In [97]: df = pandas.DataFrame({'month': np.random.randint(0,11, 100), 'A': np.random.randn(100), 'B': np.random.randn(100)})
In [98]: df.join(df.groupby('month')['A'].sum(), on='month', rsuffix='_r')
Out[98]:
A B month A_r
0 -0.040710 0.182269 0 -0.331816
1 -0.004867 0.642243 1 2.448232
2 -0.162191 0.442338 4 2.045909
3 -0.979875 1.367018 5 -2.736399
4 -1.126198 0.338946 5 -2.736399
5 -0.992209 -1.343258 1 2.448232
6 -1.450310 0.021290 0 -0.331816
7 -0.675345 -1.359915 9 2.722156