On Tue, Aug 21, 2018 at 6:47 PM Nathaniel Smith <n...@pobox.com> wrote:
> On Tue, Aug 21, 2018 at 9:39 AM, Stephan Hoyer <sho...@gmail.com> wrote: > > It is quite possible that NumPy functions could be (re)written in a way > that > > is incompatible with some unit implementations but is perfectly valid for > > "full" duck arrays. We actually see this even within NumPy already -- for > > example, see this recent PR adding support for the datetime64 dtype to > > percentile: > > https://github.com/numpy/numpy/pull/11627 > > I clicked the link, but I don't see anything about units? > To clarify: np.datetime64 arrays can be considered a variant of NumPy arrays that support units. Namely, they use a dtype for representing time units. I expect that the issues we've encountered with datetime64 will be indicative of some of the sort of issues that authors of unit-aware arrays will encounter.
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