Get year, month or day from numpy datetime64

Question

I have an array of datetime64 type:

dates = np.datetime64([\'2010-10-17\', \'2011-05-13\', \"2012-01-15\"])

Is there a better way than loop

Answer 1

As datetime is not stable in numpy I would use pandas for this:

In [52]: import pandas as pd

In [53]: dates = pd.DatetimeIndex(['2010-10-17', '2011-05-13', "2012-01-15"])

In [54]: dates.year
Out[54]: array([2010, 2011, 2012], dtype=int32)

Pandas uses numpy datetime internally, but seems to avoid the shortages, that numpy has up to now.

Answer 2

If you upgrade to numpy 1.7 (where datetime is still labeled as experimental) the following should work.

dates/np.timedelta64(1,'Y')

Answer 3

There's no direct way to do it yet, unfortunately, but there are a couple indirect ways:

[dt.year for dt in dates.astype(object)]

or

[datetime.datetime.strptime(repr(d), "%Y-%m-%d %H:%M:%S").year for d in dates]

both inspired by the examples here.

Both of these work for me on Numpy 1.6.1. You may need to be a bit more careful with the second one, since the repr() for the datetime64 might have a fraction part after a decimal point.

Answer 4

I find the following tricks give between 2x and 4x speed increase versus the pandas method described above (i.e. pd.DatetimeIndex(dates).year etc.). The speed of [dt.year for dt in dates.astype(object)] I find to be similar to the pandas method. Also these tricks can be applied directly to ndarrays of any shape (2D, 3D etc.)

dates = np.arange(np.datetime64('2000-01-01'), np.datetime64('2010-01-01'))
years = dates.astype('datetime64[Y]').astype(int) + 1970
months = dates.astype('datetime64[M]').astype(int) % 12 + 1
days = dates - dates.astype('datetime64[M]') + 1

Answer 5

Anon's answer works great for me, but I just need to modify the statement for days

from:

days = dates - dates.astype('datetime64[M]') + 1

to:

days = dates.astype('datetime64[D]') - dates.astype('datetime64[M]') + 1

Answer 6

There should be an easier way to do this, but, depending on what you're trying to do, the best route might be to convert to a regular Python datetime object:

datetime64Obj = np.datetime64('2002-07-04T02:55:41-0700')
print datetime64Obj.astype(object).year
# 2002
print datetime64Obj.astype(object).day
# 4

Based on comments below, this seems to only work in Python 2.7.x and Python 3.6+