How to transform raw data to fixed-frequency time series?
This sort of effect can be achieved with 
pandas.DataFrame.resample() combined with Resampler.aggregate() like:

Code:

df.resample("1Min").agg({'A': sum, 'B': np.mean})


Test code:

df = pd.read_fwf(StringIO(u"""
                           A    B
    2017-01-01T00:01:01    0    100
    2017-01-01T00:01:10    1    200
    2017-01-01T00:01:16    2    300
    2017-01-01T00:02:35    3    100
    2017-01-01T00:02:40    4    100"""),
                  header=1, parse_dates=[0], index_col=0)

print(df)    
print(df.resample("1Min").agg({'A': sum, 'B': np.mean}))


Results:

                     A    B
2017-01-01 00:01:01  0  100
2017-01-01 00:01:10  1  200
2017-01-01 00:01:16  2  300
2017-01-01 00:02:35  3  100
2017-01-01 00:02:40  4  100

                     A    B
2017-01-01 00:01:00  3  200
2017-01-01 00:02:00  7  100