Let's say I have the following data:
df=pd.DataFrame({'Days':[1,2,3,4,1,2,3,4],
'Flag':["First","First","First","First","Second","Second","Second","Second"],
'Payments':[1,2,3,4,9,3,1,6]})
I want to create a cumulative sum for payments, but it has to reset when flag turns from first to second. Any help?
You can use df['Flag'].ne(df['Flag'].shift()).cumsum()
to generate a grouper that will group by changes in the Flag
column. Then, group by that, and cumsum
:
df['cumsum'] = df['Payments'].groupby(df['Flag'].ne(df['Flag'].shift()).cumsum()).cumsum()
Output:
>>> df
Days Flag Payments cumsum
0 1 First 1 1
1 2 First 2 3
2 3 First 3 6
3 4 First 4 10
4 1 Second 9 9
5 2 Second 3 12
6 3 Second 1 13
7 4 Second 6 19