NP reshape (add extra 2 dimension)

I will illustrate my question with an example. If I have the array:

a = np.array([[1,2,3,4],
              [9,10,11,12],
              [17,18,19,20],
              [25,26,27,28]])

I would like to get

array([[[ 1,  2],   [[ 3,  4],
        [9, 10],    [11, 12],
        [17, 18],    [19, 20],
        [25, 26]]    [27, 28]],

So apparently if my array was MxN , now it will be Mx(N/2)x2. How to do it? I tried:

import numpy as np

# pre-computed data
data.reshape(data.shape[0], data.shape[1]//2, 2)

, does not work as expected

>Solution :

Use np.split (on column axis) + np.stack combination:

arr = np.stack(np.split(a, 2, axis=1))
print(arr)

[[[ 1  2]
  [ 9 10]
  [17 18]
  [25 26]]

 [[ 3  4]
  [11 12]
  [19 20]
  [27 28]]]