My grouped data looks like:
deviceid time total_sent
022009f075929be71975ce70db19cd47780b112f 1980-January 36 4
52 1
94 1
211 1
278 1
318 2
370 1
426 1
430 1
435 1
560 1
674 1
797 1
813 4
816 1
ff5b22df4ab9207bb6709cddef6d95c655565578 2013-August 11308408 4
12075616 1
17933654 1
22754808 12
22754987 1
22755166 3
22755345 4
22788586 4
22788765 2
22788944 2
22791830 1
22792546 1
22796843 1
22797201 2
22797380 2
Where the last column represents the count. I obtained this grouped representation using the expression:
data1.groupby(['deviceid', 'time', 'total_sent'])
How do I sum the total_sent per month?
deviceid time sum
022009f075929be71975ce70db19cd47780b112f 1980-January 6210
ff5b22df4ab9207bb6709cddef6d95c655565578 2013-August XXXX
Since total_sent column is to be summed, it shouldn't be within the groupby keys. You can try the following:
data1.groupby(['deviceid', 'time']).agg({'total_sent': sum})
which will sum the total_sent column for each group, indexed by deviceid and time.