This post is about two mathematical concepts. They’re not numbers as such, but are helpful in numerical computations.
The first of these I’d like to discuss here nan, which stands for “not a number”. This tool originated in computer science and is used to distinguish between numerical values and all other values.
nan has been available since Python was first created, but has experienced a few changes as new versions have been introduced.
The first way to create a
nan in Python was by creating a special kind of float using the
'nan' string as an input.
Nan = float('nan')
Note that the resulting object is of type float.
>>> type(nan) <class 'float'>
Infinity is another mathematical concept that is not a number. Like with nan, the original way to work with in early versions of Python was creating a float.
Inf = float('inf')
Note that is was also possible to create negative infinity in the same way:
Neg_inf = float('-inf')
Starting with Python 3.5, it became possible to use defined constants from the math module for both nan and infinity. The first step to using these is always to import the math module.
We can then create variables set to nan or infinity using the standard
packagename.value syntax like so:
Pos_inf = math.inf Neg_inf = -math.inf Not_a_num = math.nan
Note the use of capital letters when working with constants.
The math module comes with built in methods to check for infinity or finiteness.
>>> math.isinf(math.inf) True >>> math.isfinite(math.inf) False
Similarly, the math module allows you to check for nan with a built in method:
>>> math.isnan(math.nan) True
nan is never equal to anything, not even itself. Remembering this can help understand behavior that can otherwise be very puzzling:
>>> nan = math.nan >>> math.nan == nan False