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pythonpandasdataframepython-datetime

how to duplicate pandas datetime object

I have a a 1X1 pandas Series object which contains a single datetime object. I want to duplicate this row into additional X rows (eg 10). I have tried doing it through the .append command as well as plain multiplication but it does not seem to work when the object type is 'datetime'. Help appreciated.

>>> print df
0   2016-04-21
dtype: datetime64[ns]

the desired output should be something like (which I generated through rather cumbersome df.append([df,df,df...])

0   2016-04-21
0   2016-04-21
0   2016-04-21
0   2016-04-21
0   2016-04-21
0   2016-04-21
dtype: datetime64[ns]
Solution

  • you can use numpy.tile() function for that:

    In [43]: s = pd.Series(pd.to_datetime('2016-04-21'))

In [44]: s
Out[44]:
0   2016-04-21
dtype: datetime64[ns]

In [45]: np.tile(s, 10)
Out[45]:
array(['2016-04-21T02:00:00.000000000+0200',
       '2016-04-21T02:00:00.000000000+0200',
       '2016-04-21T02:00:00.000000000+0200',
       '2016-04-21T02:00:00.000000000+0200',
       '2016-04-21T02:00:00.000000000+0200',
       '2016-04-21T02:00:00.000000000+0200',
       '2016-04-21T02:00:00.000000000+0200',
       '2016-04-21T02:00:00.000000000+0200',
       '2016-04-21T02:00:00.000000000+0200',
       '2016-04-21T02:00:00.000000000+0200'], dtype='datetime64[ns]')

In [46]: pd.DataFrame(np.tile(s, 10), columns=['date'])
Out[46]:
        date
0 2016-04-21
1 2016-04-21
2 2016-04-21
3 2016-04-21
4 2016-04-21
5 2016-04-21
6 2016-04-21
7 2016-04-21
8 2016-04-21
9 2016-04-21