# What Is Graph and Its Types in Data Structure?

//

Larry Thompson

A graph is a non-linear data structure that represents a collection of interconnected nodes or vertices. It consists of a set of vertices and a set of edges that connect these vertices. Graphs are widely used in computer science and other fields to represent relationships between objects or entities.

## Types of Graphs:

### 1. Undirected Graph:

An undirected graph is a graph where the edges do not have any direction.

In other words, the relationship between two vertices is bidirectional. If there is an edge connecting vertex A to vertex B, then there is also an edge connecting vertex B to vertex A.

### 2. Directed Graph:

A directed graph, also known as a digraph, is a graph where the edges have a specific direction.

This means that the relationship between two vertices is unidirectional. If there is an edge connecting vertex A to vertex B, it does not imply that there is an edge connecting vertex B to vertex A.

### 3. Weighted Graph:

A weighted graph is a graph where each edge has an associated weight or cost. These weights can represent various properties such as distance, time, or cost between the connected vertices.

### 4. Unweighted Graph:

An unweighted graph is a graph where all edges have the same weight or do not have any associated weight at all.

## Graph Representation:

There are two common ways to represent graphs in computer science:

### 1. Adjacency Matrix:

An adjacency matrix represents a graph as a two-dimensional array of size V x V, where V represents the number of vertices in the graph. Each cell in the matrix represents whether there exists an edge between two vertices.

Example:

```1  2  3
--------
1| 0  1  1
2| 1  0  0
3| 1  0  0
```

### 2. Adjacency List:

An adjacency list represents a graph as an array of linked lists or vectors. Each element of the array corresponds to a vertex, and the linked list/vector associated with each element stores its adjacent vertices.

Example:

```1: [2,3]
2: [1]
3: [1]
```

## Graph Operations:

Graphs support various operations, including:

• Add Vertex: Adds a new vertex to the graph.
• Add Edge: Adds a new edge between two vertices in the graph.
• Delete Vertex: Removes a vertex and its associated edges from the graph.
• Delete Edge: Removes an edge between two vertices in the graph.
• Traverse Graph: Visits all vertices in the graph using traversal algorithms like Depth-First Search (DFS) or Breadth-First Search (BFS).
• Finding Paths: Finds paths between two vertices in the graph using algorithms like Dijkstra’s algorithm or A* search algorithm.

In conclusion, graphs are versatile data structures that allow us to represent and analyze complex relationships between objects. Understanding different types of graphs and their representations is crucial when solving problems that involve networks, social connections, routing algorithms, and many other domains.