2011/9/29 Grové <grove.st...@gmail.com> > > Hi Mark > > Did you ever get to write: > > date_as_datetime(datearray, hour, minute, second, microsecond, > timezone='local', unit=None, out=None) > and > datetime_as_date(datetimearray, timezone='local', out=None) > ? >
I never got to these functions, no. I am looking for an easy way of using datetime[m] data to test for business > days > and do half hourly comparisons. > > I am using: > > In [181]: np.__version__ > Out[181]: '2.0.0.dev-aded70c' > Here's a stopgap solution for converting to dates, that works for a single np.datetime64: def my_datetime_as_date(dt, timezone = 'local'): s = np.datetime_as_string(np.datetime64(dt), timezone=timezone) e = s.find('T') if e != -1: s = s[:e] return np.datetime64(s, 'D') >>> my_datetime_as_date('now') numpy.datetime64('2011-09-30') >>> my_datetime_as_date('2011-03-13T00:30Z') numpy.datetime64('2011-03-12') >>> my_datetime_as_date('2011-03-13T00:30') numpy.datetime64('2011-03-13') >>> my_datetime_as_date('2011-03-13T00:30Z', timezone='UTC') numpy.datetime64('2011-03-13') Cheers, Mark > > > Regards > > Grové Steyn > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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