Multiple aggregations of the same column using pandas GroupBy.agg()

Question

Is there a pandas built-in way to apply two different aggregating functions f1, f2 to the same column df[\"returns\"], without having to call

Answer 1

You can simply pass the functions as a list:

In [20]: df.groupby("dummy").agg({"returns": [np.mean, np.sum]})
Out[20]:         
           mean       sum
dummy                    
1      0.036901  0.369012

or as a dictionary:

In [21]: df.groupby('dummy').agg({'returns':
                                  {'Mean': np.mean, 'Sum': np.sum}})
Out[21]: 
        returns          
           Mean       Sum
dummy                    
1      0.036901  0.369012