creating a boolean array which compares numpy elements to None

Question

I have a numpy array with dtype=object, and I want to create a boolean array identifying which elements are None. But it looks like None behaves differently...

a = np.array(['Duck','Duck','Duck','Goose',None,1,2,3,1,3,None,4])
print a == 'Duck'
print a == 3
print a == None

which results in

[ True  True  True False False False False False False False False False]
[False False False False False False False  True False  True False False]
False

Is there an "numpythonic" way to get a boolean array of the None elements? I can use

np.array([x is None for x in a])

but this seems like there should be a better way.

Answer 1

You can use numpy.equal:

In [20]: np.equal(a, None)
Out[20]: 
array([False, False, False, False,  True, False, False, False, False,
       False,  True, False], dtype=bool)