{"id":333,"date":"2023-03-30T11:29:16","date_gmt":"2023-03-30T11:29:16","guid":{"rendered":"https:\/\/vmlogger.com\/algorithms\/?p=333"},"modified":"2023-05-03T10:32:30","modified_gmt":"2023-05-03T10:32:30","slug":"merge-sort-in-python-the-ultimate-guide","status":"publish","type":"post","link":"https:\/\/vmlogger.com\/algorithms\/2023\/03\/30\/merge-sort-in-python-the-ultimate-guide\/","title":{"rendered":"Merge Sort in Python: The Ultimate Guide"},"content":{"rendered":"

If you’re a programmer or data scientist, you’ve probably heard of the merge sort algorithm. Merge sort is a popular and efficient sorting algorithm widely used in computer science. In this guide, we’ll explore what merge sort is, how it works, and how to implement it in Python.<\/p>\n

\n

Topics Covered<\/h3>\n
    \n
  1. What is Merge Sort?<\/li>\n
  2. What is Merge Sort Used For?<\/li>\n
  3. Implementation of Merge Sort in Python<\/li>\n
  4. Visual representation of Merge Sort<\/li>\n
  5. Is Merge Sort Faster Than Quicksort?<\/li>\n
  6. Why is Merge Sort More Effective?<\/li>\n<\/ol>\n<\/div>\n

    What is Merge Sort?<\/h2>\n

    Merge sort is based on a divide-and-conquer principle. This works by breaking down the array into smaller subarrays, sorting those subarrays, and then merging them back together. Once you will follow the below example with python code, it will be more precise.<\/p>\n

    \"Merge

    Merge Sort Visualization – Source – Wikipedia<\/p><\/div>\n

    What is Merge Sort Used For?<\/h2>\n

    Merge sort is commonly used for sorting large datasets, as it is efficient and fast, even for very large arrays. It’s also useful for parallel sorting, where multiple processors can be used to sort the data.<\/p>\n

    Implementation of Merge Sort in Python<\/h2>\n

    Following the python code to implement merge sort in Python. The time complexity of merge sort is O(n*log n)<\/code> where n<\/code> is the number of elements in the array.<\/p>\n

    \r\ndef mergeSort(array, asc=True):\r\n    '''\r\n    Time complexity : O(nlog(n)))\r\n    parameters:\r\n        array   : Array of numbers to be sorted\r\n        asc     : boolean flag to sort ascending\r\n                  descending. Default = True (ascending)\r\n    '''\r\n    midIdx = len(array) \/\/ 2\r\n   \r\n    if len(array) == 1:\r\n        return array\r\n    \r\n    leftArr = array[:midIdx]\r\n    rightArr = array[midIdx:]\r\n    # Double recursion\r\n    # 1. To keep on dividing the entire\r\n    #    in half until only one item is left\r\n    #    in both left and right side arrays\r\n    # 2. Each time those sub-arrays will be passed\r\n    #    in the other recursive function, whihc will \r\n    #    return the sorted sub array.\r\n    return sortArray(mergeSort(leftArr, asc), mergeSort(rightArr, asc), asc)\r\n    \r\ndef sortArray(leftArray, rightArray, asc):\r\n    sortedArray = [None] * (len(leftArray) + len(rightArray))\r\n    i=j=k=0\r\n    while i < len(leftArray) and j < len(rightArray):\r\n        # based on ascending or descending order\r\n        if asc:\r\n            if leftArray[i] <= rightArray[j]:\r\n                sortedArray[k] = leftArray[i]\r\n                i += 1\r\n            else :\r\n                sortedArray[k] = rightArray[j]\r\n                j += 1\r\n        else:\r\n            if leftArray[i] >= rightArray[j]:\r\n                sortedArray[k] = leftArray[i]\r\n                i += 1\r\n            else :\r\n                sortedArray[k] = rightArray[j]\r\n                j += 1\r\n        k += 1\r\n    \r\n    while i < len(leftArray):\r\n        sortedArray[k] = leftArray[i]\r\n        i += 1\r\n        k += 1\r\n    while j < len(rightArray):\r\n        sortedArray[k] = rightArray[j]\r\n        j += 1\r\n        k += 1\r\n    \r\n    return sortedArray\r\n\r\nif __name__ == \"__main__\":\r\n    arrayToSort = [4, 6, 1, 10, 8, 9, 50, 7, 56]\r\n    print(\"Array in ascending order :\", mergeSort(arrayToSort))\r\n    print(\"Array in descending order :\", mergeSort(arrayToSort, asc=False))\r\n\r\n<\/pre>\n

    Visual representation of Merge Sort<\/h2>\n

    This example shows how merge sort can be used to sort an array of integers in Python. The algorithm divides the array in half, sorts each half recursively, and then merges the sorted halves back together. Refer to the below-animated visualization gif [from Wikipedia] which explains the process of divide and conquer sorting algorithm which is also called merge sort.<\/p>\n

    \"Merge

    Merge Sort Visualization - Source - Wikipedia<\/p><\/div>\n

    Is Merge Sort Faster Than Quicksort?<\/h2>\n

    The time complexity of merge sort is O(n*log n)<\/code>, where n<\/code> is the number of elements in the array. This means that the time required to sort the array increases logarithmically with the number of elements. Both merge sort and quicksort are efficient sorting algorithms, but they have different strengths and weaknesses. Merge sort is generally considered to be more efficient for sorting large datasets, while quicksort is better for small to medium-sized datasets.<\/p>\n

    Why is Merge Sort More Effective?<\/h2>\n

    Merge sort has several advantages over other sorting algorithms, such as:<\/p>\n

      \n
    1. It is highly scalable and can handle large datasets.<\/li>\n
    2. It is a stable sorting algorithm that maintains the relative order of equal elements.<\/li>\n
    3. It is easy to implement and understand.<\/li>\n<\/ol>\n
      \n

      Conclusion:<\/h3>\n

      Merge sort is a powerful and efficient sorting algorithm widely used in computer science. Now you know everything about the merge sort algorithm such as how merge sort works<\/code> and how to implement it in Python<\/code>\n<\/div>\n<\/span>","protected":false},"excerpt":{"rendered":"

      If you’re a programmer or data scientist, you’ve probably heard of the merge sort algorithm. Merge sort is a popular and efficient sorting algorithm widely used in computer science. In this guide, we’ll explore what merge sort is, how it works, and how to implement it in Python. Topics Covered What is Merge Sort? What […]<\/p>\n","protected":false},"author":45,"featured_media":341,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[9,10],"tags":[],"class_list":["post-333","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-medium","category-sorting"],"yoast_head":"\nMerge Sort in Python: The Ultimate Guide - Algorithms<\/title>\n<meta name=\"description\" content=\"Learn how to implement the efficient and powerful merge sort algorithm in Python. 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