How to combine multiple columns in pandas groupby

Question

I created a pandas mn data file using the following input:

keyA state n1 n2 d1 d2 key1 CA 100 1000 1 2 key2 FL 200 2000 2 4 key1 CA 300 3000 3 6 key1 AL 400 4000 4 8 key2 FL 500 5000 5 2 key1 NY 600 6000 6 4 key2 CA 700 7000 7 6 

Created an amount object as follows:

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

How to iterate over a sum s object, so I can get the following output:

Column v1 in the result below is calculated as s['n1']/s['d1']

Column v2 in the result below is calculated as s['n2']/s['d2']

 keyA state v1 v2 'key1','AL',100,500 'key1','CA',100,500 'key1','NY',100,1500 'key2','CA',100,1166 'key2','FL',100,1166 

Answer 1

Pretty much just write it as your pseudo code.

 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 examples, by the way. The second header n1 must be n2 .