如何按一列分组并排序另一列的值? [英] How to group by one column and sort the values of another column?

问题描述

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]})

我的目标是按列A分组，并按列B在分组的结果内排序.

My goal is to group by column A and sort within grouped results by column B.

这是我想出的:

sort_group = df.sort_values('B').groupby('A')

我希望分组操作不会扭曲顺序，但是它不起作用，也不会返回数据帧，而是返回groupby对象

I was hoping that grouping operation would not distort order, but it does not work and also returns not a dataframe, but groupby object

<pandas.core.groupby.DataFrameGroupBy object at 0x0000000008B190B8>

有什么建议吗?

推荐答案

您不能将sort_values直接应用于groupby对象，但是需要apply:

You cannot apply sort_values directly to a groupby object but you need an apply:

df.groupby('A').apply(lambda x: x.sort_values('B'))

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

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