Sorting is an expensive task for the computer CPU, it depends on the amount of data and the way the data is organized initially. This mix of possibilities made developers create several algorithmic solutions that can be apllied to every language.
.sort(), so why should I do it manually?
A: Sorting algorithms is one of the first lessons in Computer Science because it helps you train your mind to think like a computer. It is a great practice to fully understand the concepts of algorithms and code.
A: There is more than we can count, the top 10 in popularity are:
It's the simplest of the sorting algorithms. It repeatedly swap adjacent elements to arrange them ascendingly, the algorithm has a "
wall" that represents the last position to be compared, the wall keeps moving from right to left, shrinking the comparison size until the entire list is sorted.
📺 In this link, you will find a relly good 2 min video explanation.
📺 Here is a really weird group of bulgarian's dancing the bubble-sort algorithm.
Selection also has a wall, but in this case, it marks the beginning of the loop, the algorithm then looks for the smallest item and swaps it with the initial one, then it moves the wall one position to the right to avoid looking again that same item.
📺 In this link, you will find a relly good 3 min video explanation about the selection sort algorithm.
Cocktail Shaker works in both fronts at the same time: It looks for the biggest value scanning from left to right and it also looks for the smallest one when its coming back from right to left. It has 2 walls (both for each side of the list), and both walls keep shrinking until they hit each other, when that happens the array is fully sorted.
📺 In this link, you will find a relly good 3 min video explanation about the Cocktail Shaker Sort algorithm.
Insertion sort involves going through a pile, taking one item, comparing it to the first, swapping places if one item is larger than another and continuing this process until the minimum item is in the correct location.
📺 In this link, you will find a relly good 3 min video explanation about the insertion sort algorithm.
Merge sort is a more difficult algorithm because it uses recursivity. It is an example of a divide-and-conquer type sorting-algorithm, it splits the unsorted array into two parts and then recursively applies merge sort to these sub-arrays to further split the arrays until you are left with a bunch of single-element arrays. Then, you compare single-element arrays to one another before recombining them into a two-element, sorted array (and so on). It will end up with a single, sorted array of length n.
📺 In this link, you will find a relly good 4 min video explanation about the merge sort algorithm.
Uses the same "divide and conquer" strategy to gain the same advantages. It first selects a value, which is called the pivot value. The role of the pivot value is to assist with splitting the list. The actual position where the pivot value belongs in the final sorted list, commonly called the split point, will be used to divide the list for subsequent calls to the quick sort.
Partitioning begins by locating two position markers—let’s call them
rightmark—at the beginning and end of the remaining items in the list (positions 1 and 8 in ). The goal of the partition process is to move items that are on the wrong side with respect to the pivot value while also converging on the split point.
We begin by incrementing
leftmark until we locate a value that is greater than the pivot value. We then decrement
rightmark until we find a value that is less than the pivot value. At this point we have discovered two items that are out of place with respect to the eventual split point. For our example, this occurs at 93 and 20. Now we can exchange these two items and then repeat the process again.
At the point where
rightmark becomes less than
leftmark, we stop. The position of
rightmark is now the split point. The pivot value can be exchanged with the contents of the split point and the pivot value is now in place. In addition, all the items to the left of the split point are less than the pivot value, and all the items to the right of the split point are greater than the pivot value. The list can now be divided at the split point and the quick sort can be invoked recursively on the two halves.
quickSort function invokes a recursive function,
quickSortHelper begins with the same base case as the merge sort. If the length of the list is less than or equal to one, it is already sorted. If it is greater, then it can be partitioned and recursively sorted. The
partition function implements the process described earlier.
📺 In this link, you will find a relly good 4 min video explanation about the Quick Sort algorithm.
Here is another great visualization with all the most used algorithms: https://codepen.io/msurguy/pen/fBDJA
Here is a real life benchmark of all the mayor sorting algorithms: https://codepen.io/villa7/pen/LyLVbj
The most efficient way to learn: Join a cohort with classmates like yourself, live streamings, coding jam sessions, live mentorships with real experts and keep the motivation.
From zero to getting paid as a developer, learn the skills of the present and future. Boost your professional career and get hired by a tech company.
Start a career in data science and analytics. A hands-on approach with interactive exercises, chat support, and access to mentorships.
Keep your motivation with this 30 day challenge. Join hundreds of other developers coding a little every day.
Start with Python and Data Science, Machine Learning, Deep Learning and maintaining a production environment in A.I.