将总计行添加到pandas DataFrame groupby [英] Adding total row to pandas DataFrame groupby

问题描述

我知道此链接，但是我没有设法解决我的问题.

I am aware of this link but I didn't manage to solve my problem.

我在pandas.DataFrame.groupby().sum()的DataFrame下面有这个标签:

I have this below DataFrame from pandas.DataFrame.groupby().sum():

                                                          Value
Level      Company         Item
    1            X            a                             100
                              b                             200
                 Y            a                              35
                              b                             150
                              c                              35
    2            X            a                              48
                              b                             100
                              c                              50
                 Y            a                              80

，并希望为我必须获得的每个索引级别添加总行:

and would like to add total rows for each level of index that I have to get:

                                                          Value
Level      Company         Item
    1            X            a                             100
                              b                             200
                          Total                             300
                 Y            a                              35
                              b                             150
                              c                              35
                          Total                             520
             Total                                          820
    2            X            a                              48
                              b                             100
                              c                              50
             Total                                          198
                 Y            a                              80
                          Total                              80
               Total                                        278
Total                                                      1098

根据要求

level = list(map(int, list('111112222')))
company = list('XXYYYXXXY')
item = list('ababcabca')
value = [100,200,35,150,35,48,100,50,80]
col = ['Level', 'Company', 'Item', 'Value']
df = pd.DataFrame([level,company,item,value]).T
df.columns = col
df.groupby(['Level', 'Company', 'Item']).sum()

推荐答案

您可以尝试一次将其堆叠一层:

You can try stacking it one level at a time:

m = df.groupby(['Level','Company','Item'])['Value'].sum().unstack(level=['Company','Item'])
m = m.assign(total=m.sum(1))
m = m.stack(level='Company')
m = m.assign(total=m.sum(1))
m = m.stack(level='Item')

输出总重复如下:

Level  Company  Item 
1      X        a        100.0
                b        200.0
                total    300.0
       Y        a         35.0
                b        150.0
                c         35.0
                total    220.0
       total             520.0
                total    520.0
2      X        a         48.0
                b        100.0
                c         50.0
                total    198.0
       Y        a         80.0
                total     80.0
       total             278.0
                total    278.0
dtype: float64

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