How to convert a python set to a numpy array?

Question

I am using a set operation in python to perform a symmetric difference between two numpy arrays. The result, however, is a set and I need to convert it back to a numpy array to move forward. Is there a way to do this? Here's what I tried:

a = numpy.array([1,2,3,4,5,6]) b = numpy.array([2,3,5]) c = set(a) ^ set(b) 

The results is a set:

In [27]: c Out[27]: set([1, 4, 6]) 

If I convert to a numpy array, it places the entire set in the first array element.

In [28]: numpy.array(c) Out[28]: array(set([1, 4, 6]), dtype=object) 

What I need, however, would be this:

array([1,4,6],dtype=int) 

I could loop over the elements to convert one by one, but I will have 100,000 elements and hoped for a built-in function to save the loop. Thanks!

Answer 1

Do:

>>> numpy.array(list(c)) array([1, 4, 6]) 

And dtype is int (int64 on my side.)

Answer 2

Don't convert the numpy array to a set to perform exclusive-or. Use setxor1d directly.

>>> import numpy >>> a = numpy.array([1,2,3,4,5,6]) >>> b = numpy.array([2,3,5]) >>> numpy.setxor1d(a, b) array([1, 4, 6])