How to resample pandas Dataframe time series data from 8hz to 16hz?

I have time series data in pandas Dataframe with a 8hz sampling rate, i.e. 8 samples per second. I need to convert it to 16 hz data i.e. 16 samples per second. the index is in first column, in the format yyyy-mm-dd hh:mm:ss.ssssss. I am unable to resample using standard pandas command. can an one please help me with how to do this ? other answers speaks about hours 'H', minutes 'm', but can some one help me with where data is sub second.

You can actually do it the same way. Pandas resample supports values up to nanoseconds. Here are some values to keep in mind:

S        seconds
L        milliseconds
U        microseconds
N        nanoseconds

For your case, 8 samples per second is equivalent to 125 mellisecond, and 16 samples per second is 62.5 mellisecond.

Generate an example (8hz):

index = pd.date_range('1/1/2000', periods=9, freq='125L')
series = pd.Series(range(9), index=index)

Gives:

2000-01-01 00:00:00.000    0
2000-01-01 00:00:00.125    1
2000-01-01 00:00:00.250    2
2000-01-01 00:00:00.375    3
2000-01-01 00:00:00.500    4
2000-01-01 00:00:00.625    5
2000-01-01 00:00:00.750    6
2000-01-01 00:00:00.875    7
2000-01-01 00:00:01.000    8

Resample:

series = series.resample('62.5L').ffill()

Gives:

2000-01-01 00:00:00.000000    0
2000-01-01 00:00:00.062500    0
2000-01-01 00:00:00.125000    1
2000-01-01 00:00:00.187500    1
2000-01-01 00:00:00.250000    2
2000-01-01 00:00:00.312500    2
2000-01-01 00:00:00.375000    3
2000-01-01 00:00:00.437500    3
2000-01-01 00:00:00.500000    4
2000-01-01 00:00:00.562500    4
2000-01-01 00:00:00.625000    5
2000-01-01 00:00:00.687500    5
2000-01-01 00:00:00.750000    6
2000-01-01 00:00:00.812500    6
2000-01-01 00:00:00.875000    7
2000-01-01 00:00:00.937500    7
2000-01-01 00:00:01.000000    8