# Python - Sorting Algorithms

Sorting refers to arranging data in a particular format. Sorting algorithm specifies the way to arrange data in a particular order. Most common orders are in numerical or lexicographical order.

The importance of sorting lies in the fact that data searching can be optimized to a very high level, if data is stored in a sorted manner. Sorting is also used to represent data in more readable formats. Below we see five such implementations of sorting in python.

• Bubble Sort
• Merge Sort
• Insertion Sort
• Shell Sort
• Selection Sort

## Bubble Sort

It is a comparison-based algorithm in which each pair of adjacent elements is compared and the elements are swapped if they are not in order.

```def bubblesort(list):

# Swap the elements to arrange in order
for iter_num in range(len(list)-1,0,-1):
for idx in range(iter_num):
if list[idx]>list[idx+1]:
temp = list[idx]
list[idx] = list[idx+1]
list[idx+1] = temp

list = [19,2,31,45,6,11,121,27]
bubblesort(list)
print(list)
```

When the above code is executed, it produces the following result −

```[2, 6, 11, 19, 27, 31, 45, 121]
```

## Merge Sort

Merge sort first divides the array into equal halves and then combines them in a sorted manner.

```def merge_sort(unsorted_list):
if len(unsorted_list) <= 1:
return unsorted_list
# Find the middle point and devide it
middle = len(unsorted_list) // 2
left_list = unsorted_list[:middle]
right_list = unsorted_list[middle:]

left_list = merge_sort(left_list)
right_list = merge_sort(right_list)
return list(merge(left_list, right_list))

# Merge the sorted halves

def merge(left_half,right_half):

res = []
while len(left_half) != 0 and len(right_half) != 0:
if left_half[0] < right_half[0]:
res.append(left_half[0])
left_half.remove(left_half[0])
else:
res.append(right_half[0])
right_half.remove(right_half[0])
if len(left_half) == 0:
res = res + right_half
else:
res = res + left_half
return res

unsorted_list = [64, 34, 25, 12, 22, 11, 90]

print(merge_sort(unsorted_list))
```

When the above code is executed, it produces the following result −

```[11, 12, 22, 25, 34, 64, 90]
```

## Insertion Sort

Insertion sort involves finding the right place for a given element in a sorted list. So in beginning we compare the first two elements and sort them by comparing them. Then we pick the third element and find its proper position among the previous two sorted elements. This way we gradually go on adding more elements to the already sorted list by putting them in their proper position.

```def insertion_sort(InputList):
for i in range(1, len(InputList)):
j = i-1
nxt_element = InputList[i]
# Compare the current element with next one

while (InputList[j] > nxt_element) and (j >= 0):
InputList[j+1] = InputList[j]
j=j-1
InputList[j+1] = nxt_element

list = [19,2,31,45,30,11,121,27]
insertion_sort(list)
print(list)
```

When the above code is executed, it produces the following result −

```[2, 11, 19, 27, 30, 31, 45, 121]
```

## Shell Sort

Shell Sort involves sorting elements which are away from ech other. We sort a large sublist of a given list and go on reducing the size of the list until all elements are sorted. The below program finds the gap by equating it to half of the length of the list size and then starts sorting all elements in it. Then we keep resetting the gap until the entire list is sorted.

```def shellSort(input_list):

gap = len(input_list) // 2
while gap > 0:

for i in range(gap, len(input_list)):
temp = input_list[i]
j = i
# Sort the sub list for this gap

while j >= gap and input_list[j - gap] > temp:
input_list[j] = input_list[j - gap]
j = j-gap
input_list[j] = temp

# Reduce the gap for the next element

gap = gap//2

list = [19,2,31,45,30,11,121,27]

shellSort(list)
print(list)
```

When the above code is executed, it produces the following result −

```[2, 11, 19, 27, 30, 31, 45, 121]
```

## Selection Sort

In selection sort we start by finding the minimum value in a given list and move it to a sorted list. Then we repeat the process for each of the remaining elements in the unsorted list. The next element entering the sorted list is compared with the existing elements and placed at its correct position. So at the end all the elements from the unsorted list are sorted.

```def selection_sort(input_list):

for idx in range(len(input_list)):

min_idx = idx
for j in range( idx +1, len(input_list)):
if input_list[min_idx] > input_list[j]:
min_idx = j
# Swap the minimum value with the compared value

input_list[idx], input_list[min_idx] = input_list[min_idx], input_list[idx]

l = [19,2,31,45,30,11,121,27]
selection_sort(l)
print(l)
```

When the above code is executed, it produces the following result −

```[2, 11, 19, 27, 30, 31, 45, 121]
```

+
Ans: Python Data Structure Introduction - Learn Python Data Structure in simple and easy steps starting from basic to advanced concepts with examples including Introduction, Environment, Arrays, Lists, Tuples, Dictionary, 2-D Array, Matrix, Sets, Maps, Linked Lists, Stack, Queue, Dequeue, Advanced Linked list, Hash Table, Binary Tree, Search Tree, Heaps, Graphs, Algorithm Design, Divide and conquer, Recursion, backtracking, Tree Traversal, Sorting, Searching, Graph Algorithms, Algorithm Analysis, Big-O Notation, Algorithim classes, Amortized analysis, Algorithm Justifications. view more..
+
Ans: Python Data Structure Introduction - Learn Python Data Structure in simple and easy steps starting from basic to advanced concepts with examples including Introduction, Environment, Arrays, Lists, Tuples, Dictionary, 2-D Array, Matrix, Sets, Maps, Linked Lists, Stack, Queue, Dequeue, Advanced Linked list, Hash Table, Binary Tree, Search Tree, Heaps, Graphs, Algorithm Design, Divide and conquer, Recursion, backtracking, Tree Traversal, Sorting, Searching, Graph Algorithms, Algorithm Analysis, Big-O Notation, Algorithim classes, Amortized analysis, Algorithm Justifications. view more..
+
Ans: Python Data Structure Introduction - Learn Python Data Structure in simple and easy steps starting from basic to advanced concepts with examples including Introduction, Environment, Arrays, Lists, Tuples, Dictionary, 2-D Array, Matrix, Sets, Maps, Linked Lists, Stack, Queue, Dequeue, Advanced Linked list, Hash Table, Binary Tree, Search Tree, Heaps, Graphs, Algorithm Design, Divide and conquer, Recursion, backtracking, Tree Traversal, Sorting, Searching, Graph Algorithms, Algorithm Analysis, Big-O Notation, Algorithim classes, Amortized analysis, Algorithm Justifications. view more..
+
Ans: Python Data Structure Introduction - Learn Python Data Structure in simple and easy steps starting from basic to advanced concepts with examples including Introduction, Environment, Arrays, Lists, Tuples, Dictionary, 2-D Array, Matrix, Sets, Maps, Linked Lists, Stack, Queue, Dequeue, Advanced Linked list, Hash Table, Binary Tree, Search Tree, Heaps, Graphs, Algorithm Design, Divide and conquer, Recursion, backtracking, Tree Traversal, Sorting, Searching, Graph Algorithms, Algorithm Analysis, Big-O Notation, Algorithim classes, Amortized analysis, Algorithm Justifications. view more..
+
Ans: Python Data Structure Introduction - Learn Python Data Structure in simple and easy steps starting from basic to advanced concepts with examples including Introduction, Environment, Arrays, Lists, Tuples, Dictionary, 2-D Array, Matrix, Sets, Maps, Linked Lists, Stack, Queue, Dequeue, Advanced Linked list, Hash Table, Binary Tree, Search Tree, Heaps, Graphs, Algorithm Design, Divide and conquer, Recursion, backtracking, Tree Traversal, Sorting, Searching, Graph Algorithms, Algorithm Analysis, Big-O Notation, Algorithim classes, Amortized analysis, Algorithm Justifications. view more..
+
Ans: Python Data Structure Introduction - Learn Python Data Structure in simple and easy steps starting from basic to advanced concepts with examples including Introduction, Environment, Arrays, Lists, Tuples, Dictionary, 2-D Array, Matrix, Sets, Maps, Linked Lists, Stack, Queue, Dequeue, Advanced Linked list, Hash Table, Binary Tree, Search Tree, Heaps, Graphs, Algorithm Design, Divide and conquer, Recursion, backtracking, Tree Traversal, Sorting, Searching, Graph Algorithms, Algorithm Analysis, Big-O Notation, Algorithim classes, Amortized analysis, Algorithm Justifications. view more..
+
Ans: Python Data Structure Introduction - Learn Python Data Structure in simple and easy steps starting from basic to advanced concepts with examples including Introduction, Environment, Arrays, Lists, Tuples, Dictionary, 2-D Array, Matrix, Sets, Maps, Linked Lists, Stack, Queue, Dequeue, Advanced Linked list, Hash Table, Binary Tree, Search Tree, Heaps, Graphs, Algorithm Design, Divide and conquer, Recursion, backtracking, Tree Traversal, Sorting, Searching, Graph Algorithms, Algorithm Analysis, Big-O Notation, Algorithim classes, Amortized analysis, Algorithm Justifications. view more..
+
Ans: Python Data Structure Introduction - Learn Python Data Structure in simple and easy steps starting from basic to advanced concepts with examples including Introduction, Environment, Arrays, Lists, Tuples, Dictionary, 2-D Array, Matrix, Sets, Maps, Linked Lists, Stack, Queue, Dequeue, Advanced Linked list, Hash Table, Binary Tree, Search Tree, Heaps, Graphs, Algorithm Design, Divide and conquer, Recursion, backtracking, Tree Traversal, Sorting, Searching, Graph Algorithms, Algorithm Analysis, Big-O Notation, Algorithim classes, Amortized analysis, Algorithm Justifications. view more..
+
Ans: Python Data Structure Algorithm Classes - Learn Python Data Structure in simple and easy steps starting from basic to advanced concepts with examples including Introduction, Environment, Arrays, Lists, Tuples, Dictionary, 2-D Array, Matrix, Sets, Maps, Linked Lists, Stack, Queue, Dequeue, Advanced Linked list, Hash Table, Binary Tree, Search Tree, Heaps, Graphs, Algorithm Design, Divide and conquer, Recursion, backtracking, Tree Traversal, Sorting, Searching, Graph Algorithms, Algorithm Analysis, Big-O Notation, Algorithim classes, Amortized analysis, Algorithm Justifications. view more..
+
Ans: Python Data Structure Introduction - Learn Python Data Structure in simple and easy steps starting from basic to advanced concepts with examples including Introduction, Environment, Arrays, Lists, Tuples, Dictionary, 2-D Array, Matrix, Sets, Maps, Linked Lists, Stack, Queue, Dequeue, Advanced Linked list, Hash Table, Binary Tree, Search Tree, Heaps, Graphs, Algorithm Design, Divide and conquer, Recursion, backtracking, Tree Traversal, Sorting, Searching, Graph Algorithms, Algorithm Analysis, Big-O Notation, Algorithim classes, Amortized analysis, Algorithm Justifications. view more..
+
Ans: Python Data Structure Introduction - Learn Python Data Structure in simple and easy steps starting from basic to advanced concepts with examples including Introduction, Environment, Arrays, Lists, Tuples, Dictionary, 2-D Array, Matrix, Sets, Maps, Linked Lists, Stack, Queue, Dequeue, Advanced Linked list, Hash Table, Binary Tree, Search Tree, Heaps, Graphs, Algorithm Design, Divide and conquer, Recursion, backtracking, Tree Traversal, Sorting, Searching, Graph Algorithms, Algorithm Analysis, Big-O Notation, Algorithim classes, Amortized analysis, Algorithm Justifications. view more..
+
Ans: Python Network Programming - Learn Python Network Programming in simple and easy steps starting from basic to advanced concepts with examples. view more..
+
Ans: Python Network Programming Introduction - Learn Python Network Programming in simple and easy steps starting from basic to advanced concepts with examples. view more..
+
Ans: Python Netwrok Environment - Learn Python Network Programming in simple and easy steps starting from basic to advanced concepts with examples. view more..
+
Ans: Python Internet Protocol - Learn Python Network Programming in simple and easy steps starting from basic to advanced concepts with examples. view more..
+
Ans: Python IP Address - Learn Python Network Programming in simple and easy steps starting from basic to advanced concepts with examples. view more..
+
Ans: Python DNS Look-up- Learn Python Network Programming in simple and easy steps starting from basic to advanced concepts with examples. view more..
+
Ans: Python Routing - Learn Python Network Programming in simple and easy steps starting from basic to advanced concepts with examples. view more..

Rating - NAN/5
506 views