I’d like to return all rows from a dataframe, tos, for 5 minute intervals.

To start, I’m simply looping to allow space for processing the collected rows, but not opposed to vectorizing if it makes sense.

tos

                             Time  TickType     Price  Size
0      2023-08-13 15:10:46.166268         1 4487.2500     1
1      2023-08-13 15:10:47.375489         1 4487.0000     1
2      2023-08-13 15:10:54.656049         1 4487.2500     2
3      2023-08-13 15:10:57.626667         1 4487.0000     1
4      2023-08-13 15:10:57.627504         1 4487.0000     1
                          ...       ...       ...   ...
380508 2023-08-14 13:59:59.504712         1 4506.5000     1
380509 2023-08-14 13:59:59.504954         1 4506.5000     1
380510 2023-08-14 13:59:59.505058         1 4506.7500    14
380511 2023-08-14 14:00:00.107130         1 4506.7500     8
380512 2023-08-14 14:00:00.107344         1 4506.5000     1

Starting here to debug:

import pandas as pd

st = datetime.datetime(2023,8,13,15,10)
end = datetime.datetime(2023,8,14,14,00)

int_range = pd.date_range(st, end, freq='5min', inclusive='both')

for i, k in enumerate(int_range):
    
    a = tos.set_index('Time').between_time(k, int_range[i+1])
    print(a)
    

Which gives the following error:

ValueError: Cannot convert arg [Timestamp('2023-08-13 15:10:47.284558', freq='5T')] to a time

Is there a better approach to doing this and how to get around the error?