Sorting is one of the central topic in Computer Science degrees. In general sorting means rearranging data according to a defined pattern with the end goal of transforming the original unsorted sequence into a sorted sequence It’s lies at the heart of successful businesses ventures such as Google or Amazon, but is also present in many applications we use daily, such as Excel or Facebook.

Many different algorithms have been developed to sort data. Wikipedia lists over 45 but there are probably even more. Some work by exchanging data points in a sequence, others insert and/or merge parts of sequences. More importantly, some algorithms are quite effective in terms of the time they take to sort data — taking only time to sort datapoints — whereas others are very slow — taking as much as . Moreover, some algorithms are stable — in the sense that they always take the same amount of time to process datapoints — whereas others may fluctuate in terms of processing time based on the original order of the data.

I really enjoyed this video by TED-Ed on how to best sort your book collection. It provides a very intuitive introduction into sorting strategies (i.e., algorithms). Moreover, Algorithms to Live By (Christian & Griffiths, 2016) provided the amazing suggestion to get friends and pizza in whenever you need to sort something, next to the great explanation of various algorithms and their computational demand.

The main reason for this blog is that I stumbled across some nice video’s and GIFs of sorting algorithms in action. These visualizations are not only wonderfully intriguing to look at, but also help so much in understanding how the sorting algorithms process the data under the hood. You might want to start with the 4-minute YouTube video below, demonstrating how nine different sorting algorithms (*Selection Sort, Shell Sort, Insertion Sort, Merge Sort, Quick Sort, Heap Sort, Bubble Sort, Comb Sort, & Cocktail Sort*) process a variety of datasets.

This interactive website toptal.com allows you to play around with the most well-known sorting algorithms, putting them to work on different datasets. For the grande finale, I found these GIFs and short video’s of several sorting algorithms on imgur. In the visualizations below, each row of the image represents an independent list being sorted. You can see that Bubble Sort is quite slow:

Cocktail Shaker Sort already seems somewhat faster, but still takes quite a while.

For some algorithms, the visualization clearly shows that the settings you pick matter. For instance, Heap Sort is much quicker if you choose to *shift down *instead of *up*.

In contrast, for Merge Sort it doesn’t matter whether you sort by *breadth first *or *depth first*.

The imgur overview includes many more visualized sorting algorithms but I don’t want to overload WordPress or your computer, so I’ll leave you with two types of Radix Sort, the rest you can look up yourself!