Reputation: 349
I have an array of n numbers, say [1,4,6,2,3]
. The sorted array is [1,2,3,4,6]
, and the indexes of these numbers in the old array are 0, 3, 4, 1, and 2. What is the best way, given an array of n numbers, to find this array of indexes?
My idea is to run order statistics for each element. However, since I have to rewrite this function many times (in contest), I'm wondering if there's a short way to do this.
Upvotes: 10
Views: 14701
Reputation: 1
The long way instead of using list comprehension for beginner like me
a = [1,4,6,2,3]
b = enumerate(a)
c = sorted(b, key = lambda i:i[1])
d = []
for e in c:
d.append(e[0])
print(d)
Upvotes: 0
Reputation: 24788
This should do the trick:
from operator import itemgetter
indices = zip(*sorted(enumerate(my_list), key=itemgetter(1)))[0]
Upvotes: 0
Reputation: 231
Using numpy arrays instead of lists may be beneficial if you are doing a lot of statistics on the data. If you choose to do so, this would work:
import numpy as np
a = np.array( [1,4,6,2,3] )
b = np.argsort( a )
argsort() can operate on lists as well, but I believe that in this case it simply copies the data into an array first.
Upvotes: 3
Reputation: 251365
Here is another way:
>>> sorted(xrange(len(a)), key=lambda ix: a[ix])
[0, 3, 4, 1, 2]
This approach sorts not the original list, but its indices (created with xrange
), using the original list as the sort keys.
Upvotes: 1
Reputation: 1107
>>> a = [1,4,6,2,3]
>>> [b[0] for b in sorted(enumerate(a),key=lambda i:i[1])]
[0, 3, 4, 1, 2]
Explanation:
enumerate(a)
returns an enumeration over tuples consisting of the indexes and values in the original list: [(0, 1), (1, 4), (2, 6), (3, 2), (4, 3)]
Then sorted
with a key
of lambda i:i[1]
sorts based on the original values (item 1 of each tuple).
Finally, the list comprehension [b[0] for b in
...]
returns the original indexes (item 0 of each tuple).
Upvotes: 18