Assuming i have the following data frame
date | flag | user | num | |
---|---|---|---|---|
0 | 2019-01-01 | 1 | a | 10 |
1 | 2019-01-02 | 0 | a | 20 |
2 | 2019-01-03 | 1 | b | 30 |
3 | 2019-03-04 | 1 | b | 40 |
I want to create a cumulative sum of the nums grouped by user only if flag == 1 so i will get this:
date | flag | user | num | cumsum | |
---|---|---|---|---|---|
0 | 2019-01-01 | 1 | a | 10 | 10 |
1 | 2019-01-02 | 0 | a | 20 | 10 |
2 | 2019-01-03 | 1 | b | 30 | 30 |
3 | 2019-03-04 | 1 | b | 40 | 70 |
So far i was able to cumsum by flag, disregarding the group by user
df['cumsum'] = df[df['flag'] == 1 ]['num'].transform(pd.Series.cumsum)
or cumsum by user disregarding the flag
df['cumsum'] = df.groupby('user')['num'].transform(pd.Series.cumsum)
I need help making them work together.