The time complexity of any of the sorting algorithm and represent it graphically

Algorithm:

Algorithm BubbleSort(array,size) start:=time;

for i:=0 to n do

{

for j:=i+1 to n do

{

if (array[i]>array[j]) then

{

temp = array[i]; array[i] = array[j]; array[j] = temp;

}

}

}

end:=time;

Source Code:

import time import random

import matplotlib.pyplot as plt import numpy as np

 

def bubble_sort_time(n): 

start = time.time()

 

array = []

for i in range(n):

rannum = random.randint(1, n) array.append(rannum)

 

leng = len(array) for i in range(leng):

for j in range(i, leng):

if (array[i] > array[j]): temp = array[i] array[i] = array[j] array[j] = temp

 

end = time.time()

print("Execution Time for Sorting", n, "Values:", end-start) return end - start

exetime = [bubble_sort_time(n) for n in range(1000, 7000, 1000)] 

x = np.array([1000, 2000, 3000, 4000, 5000, 6000])

plt.title("Linear Graph for Execution Time of Bubble Sort")

plt.xlabel("Values")

plt.ylabel("Execution Time") plt.plot(x, exetime, marker='o') 

plt.show()