Sankarshan Mudkavi <smudkavi <at> uwaterloo.ca> writes: > > Hey all, > It's been a while since the last datetime and timezones discussion thread was visited (linked below): > > http://thread.gmane.org/gmane.comp.python.numeric.general/53805 > > It looks like the best approach to follow is the UTC only approach in the linked thread with an optional flag to indicate the timezone (to avoid confusing applications where they don't expect any timezone info). Since this is slightly more useful than having just a naive datetime64 package and would be open to extension if required, it's probably the best way to start improving the datetime64 library. > <snip> > I would like to start writing a NEP for this followed by implementation, however I'm not sure what the format etc. is, could someone direct me to a page where this information is provided? > > Please let me know if there are any ideas, comments etc. > > Cheers, > Sankarshan >
See: http://article.gmane.org/gmane.comp.python.numeric.general/55191 You could use a current NEP as a template: https://github.com/numpy/numpy/tree/master/doc/neps I'm a huge +100 on the simplest UTC fix. As is, using numpy datetimes is likely to silently give incorrect results - something I've already seen several times in end-user data analysis code. Concrete Example: In [16]: dates = pd.date_range('01-Apr-2014', '04-Apr-2014', freq='H')[:-1] ...: values = np.array([1,2,3]).repeat(24) ...: records = zip(map(str, dates), values) ...: pd.TimeSeries(values, dates).groupby(lambda d: d.date()).mean() ...: Out[16]: 2014-04-01 1 2014-04-02 2 2014-04-03 3 dtype: int32 In [17]: df = pd.DataFrame(np.array(records, dtype=[('dates', 'M8[h]'), ('values', float)])) ...: df.set_index('dates', inplace=True) ...: df.groupby(lambda d: d.date()).mean() ...: Out[17]: values 2014-03-31 1.000000 2014-04-01 1.041667 2014-04-02 2.041667 2014-04-03 3.000000 [4 rows x 1 columns] Try it in your timezone and see what you get! -Dave _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
