我正在尝试按帐户计算累计收入。以下是一些示例数据：
import pandas as pd
data = {
'account_id': ['111','111','111','222','222','333','333','333','666','666'],
'company': ['initech','initech','initech','jackson steinem & co','jackson steinem & co','ingen','ingen','ingen','enron','enron'],
'cohort_period': [0,1,2,0,1,0,1,2,0,1],
'revenue':[3.67,9.95,9.95,193.29,299.95,83.03,499.95,99.95,1.52,19.95]
}
df = pd.DataFrame(data)
哪个输出：
In [17]: df
Out[17]:
account_id cohort_period company revenue
0 111 0 initech 3.67
1 111 1 initech 9.95
2 111 2 initech 9.95
3 222 0 jackson steinem & co 193.29
4 222 1 jackson steinem & co 299.95
5 333 0 ingen 83.03
6 333 1 ingen 499.95
7 333 2 ingen 99.95
8 666 0 enron 1.52
9 666 1 enron 19.95
有关如何执行此操作的示例很多，基本上是：
df['cumulative_revenue'] = df.groupby('account_id')['revenue'].cumsum()
但是，这里有个问题：在此数据中，同类群组第0期的收入按比例分配，出于我的分析目的，我并不在意。我需要在同类群组1开始累计金额。例如，Initech的累计收入应如下所示：
0 nan
1 9.95
2 19.90
最佳答案
这是一种方法：
# check valid cohort_period
valid_cohort = df.cohort_period.ne(0)
# cumulative sum revenue where cohort_period is not equal to zero and mask otherwise as nan
df['cum_revenue'] = valid_cohort.mul(df.revenue).groupby(df.account_id).cumsum().where(valid_cohort)
print(df)
# account_id cohort_period company revenue cum_revenue
#0 111 0 initech 3.67 NaN
#1 111 1 initech 9.95 9.95
#2 111 2 initech 9.95 19.90
#3 222 0 jackson steinem & co 193.29 NaN
#4 222 1 jackson steinem & co 299.95 299.95
#5 333 0 ingen 83.03 NaN
#6 333 1 ingen 499.95 499.95
#7 333 2 ingen 99.95 599.90
#8 666 0 enron 1.52 NaN
#9 666 1 enron 19.95 19.95
关于python - 在 Pandas 中转移Groupby，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/47193386/