Combine elements from two arrays by pairs

Question

So I want to concatenate two arrays but by pairs. The input is as follows:

a = array([1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1]) b = array([0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0])

And the output should be as follows:

out_put = [[1, 0], [1, 0], [0, 1], [1, 0], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [1, 0]]

I managed to get such result by iterating over the two arrays

out_put = [[a[i],b[i]] for i in range(len(a)]

but I wonder if there any faster way .

Thank you

jpp · Accepted Answer · 2018-07-05 13:56:54Z

8

For a vectorised solution, you can stack and transpose:

a = np.array([1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1]) b = np.array([0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0]) c = np.vstack((a, b)).T # or, c = np.dstack((a, b))[0] array([[1, 0], [1, 0], [0, 1], [1, 0], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [1, 0]])

edited Jul 5, 2018 at 13:56

answered Jul 5, 2018 at 13:16

jpp

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3 Comments

Brad Solomon Over a year ago

Or just np.dstack((a, b)), though it's only a wrapper around concatenate

jpp Over a year ago

@BradSolomon, Thanks, think you'll also need to index [0] with that solution.

user3483203 Over a year ago

@BradSolomon column_stack is dstack without adding the additional dimension for 2 1D arrays

user3483203 · Accepted Answer · 2018-07-05 13:55:33Z

Using np.column_stack

Stack 1-D arrays as columns into a 2-D array.

np.column_stack((a, b)) array([[1, 0], [1, 0], [0, 1], [1, 0], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [0, 1], [1, 0]])

Patrick Haugh · Accepted Answer · 2018-07-05 13:21:15Z

You can use the zip function to combine any two iterables like this. It will continue until it reaches the end of the shorter iterable

list(zip(a, b)) # [(1, 0), (1, 0), (0, 1), (1, 0), (0, 1), (0, 1), (0, 1), (0, 1), (0, 1), (0, 1), (0, 1), (0, 1), (0, 1), (0, 1), (1, 0)]

Note: zip + NumPy arrays are actually inefficient: see this answer.

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