Concatenating column vectors using numpy arrays

Question

I'd like to concatenate 'column' vectors using numpy arrays but because numpy sees all arrays as row vectors by default, np.hstack and np.concatenate along any axis don't help (and neither did np.transpose as expected).

a = np.array((0, 1)) b = np.array((2, 1)) c = np.array((-1, -1))  np.hstack((a, b, c)) # array([ 0,  1,  2,  1, -1, -1])  ## Noooooo np.reshape(np.hstack((a, b, c)), (2, 3)) # array([[ 0,  1,  2], [ 1, -1, -1]]) ## Reshaping won't help 

One possibility (but too cumbersome) is

np.hstack((a[:, np.newaxis], b[:, np.newaxis], c[:, np.newaxis])) # array([[ 0,  2, -1], [ 1,  1, -1]]) ## 

Are there better ways?

Answer 1

I believe numpy.column_stack should do what you want. Example:

>>> a = np.array((0, 1)) >>> b = np.array((2, 1)) >>> c = np.array((-1, -1)) >>> numpy.column_stack((a,b,c)) array([[ 0,  2, -1],        [ 1,  1, -1]]) 

It is essentially equal to

>>> numpy.vstack((a,b,c)).T 

though. As it says in the documentation.

Answer 2

I tried the following. Hope this is good enough for what you are doing ?

>>> np.vstack((a,b,c)) array([[ 0,  1],        [ 2,  1],        [-1, -1]]) >>> np.vstack((a,b,c)).T array([[ 0,  2, -1],        [ 1,  1, -1]])