python - pandas: for each row in df copy row N times with slight changes -

so have dataframe this:

   n    start 1  1    08/01/2014 9:30:02 2  1    08/01/2014 10:30:02  3  2    08/01/2014 12:30:02 4  3    08/01/2014 4:30:02 

and need duplicate each row n times, adding 1 hour start each time, this:

   n    start 1  1    08/01/2014 9:30:02 2  1    08/01/2014 10:30:02  3  2    08/01/2014 12:30:02 3  2    08/01/2014 13:30:02 4  3    08/01/2014 4:30:02 4  3    08/01/2014 5:30:02 4  3    08/01/2014 6:30:02 

how can within pandas?

you use reindex expand dataframe, , timedeltaindex add hours:

import pandas pd df = pd.dataframe({'n': [1, 1, 2, 3],                    'start': ['08/01/2014 9:30:02',                              '08/01/2014 10:30:02',                              '08/01/2014 12:30:02',                              '08/01/2014 4:30:02']}) df['start'] = pd.to_datetime(df['start']) df = df.reindex(np.repeat(df.index.values, df['n']), method='ffill') df['start'] += pd.timedeltaindex(df.groupby(level=0).cumcount(), unit='h') 

which yields

   n               start 0  1 2014-08-01 09:30:02 1  1 2014-08-01 10:30:02 2  2 2014-08-01 12:30:02 2  2 2014-08-01 13:30:02 3  3 2014-08-01 04:30:02 3  3 2014-08-01 05:30:02 3  3 2014-08-01 06:30:02