Pandas dataframe resample aggregation by mills too slow
It appears you don't really want to use resampling.  You are immediately throwing away the resampled data.  I think what you actually need is to simply groupby records in the same millisecond.  That can be accomplished with:

Truncate to milliseconds and group by

df['milliseconds'] = df['date'].str[:-3]
grouped_and_summed = df.groupby(df.milliseconds).sum()


Test Code

import pandas as pd
import numpy as np

data = {'date': ['2014-05-01 18:47:05.069722', '2014-05-01 18:47:05.119994',
                 '2014-05-02 18:47:05.178768', '2014-05-02 18:47:05.230071',
                 '2014-05-02 18:47:05.230071', '2014-05-02 18:47:05.280592',
                 '2014-05-03 18:47:05.332662', '2014-05-03 18:47:05.385109',
                 '2014-05-04 18:47:05.436523',
                 '2014-05-04 18:47:05.486877'],
        'battle_deaths': [34, 25, 26, 15, 15, 14, 26, 25, 62, 41],
        'prisioners': [3, 4, 3, 2, 2, 6, 4, 5, 2, 8]}
df = pd.DataFrame(data, columns=['date', 'battle_deaths', 'prisioners'])

df['milliseconds'] = df['date'].str[:-3]
print(df.groupby(df.milliseconds).sum())


Results:

                         battle_deaths  prisioners
milliseconds                                      
2014-05-01 18:47:05.069             34           3
2014-05-01 18:47:05.119             25           4
2014-05-02 18:47:05.178             26           3
2014-05-02 18:47:05.230             30           4
2014-05-02 18:47:05.280             14           6
2014-05-03 18:47:05.332             26           4
2014-05-03 18:47:05.385             25           5
2014-05-04 18:47:05.436             62           2
2014-05-04 18:47:05.486             41           8