Graph Representation

Understand key graph representation methods including adjacency matrices and adjacency lists. Explore how each stores graph data differently, their space and time complexities, and scenarios for their optimal use. This lesson prepares you to implement graph algorithms effectively in coding challenges and interviews.

We'll cover the following...

- Introduction
  - Adjacency matrix
- - Adjacency list

Introduction

There are many ways to represent a graph. The two most common ways of representing a graph are explained below:

Adjacency matrix

An adjacency matrix is a V*V binary matrix A. Element $A_{i,j}$ , is 1 if there is an edge from vertex i to vertex j. Else, $A_{i,j}$ , is 0.

Note: A binary matrix is a matrix in which the cells can have only one of two possible values - either 0 or 1.

The adjacency matrix can also be modified for the weighted graph in which instead of storing 0 or 1 in $A$ ...

1.Overview

2.Number Theory

Assessment

3.Divide and Conquer

4.Greedy Algorithms

Assessment

5.Recursion and Backtracking

Assessment

6.Dynamic Programming

7.Graphs

8.Bonus Lessons

Graph Representation

Introduction

Adjacency matrix