Equivalent of NumPy index arrays with standard Python lists or arrays

Question

I can use an array or a list to index into numpy.array, e.g.:

a = np.array([1, 2, 3, 4])
print(a[[1, 3]])

will produce

[2 4]

Is there an equivalent construct to index into a standard Python list or array?

Just to be more specific: indexing has to be with an array and indexing pattern is random, i.e. not possible with slicing. Here is a better example:

a = np.array([1, 2, 3, 4])
i = [3, 0, 1]
print(a[i])
.....
[4 1 2]

It depends on what you mean by equivalent. `[my_list[i] for i in index_list]` would give such result. — bb1, Nov 17 '21 at 05:11
In this specific case a slice would do. But you are probably not just looking for evenly spaced indices, do you? — MisterMiyagi, Nov 17 '21 at 05:34
If you try indexing with a list, you get a clear statement of what is possible, `TypeError: list indices must be integers or slices, not list`. — hpaulj, Nov 17 '21 at 07:54

score 1 · Answer 1 · 2021-11-17T08:52:43.307

1

from operator import itemgetter 

print(itemgetter(1,3)(a))

and to turn it into a list:

print(list(itemgetter(1,3)(a)))

edited Nov 17 '21 at 08:52

answered Nov 17 '21 at 05:21

Which is implemented as an iteration on the indices: `tuple(obj[i] for i in items)` – hpaulj Nov 17 '21 at 05:59
Not quite there, since it indexes with and produces a tuple not an array. – Paul Jurczak Nov 17 '21 at 07:08

1 Answers1