[Numpy-discussion] feedback request: proposal to add masks to the core ndarray

Charles R Harris charlesr.harris@gmail....
Fri Jun 24 09:46:21 CDT 2011


On Fri, Jun 24, 2011 at 8:44 AM, Robert Kern <robert.kern@gmail.com> wrote:

> On Fri, Jun 24, 2011 at 09:35, Robert Kern <robert.kern@gmail.com> wrote:
> > On Fri, Jun 24, 2011 at 09:24, Keith Goodman <kwgoodman@gmail.com>
> wrote:
> >> On Fri, Jun 24, 2011 at 7:06 AM, Robert Kern <robert.kern@gmail.com>
> wrote:
> >>
> >>> The alternative proposal would be to add a few new dtypes that are
> >>> NA-aware. E.g. an nafloat64 would reserve a particular NaN value
> >>> (there are lots of different NaN bit patterns, we'd just reserve one)
> >>> that would represent NA. An naint32 would probably reserve the most
> >>> negative int32 value (like R does). Using the NA-aware dtypes signals
> >>> that you are using NA values; there is no need for an additional flag.
> >>
> >> I don't understand the numpy design and maintainable issues, but from
> >> a user perspective (mine) nafloat64, etc sounds nice.
> >
> > It's worth noting that this is not a replacement for masked arrays,
> > nor is it intended to be the be-all, end-all solution to missing data
> > problems. It's mostly just intended to be a focused tool to fill in
> > the gaps where masked arrays are less convenient for whatever reason;
> > e.g. where you're tempted to (ab)use NaNs for the purpose and the
> > limitations on the range of values is acceptable. Not every dtype
> > would have an NA-aware counterpart. I would suggest just nabool,
> > nafloat64, naint32, nastring (a little tricky due to the flexible
> > size, but doable), and naobject. Maybe a couple more, if we get
> > requests, like naint64 and nacomplex128.
>
> Oh, and nadatetime64 and natimedelta64.
>
>
Beat me to it ;)

Chuck
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