How do I access the ith column of a NumPy multidimensional array?

With:

test = np.array([[1, 2], [3, 4], [5, 6]])

To access column 0:

>>> test[:, 0]
array([1, 3, 5])

To access row 0:

>>> test[0, :]
array([1, 2])

This is covered in Section 1.4 (Indexing) of the NumPy reference. This is quick, at least in my experience. It's certainly much quicker than accessing each element in a loop.

>>> test[:,0]
array([1, 3, 5])

this command gives you a row vector, if you just want to loop over it, it's fine, but if you want to hstack with some other array with dimension 3xN, you will have

ValueError: all the input arrays must have same number of dimensions

while

>>> test[:,[0]]
array([[1],
       [3],
       [5]])

gives you a column vector, so that you can do concatenate or hstack operation.

e.g.

>>> np.hstack((test, test[:,[0]]))
array([[1, 2, 1],
       [3, 4, 3],
       [5, 6, 5]])

And if you want to access more than one column at a time you could do:

>>> test = np.arange(9).reshape((3,3))
>>> test
array([[0, 1, 2],
       [3, 4, 5],
       [6, 7, 8]])
>>> test[:,[0,2]]
array([[0, 2],
       [3, 5],
       [6, 8]])

You could also transpose and return a row:

In [4]: test.T[0]
Out[4]: array([1, 3, 5])