[Numpy-discussion] Why NaN?

Bruce Southey bsouthey@gmail....
Wed Aug 5 03:40:17 CDT 2009

On Tue, Aug 4, 2009 at 4:05 PM, Keith Goodman<kwgoodman@gmail.com> wrote:
> On Tue, Aug 4, 2009 at 1:53 PM, Bruce Southey<bsouthey@gmail.com> wrote:
>> On Tue, Aug 4, 2009 at 1:40 PM, Gökhan Sever<gokhansever@gmail.com> wrote:
>>> This is the loveliest of all solutions:
>>> c[isfinite(c)].mean()
>> This handling of nonfinite elements has come up before.
>> Please remember that this only for 1d or flatten array so it not work
>> in general especially along an axis.
> If you don't want to use nanmean from scipy.stats you could use:
> np.nansum(c, axis=0) / (~np.isnan(c)).sum(axis=0)
> or
> np.nansum(c, axis=0) / (c == c).sum(axis=0)
> But if c contains ints then you'll run into trouble with the division,
> so you'll need to protect against that.

That is not a problem because nan and infinity are only defined for
floating point numbers not integers. So any array that have nonfinite
elements like nans and infinity must have a floating point dtype.


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