Tricky aggregation using pandas

pandas, python

Solution

More or less what @DSM was saying:

In [3]: grouped = df.groupby('game_id')

In [4]: won = grouped.won.sum()

In [5]: DataFrame({True: won, False: grouped.person.nunique() - won}).stack()
Out[5]: 
game_id       
2        False    1
         True     1
3        False    0
         True     2
4        False    1
         True     0
dtype: float64

Problem

Am new to pandas and curious if this is too tricky to accomplish using it. Example input: ``` time person game_id won ----------------------------------- 12:34:01 John 3 False 12:34:04 Ringo 2 True 12:35:05 John 3 False 12:36:01 John 3 True 12:36:12 Ringo 3 True 12:36:41 Paul 4 False 12:37:01 George 2 False 12:37:41 George 2 False ``` It shows a number of persons playing a number of games over time. The won column indicates if the person won or not at that time. What I want as output is how many people won each game at least once. But also how many people played the game and never won. Example Output: ``` game_id won count ----------------------- 2 True 1 False 1 3 True 2 False 0 4 True 0 False 1 ```

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