Pandas percentage of total with groupby

Question

This is obviously simple, but as a numpy newbe I\'m getting stuck.

I have a CSV file that contains 3 columns, the State, the Office ID, and the Sales for that office

Answer 1

For conciseness I'd use the SeriesGroupBy:

In [11]: c = df.groupby(['state', 'office_id'])['sales'].sum().rename("count")

In [12]: c
Out[12]:
state  office_id
AZ     2            925105
       4            592852
       6            362198
CA     1            819164
       3            743055
       5            292885
CO     1            525994
       3            338378
       5            490335
WA     2            623380
       4            441560
       6            451428
Name: count, dtype: int64

In [13]: c / c.groupby(level=0).sum()
Out[13]:
state  office_id
AZ     2            0.492037
       4            0.315321
       6            0.192643
CA     1            0.441573
       3            0.400546
       5            0.157881
CO     1            0.388271
       3            0.249779
       5            0.361949
WA     2            0.411101
       4            0.291196
       6            0.297703
Name: count, dtype: float64

For multiple groups you have to use transform (using Radical's df):

In [21]: c =  df.groupby(["Group 1","Group 2","Final Group"])["Numbers I want as percents"].sum().rename("count")

In [22]: c / c.groupby(level=[0, 1]).transform("sum")
Out[22]:
Group 1  Group 2  Final Group
AAHQ     BOSC     OWON           0.331006
                  TLAM           0.668994
         MQVF     BWSI           0.288961
                  FXZM           0.711039
         ODWV     NFCH           0.262395
...
Name: count, dtype: float64

This seems to be slightly more performant than the other answers (just less than twice the speed of Radical's answer, for me ~0.08s).