Algorithms in Python | Quick Sort| Full Code | Telugu
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Algorithms in Python | Quick Sort | Full Code with Time Complexity explanation| Telugu using Recursion
Quick sort is a divide and conquer algorithm. It works by selecting a 'pivot' element from the array and partitioning the other elements into two sub-arrays, according to whether they are less than or greater than the pivot. For this reason, it is sometimes called partition-exchange sort.The sub-arrays are then sorted recursively. This can be done in-place, requiring small additional amounts of memory to perform the sorting.
Python Code Implementation
list_num = [5, 6, 8, 3, 4, 5, 2, 11]
def quick_sort(sequence):
if len(sequence) LESS THAN EQUAL TO 1:
return sequence
else:
lower_list = []
greater_list = []
pivot = sequence.pop()
for item in sequence:
if item LESS THAN pivot:
lower_list.append(item)
else:
greater_list.append(item)
return quick_sort(lower_list) + [pivot] + quick_sort(greater_list)
print(quick_sort(list_num))
Time Code
00:00 Intro to Quick Sort
05:21 Python Implementation
Time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm
Time Complexity is commonly expressed using big O notation, typically O(n), O (logn), O(n^2), O(2^n), O(n!) etc where n is the input size in units of bits needed to represent the input.
Best/ Average Case Time COmplexity - n log n
Worst Case Time Complexity - O(n2)
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