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

(This solution is inspired from this article https://pbpython.com/pandas_transform.html)

I find the following solution to be the simplest(and probably the fastest) using transformation:

Transformation: While aggregation must return a reduced version of the data, transformation can return some transformed version of the full data to recombine. For such a transformation, the output is the same shape as the input.

So using transformation, the solution is 1-liner:

df['%'] = 100 * df['sales'] / df.groupby('state')['sales'].transform('sum')

And if you print:

print(df.sort_values(['state', 'office_id']).reset_index(drop=True))

   state  office_id   sales          %
0     AZ          2  195197   9.844309
1     AZ          4  877890  44.274352
2     AZ          6  909754  45.881339
3     CA          1  614752  50.415708
4     CA          3  395340  32.421767
5     CA          5  209274  17.162525
6     CO          1  549430  42.659629
7     CO          3  457514  35.522956
8     CO          5  280995  21.817415
9     WA          2  828238  35.696929
10    WA          4  719366  31.004563
11    WA          6  772590  33.298509