On Tue, Sep 29, 2015 at 11:14 AM, Antoine Pitrou <solip...@pitrou.net>
wrote:
>
> None for example? float('nan') may be a bit weird amongst e.g. an array
> of Decimals
The downside to `None` is that it's one more thing to check for and makes
object arrays an even weirder edge case. (Incidentally, Decimal does have
its own non-float NaN which throws a whole different wrench in the works. `
np.sign(Decimal('NaN'))` is going to raise an error no matter what.)
A float (or numpy) NaN makes more sense to return for mixed datatypes than
None does, in my opinion. At least then one can use `isfinite`, etc to
check while `np.isfinite(None)` will raise an error. Furthermore, if
there's at least one floating point NaN in the object array, getting a
float NaN out makes sense.
Just my $0.02, anyway.
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