将总计行添加到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()
答
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