Python code for Adjacency Matrix - Adjasency List | DSA in Tamil | DSA with Python смотреть онлайн

Both adjacency list and adjacency matrix are commonly used data structures to represent a graph.

An adjacency list is a collection of unordered lists used to represent a finite graph. Each list describes the set of neighbors of a vertex in the graph. The list is implemented using an array or linked list data structure. Each element of the array or linked list represents a vertex in the graph, and the list associated with the element contains the vertices that are adjacent to it.

On the other hand, an adjacency matrix is a 2-dimensional array used to represent a finite graph. The rows and columns of the matrix represent the vertices in the graph. The entry at row i and column j represents whether there is an edge between vertex i and vertex j. If there is an edge between vertices i and j, the value at the entry will be 1. Otherwise, it will be 0.

The choice between the two data structures depends on the specific application and the type of operations that need to be performed on the graph. An adjacency list is usually more space-efficient than an adjacency matrix for sparse graphs, where the number of edges is much smaller than the number of vertices. It is also more efficient for certain graph algorithms that require traversing the neighbors of each vertex. On the other hand, an adjacency matrix is more space-efficient for dense graphs, where the number of edges is close to the maximum possible. It is also more efficient for certain graph algorithms that require checking the presence or absence of an edge between two vertices.