Quick Sort Algorithm in Python.

• Selecting the first and last element as the pivot is simple and efficient in implementation. However, this approach might lead to unbalanced partitions if the array is already sorted or nearly sorted.

• Choosing the middle element of the array as the pivot. This method often provides a better pivot choice, especially for larger datasets.

• Step 1: Select an element from the array as the pivot (commonly the last element).

• Step 2: Rearrange the elements in the array so that elements smaller than the pivot are placed before it, while elements larger than the pivot are placed after it. 

• Step 3: After Step 2,  the pivot assumes its correct position in the sorted array.

• Step 4: Apply Quick Sort recursively to the subarrays formed by partitioning until the entire array is sorted.

# Python code implementation of Quick Sort Algorithm
def partition(arr, low, high):
    # Choose the last element as the pivot    
    pivot = arr[high]  
    i = low - 1  # Index of smaller element
    
    for j in range(low, high):
        if arr[j] < pivot:
            i += 1
            arr[i], arr[j] = arr[j], arr[i]
    arr[i + 1], arr[high] = arr[high], arr[i + 1]
    return i + 1

def quick_sort(arr, low, high):
    if low < high:
        # Partitioning index
        pi = partition(arr, low, high)

        # Recursively sort elements before and after partition
        quick_sort(arr, low, pi - 1)
        quick_sort(arr, pi + 1, high)

# Example usage:
arr = [64, 34, 25, 12, 22, 11, 90]
quick_sort(arr, 0, len(arr) - 1)
print("Sorted array:", arr)

Sorted array: [11, 12, 22, 25, 34, 64, 90]