Hi Robert, Thanks for the quick reply.
On Sep 13, 1:22 pm, Robert Kern <robert.k...@gmail.com> wrote: > The problem is that you are trying to use "is" to compare by Python object > identity. Except for dtype=object arrays, the object identities of the > individual elements that you extract from numpy arrays are never guaranteed. > Usually, they will always be different. You need to use numpy.isnan() to > determine whether an object is a NaN. OK, so there's a dedicated function in numpy to handle this. Thanks! I tried "x is NaN" after noting the obvious, that any equality or inequality test involving NaN will return False. In my leisure time, I would like to dig deeper into the issue of why object identities are not guaranteed for elements in numpy arrays... with elements of type "float", at least, I thought this would be trivial. -- http://mail.python.org/mailman/listinfo/python-list
