New submission from Adam Davison:
If you pass an array containing nan to collections.Counter, rather than
counting the number of 'nan's it outputs 'nan': 1 n times into the
dictionary. I appreciate using this on an array of floats is a bit of an
unusual case but I don't think this is the
Mark Dickinson added the comment:
Presumably this relates to the fact that nan != nan.
Yep. What you're seeing is pretty much expected behaviour, and it matches how
NaNs behave with respect to containment in other Python contexts:
x = float('nan')
y = float('nan')
s = {x}
x in s
True
y
Adam Davison added the comment:
Thanks for the quick response. I'm really using a pandas Series, which is
effectively a numpy array behind the scenes as far as I understand, the example
I pasted was just to illustrate the behaviour. So the nans are being produced
elsewhere, I don't really
Mark Dickinson added the comment:
perhaps collections.Counter should handle nans as a special case
I don't think that would be a good idea: I'd rather that collections.Counter
didn't special case NaNs in any way, but instead treated NaNs following the
same (admittedly somewhat awkward)
Terry J. Reedy added the comment:
This is the sort of issue that makes me think that there should be a single nan
object (perhaps an instance of a Nan(float) subclass with a special __eq__
method ;-). Pending that, I agree with closing as won't fix.
--
nosy: +terry.reedy
Changes by Raymond Hettinger raymond.hettin...@gmail.com:
--
resolution: - wont fix
status: open - closed
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Python tracker rep...@bugs.python.org
http://bugs.python.org/issue19161
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