你将不得不创建第二个groupby
对象,但是你可以以一种更简单的方式来计算百分比-仅groupby
计算state_office
并将该sales
列除以其和即可。复制Paul H答案的开头:
# From Paul H
import numpy as np
import pandas as pd
np.random.seed(0)
df = pd.DataFrame({'state': ['CA', 'WA', 'CO', 'AZ'] * 3,
'office_id': list(range(1, 7)) * 2,
'sales': [np.random.randint(100000, 999999)
for _ in range(12)]})
state_office = df.groupby(['state', 'office_id']).agg({'sales': 'sum'})
# Change: groupby state_office and divide by sum
state_pcts = state_office.groupby(level=0).apply(lambda x:
100 * x / float(x.sum()))
返回值:
sales
state office_id
AZ 2 16.981365
4 19.250033
6 63.768601
CA 1 19.331879
3 33.858747
5 46.809373
CO 1 36.851857
3 19.874290
5 43.273852
WA 2 34.707233
4 35.511259
6 29.781508