How can I make a python numpy arange of datetime

Question

I have some input data, with timestamps in the input file in the form of hours from the date time specified in the filename.

This is a bit useless, so I need to convert it to python datetime.datetime objects, and then put it in a numpy array. I could write a for loop, but I'd like to do something like:

numpy.arange(datetime.datetime(2000, 1,1), datetime.datetime(2000, 1,2), datetime.timedelta(hours=1)) 

which throws a TypeError.

Can this be done? I'm stuck with python 2.6 and numpy 1.6.1.

Answer 1

from datetime import datetime, timedelta  t = np.arange(datetime(1985,7,1), datetime(2015,7,1), timedelta(days=1)).astype(datetime) 

The key point here is to use astype(datetime), otherwise the result will be datetime64.

Answer 2

See NumPy Datetimes and Timedeltas. Basically, you can represent datetimes in NumPy using the numpy.datetime64 type, which permits you to do ranges of values.

For NumPy 1.6, which has a much less useful datetime64 type, you can use a suitable list comprehension to build the datetimes (see also Creating a range of dates in Python):

base = datetime.datetime(2000, 1, 1) arr = numpy.array([base + datetime.timedelta(hours=i) for i in xrange(24)]) 

This produces

array([2000-01-01 00:00:00, 2000-01-01 01:00:00, 2000-01-01 02:00:00,    2000-01-01 03:00:00, 2000-01-01 04:00:00, 2000-01-01 05:00:00,    2000-01-01 06:00:00, 2000-01-01 07:00:00, 2000-01-01 08:00:00,    2000-01-01 09:00:00, 2000-01-01 10:00:00, 2000-01-01 11:00:00,    2000-01-01 12:00:00, 2000-01-01 13:00:00, 2000-01-01 14:00:00,    2000-01-01 15:00:00, 2000-01-01 16:00:00, 2000-01-01 17:00:00,    2000-01-01 18:00:00, 2000-01-01 19:00:00, 2000-01-01 20:00:00,    2000-01-01 21:00:00, 2000-01-01 22:00:00, 2000-01-01 23:00:00], dtype=object)