How to Sort a Numpy Array Using Indexes from Another Array

Discover how to efficiently reorganize a Numpy array according to specified indices in another array without using loops.
---

Visit these links for original content and any more details, such as alternate solutions, comments, revision history etc. For example, the original title of the Question was: Sorting numpy array according to index provided by another array

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Sorting a Numpy Array Using Another Array's Indexes

Sorting arrays efficiently is a common requirement in data analysis and scientific computing. If you are working with Numpy, you might have encountered a scenario where you want to sort one array according to the indices provided by another array. In this post, we'll address this problem and provide a solution that avoids the use of loops.

The Problem

Imagine you have an array A with the elements [5, 7, 6] and an index array I with the values [2, 0, 1]. Your goal is to rearrange the elements of A based on the indices provided in I, so that the new array A_new becomes [7, 6, 5].

The Solution

Understanding the Desired Output

To achieve the intended outcome, we need to recognize how the indices work in our arrays. In this scenario:

The second index of I (which is 0) points to the first element of A (value 5).

The first index of I (which is 2) points to the third element of A (value 6), and so on.

We want to reorganize A so that:

The item at index 2 of I (which is the value 5) goes to the new index 0 of A_new.

The value 7 should be first in A_new.

The value 6 should occupy the second position.

Using Numpy for Efficient Assignment

Instead of using loops, we can leverage Numpy’s array manipulation capabilities. Here’s a simple trick to reorganize A using the index array I:

Initialize a Result Array: Create an empty array of the same size and shape as A, filled with zeros.

Assign Values Using the Index Array: Use the index array I to place the elements of A into the corresponding positions in the new array.

Here's how you can implement this in Python:

[[See Video to Reveal this Text or Code Snippet]]

Alternative: Using argsort

Another method is to convert I into a corrected index using argsort, which provides a way to sort I. Here’s how that looks:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

By using the Numpy functionality and understanding the behavior of indices, you can efficiently reorganize arrays without resorting to loops. The method described above simplifies the task by using advanced array indexing techniques. Whether you prefer the direct assignment method or using argsort, both solutions are effective for sorting based on index arrays in Numpy.

With this knowledge, you can handle similar problems in Numpy with ease and flexibility. Should you have more such challenges, feel free to explore Numpy’s vast array of functionalities!