the sparse matrix we formed in question 1 (answered below) we have to implement in adjacency list data structure and then represent it in graphical format. Can you do please?

import numpy as np import matplotlib.pyplot as plt def sparse_matrix(n): ''' Construct a sparse and a dense matrices of size 1000x1000 ''' sparse_matrix = np.zeros((n, n)) dense_matrix = np.zeros((n, n)) for i in range(n): for j in range(n): if i == j: sparse_matrix[i][j] = 1 dense_matrix[i][j] = 1 elif i < j: sparse_matrix[i][j] = 1 dense_matrix[i][j] = 1 return sparse_matrix, dense_matrix # 2. Identify the data structure to store the given sparse matrices # Adjacency list data structure # 3. Justify your selection of data structure (use adjacency list data structure) # Adjacency list data structure is used to store the sparse matrix. # It is a list of lists. # Each list contains the row index and the column index of the non-zero elements. # The list is sorted in ascending order of the row index.

original question:

1. Construct a sparse and a dense matrices of size 1000x1000

2. Identify the data structure to store the given sparse matrices

3. Justify your selection of data structure (use adjacency list data structure)

4. Write a program to implement the data structure

5. Write a function to visualize the sparse matrix in a graphical format