Insert missing data in a dataframe

[perfringo]

No code is posted, so neither do I, only provide idea: if time is index, then create new dataframe with step on 2 minutes for needed duration and value of 0. Then just add two columns, those rows which are only in new dataframe will keep value 0 and those which have value 1 in initial dataframe will have that value (1 + 0 = 1).

Implementation of idea above (I have little idea whether it address actual problem):

Creating sample data - three datetimes as indices with value of 1:

import pandas as pd

data = dict.fromkeys(('2006-09-17 12:49:00', '2006-09-17 12:57:00', '2006-09-17 13:01:00'), 1)
df = pd.DataFrame.from_dict(data, orient='index')
print(df)

Output:
                     0
2006-09-17 12:49:00  1
2006-09-17 12:57:00  1
2006-09-17 13:01:00  1

Create dataframe with all needed datetimes with interval of 2 minutes and values of 0:

import numpy as np

index = pd.date_range('2006-09-17 12:45:00', periods=10, freq='2T')
df_2 = pd.DataFrame(np.zeros(10), index=index)
print(df_2)

Output:
                   0
2006-09-17 12:45:00  0
2006-09-17 12:47:00  0
2006-09-17 12:49:00  0
2006-09-17 12:51:00  0
2006-09-17 12:53:00  0
2006-09-17 12:55:00  0
2006-09-17 12:57:00  0
2006-09-17 12:59:00  0
2006-09-17 13:01:00  0
2006-09-17 13:03:00  0

Now I just add these two dataframes. Addition will be indices based, just fill NaN-s with zeros:

new = (df_2 + df).fillna(0).astype(int)
print(new)

Output:
                    0
2006-09-17 12:45:00  0
2006-09-17 12:47:00  0
2006-09-17 12:49:00  1
2006-09-17 12:51:00  0
2006-09-17 12:53:00  0
2006-09-17 12:55:00  0
2006-09-17 12:57:00  1
2006-09-17 12:59:00  0
2006-09-17 13:01:00  1
2006-09-17 13:03:00  0

Now I have dataframe which have two minutes interval and have value 1 from source data and 0 where particular datetime missing in source data.