/2000' ],
'D':[1,7,3,4,5]})
My goal is to group by column Aand sort within grouped results by column B.
我的目标是按列A分组并按列对分组结果进行排序B。
Here is what I came up with:
这是我想出的：
sort_group = df.sort_values('B').groupby('A')
I was hoping that grouping operation would not distort order, but it does not work and also returns not a dataframe, but groupbyobject
我希望分组操作不会扭曲顺序，但它不起作用并且返回的不是数据帧，而是groupby对象
<pandas.core.groupby.DataFrameGroupBy object at 0x0000000008B190B8>
Any suggestions?
有什么建议？
回答by Cleb
You cannot apply sort_valuesdirectly to a groupbyobject but you need an apply:
您不能sort_values直接应用于groupby对象，但您需要一个apply：
df.groupby('A').apply(lambda x: x.sort_values('B'))
gives you the desired output:
为您提供所需的输出：
A B C D
A
one 0 one Ar 12/15/2011 1
4 one Ar 03/03/2000 5
1 one Br 11/11/2001 7
two 3 two Ar 07/3/1999 4
2 two Cr 08/30/2015 3
