Pandas groupby using agg and apply at the same time

Question

I have the following dataframe:

df = pd.DataFrame({'id': [1,1,1,2,3,2], 'year': ['2020', '2014', '2002', '2020', '2016', '2014'], 'e': [True, False, True, True, False, True], 'val': [100,200,300, 200, 300, 200]})

id  year      e  val
0   1  2020   True  100
1   1  2014  False  200
2   1  2002   True  300
3   2  2020   True  200
4   3  2016  False  300
5   2  2014   True  200

And I want the following information:

df.groupby('id').apply(lambda x: x[x['e']]['year'].min())
id
1    2002
2    2014
3     NaN

And

df.groupby('id').val.sum()
id
1    600
2    400
3    300

My question is if it is possible to return both of these in the same group by? Or will I have to do separately and then merge?

Answer 1

I think using agg on direct column year and val is better than apply with pd.Series

df_final = df.groupby('id').agg({'year': lambda x: x[df.loc[x.index, 'e']].min(), 
                                 'val': 'sum'})

Out[347]:
    year  val
id
1   2002  600
2   2014  400
3    NaN  300