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From Daniel Nugent <nug...@gmail.com>
Subject Re: Attn: Wes, Re: Masked Arrays
Date Mon, 30 Mar 2020 16:20:06 GMT
Thanks! Since I'm just using it to jump to Arrow, I think I'll stick with
it.

Do you have any feelings about why Numpy's masked arrays didn't gain favor
when many data representation formats explicitly support nullity (including
Arrow)? Is it just that not carrying nulls in computations forward is
preferable (that is, early filtering/value filling was easier)?

-Dan Nugent


On Mon, Mar 30, 2020 at 11:40 AM Wes McKinney <wesmckinn@gmail.com> wrote:

> On Mon, Mar 30, 2020 at 8:31 AM Daniel Nugent <nugend@gmail.com> wrote:
> >
> > Didn’t want to follow up on this on the Jira issue earlier since it's
> sort of tangential to that bug and more of a usage question. You said:
> >
> > > I wouldn't recommend building applications based on them nowadays
> since the level of support / compatibility in other projects is low.
> >
> > In my case, I am using them since it seemed like a straightforward
> representation of my data that has nulls, the format I’m converting from
> has zero cost numpy representations, and converting from an internal format
> into Arrow in memory structures appears zero cost (or close to it) as well.
> I guess I can just provide the mask as an explicit argument, but my
> original desire to use it came from being able to exploit
> numpy.ma.concatenate in a way that saved some complexity in implementation.
> >
> > Since Arrow itself supports masking values with a bitfield, is there
> something intrinsic to the notion of array masks that is not well
> supported? Or do you just mean the specific numpy MaskedArray class?
> >
>
> I mean just the numpy.ma module. Not many Python computing projects
> nowadays treat MaskedArray objects as first class citizens. Depending
> on what you need it may or may not be a problem. pyarrow supports
> ingesting from MaskedArray as a convenience, but it would not be
> common in my experience for a library's APIs to return MaskedArrays.
>
> > If this is too much of a numpy question rather than an arrow question,
> could you point me to where I can read up on masked array support or maybe
> what the right place to ask the numpy community about whether what I'm
> doing is appropriate or not.
> >
> > Thanks,
> >
> >
> > -Dan Nugent
>

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