numpy.isnan

numpy.isnan(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'isnan'>

Test elementwise for NaN and return result as a boolean array.
Parameters: 

x : array_like 
Input array. 
out : ndarray, None, or tuple of ndarray and None, optional 
A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None , a freshlyallocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs. 
where : array_like, optional 
This condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default out=None , locations within it where the condition is False will remain uninitialized.  **kwargs

For other keywordonly arguments, see the ufunc docs. 
Returns: 

y : ndarray or bool 
True where x is NaN, false otherwise. This is a scalar if x is a scalar. 
Notes
NumPy uses the IEEE Standard for Binary FloatingPoint for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity.
Examples
>>> np.isnan(np.nan)
True
>>> np.isnan(np.inf)
False
>>> np.isnan([np.log(1.),1.,np.log(0)])
array([ True, False, False])