How to aggregate multiple columns in pandas groupby

Question

I have created a pandas dataframe mn using following input:

keyA     state n1    n2     d1  d2
key1     CA   100   1000    1   2
key2     FL   200   2000             


        

Answer 1

Pretty much just write it like your pseudocode.

In [14]: s = mn.groupby(['keyA','state'], as_index=False).sum()

In [15]: s['v1'] = s['n1'] / s['d1']

In [16]: s['v2'] = s['n2'] / s['d2']

In [17]: s[['keyA', 'state', 'v1', 'v2']]
Out[17]: 
   keyA state   v1           v2
0  key1    AL  100   500.000000
1  key1    CA  100   500.000000
2  key1    NY  100  1500.000000
3  key2    CA  100  1166.666667
4  key2    FL  100  1166.666667

[5 rows x 4 columns]

I think you have a typo in your example data by the way. The second n1 header should be n2.