We could put them in an array that looked like this:Īnd, if we simply walked the array – it’s sorted! Problem 1: Zip Codes aren’t unique Then if we walk the array the elements will be sorted! At it’s core the idea is simple – all we need to do is treat each element value as a position in an array. It is – and this is where Radix Sort comes in. However, what if we didn’t need to compare members? Could we do better? Is it even possible?

It can be shown that any comparison sort cannot do better than O(n*logn) which is the order of a good MergeSort as well.

What this means is that it needs to compare the elements in order to sort them. MergeSort is a comparison sort algorithm. Can we do better? It turns out we can! Enter Radix Sort But it seems like we aren’t really using the fact that it is sorted to give us any benefit. Now bottom-up MergeSort is stable, so we can use that. Sort by zip and use a stable sorting algorithm that maintains the order.Use a comparison function that compares first on zip and then on importance.Well, we basically need to re-sort the entire list and we can do it in two ways: Imagine the following situation – you have a million users and they have been ‘ranked’ by some measure of importance (interest in your product/amount of interaction/connectedness in network/…). Yet there is one algorithm that is both simple and powerful that I find many engineers don’t know very well – Radix Sort. Most of us are pretty familiar with QuickSort, Mergesort, and so on. Sorting algorithms are the backbone of any Data Science & Algorithm course.

Radix sort best case