In addition to dtype
objects, NumPy introduces special numeric values: nan
and inf
. These can arise in mathematical computations. Not A Number (nan). It indicates that a value that should be numeric is, in fact, not defined mathematically. For example, 0/0
yields nan
. Sometimes, nan
is also used to signify missing information; for example, pandas uses this. inf
indicates a quantity that is arbitrarily large, so in practice, it means larger than any number the computer can conceive of. -inf
is also defined and it means arbitrarily small. This could occur if a numeric operation blows up, that is, grows rapidly without bounds.
Nothing is ever equal to nan
; it makes no sense for something undefined to be equal to something else. You need to use the NumPy function isnan
to identify nan
. While the ==
sign does not work for nan
, it does work for inf
. That said, you're better off distinguishing finite and infinite values using the function is finite or is inf
. Arithmetic involving...