Rearrange columns of numpy 2D array

This is possible in O(n) time and O(n) space using fancy indexing:

>>> import numpy as np
>>> a = np.array([[10, 20, 30, 40, 50],
...               [ 6,  7,  8,  9, 10]])
>>> permutation = [0, 4, 1, 3, 2]
>>> idx = np.empty_like(permutation)
>>> idx[permutation] = np.arange(len(permutation))
>>> a[:, idx]  # return a rearranged copy
array([[10, 30, 50, 40, 20],
       [ 6,  8, 10,  9,  7]])
>>> a[:] = a[:, idx]  # in-place modification of a

Note that a[:, idx] is returning a copy, not a view. An O(1)-space solution is not possible in the general case, due to how numpy arrays are strided in memory.

The easiest way in my opinion is:

a = np.array([[10, 20, 30, 40, 50],
              [6,  7,  8,  9,  10]])
print(a[:, [0, 2, 4, 3, 1]])

the result is:

[[10 30 50 40 20]
 [6  8  10 9  7 ]]