On Jun 29, 2011, at 1:39 AM, Mark Wiebe wrote: > On Tue, Jun 28, 2011 at 5:20 PM, Matthew Brett <matthew.br...@gmail.com> > wrote: > Hi, > > On Tue, Jun 28, 2011 at 4:06 PM, Nathaniel Smith <n...@pobox.com> wrote: > ... > > (You might think, what difference does it make if you *can* unmask an > > item? Us missing data folks could just ignore this feature. But: > > whatever we end up implementing is something that I will have to > > explain over and over to different people, most of them not > > particularly sophisticated programmers. And there's just no sensible > > way to explain this idea that if you store some particular value, then > > it replaces the old value, but if you store NA, then the old value is > > still there. > > Ouch - yes. No question, that is difficult to explain. Well, I > think the explanation might go like this: > > "Ah, yes, well, that's because in fact numpy records missing values by > using a 'mask'. So when you say `a[3] = np.NA', what you mean is, > 'a._mask = np.ones(a.shape, np.dtype(bool); a._mask[3] = False`" > > Is that fair? > > My favorite way of explaining it would be to have a grid of numbers written > on paper, then have several cardboards with holes poked in them in different > configurations. Placing these cardboard masks in front of the grid would show > different sets of non-missing data, without affecting the values stored on > the paper behind them.
And when there's a hole (or just a blank) in your piece of paper ? _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
