To make a heap sort algorithm, we must create a heap of the array first. The largest/smallest element is at the root of the heap, depending on the way you sorted it.Heap Sort uses a heap data structure.Ī heap is a complete binary tree. Heap Sort is one of the best sorting methods being in-place and with no quadratic worst-case complexity. Insertion doesn't perform well when close elements are far.Shell Sort has average-case and best-case complexity of O(n*log(n)).Shell Sort has worst-case complexity less or equal than O(n2).The performance of the shell sort depends on the type of sequence used for a given input array. The interval between the elements is gradually decreased based on the sequence used. With this algorithm, the array is sorted at a specific interval based on the chosen sequence. Shell Sort is a variation of Insertion Sort. Input is uniformly distributed over a range.It occurs when elements are randomly distributed in the array. It can even be better if the array is already sorted. It occurs when the elements are uniformly distributed in the buckets with a nearly equal number of elements in each bucket. Also, it can be even worse when an inappropriate sorting algorithm is used to sort elements in the buckets. It occurs when elements in the same range are put in the same bucket, resulting in more elements in some buckets than others. Bucket Sort algorithm has the worst-case complexity of O(n2).extend ( left or right ) break return result append ( right ) rightIndex += 1 if leftIndex = len ( left ) or rightIndex = len ( right ): result. append ( left ) leftIndex += 1 else : result. While ( len ( result ) < totalLen ): #Perform the required comparisons and merge the two parts If not len ( left ): return left if not len ( right ): return right result = leftIndex = 0 rightIndex = 0 totalLen = len ( left ) + len ( right ) # #meaning that it's an individual item and it's already sorted. It means that this is an individual item and is already sorted.""" #We make sure the right/left side is not empty Print ( "The left side is: ", left ) print ( "The right side is: ", right ) merged = merge ( left, right ) print ( "Merged ", merged ) return merged def merge ( left, right ): """When left side/right side is empty, Left = mergeSort ( data ) right = mergeSort ( data ) # Merge the two sorted parts into a larger piece. Into individual parts""" if len ( data ) < 2 : return data middle = len ( data ) // 2 # We break the list in two parts Wikipediaĭef mergeSort ( data ): """This function determines whether the list is broken Finally, all the elements are sorted and merged. First divide the list into the smallest unit (1 element), then compare each element with the adjacent list to sort and merge the two adjacent lists. The sorting and merging continue until the entire dataset is again a single piece.Īn example of a merge sort. It then merges the pieces in a manner that ensures that it has sorted the merged piece. The sort begins by breaking the dataset into individual pieces and sorting the pieces. It occurs when the pivot element is always the middle element or near to the middle element.Ī Mergesort works by applying the divide and conquer approach. The best-case and average-case complexity are O(n*log(n)).It occurs when the pivot element picked is always either the greatest or the smallest element. QuickSort has worst-case complexity of O(n2).I also provided solutions for each algorithm written in Python, however, if you want to challenge yourself, try it on your own before check it.□īubble sort a simple sorting algorithm that works by swapping the items between them if they are in the wrong order.Įnter fullscreen mode Exit fullscreen mode This section focus on explaining each algorithm: the concept, the complexity, and the use cases. Even if there is a lot of methods to sort data, some of them are better than others, some are more efficient for specific usages.ĭepending on the method ( recursion, iteration, comparisons ) or the data structures used, you can have a lot of possibilities. When working with data, sorting is one of the essentials tasks. I think that you got the point, so let's dive in. If you are a programmer or if you have already been interviewed for a job, then you surely know the importance of knowing and mastering algorithms in order to increase your coding level or have a chance to get hired.Įven if they may seem easy, they can really become tricky.Īnd that's why you should practice a lot.Īlgorithms are made to be practiced, not learned. In this post, I am going to show you common sorting algorithms and provide their implementation in python.
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