python - how to get the datetimes before and after some specific dates in Pandas? -

i have pandas dataframe looks like

col1 2015-02-02 2015-04-05 2016-07-02 

i add, each date in col 1, x days before , x days after date.

that means resulting dataframe contain more rows (specifically, n(1+ 2*x), n orignal number of dates in col1)

how can in proper pandonic way?

output (for x=1)

col1 2015-01-01 2015-01-02 2015-01-03 2015-04-04 etc 

thanks!

you can way, i'm not sure it's best / fastest way it:

in [143]: df out[143]:         col1 0 2015-02-02 1 2015-04-05 2 2016-07-02  in [144]: %paste n = 2 (df.col1.apply(lambda x: pd.series(pd.date_range(x - pd.timedelta(days=n),                                                  x + pd.timedelta(days=n))                          )          )         .stack()         .drop_duplicates()         .reset_index(level=[0,1], drop=true)         .to_frame(name='col1') ) ## -- end pasted text -- out[144]:          col1 0  2015-01-31 1  2015-02-01 2  2015-02-02 3  2015-02-03 4  2015-02-04 5  2015-04-03 6  2015-04-04 7  2015-04-05 8  2015-04-06 9  2015-04-07 10 2016-06-30 11 2016-07-01 12 2016-07-02 13 2016-07-03 14 2016-07-04