# What Is Graph in Data Structure and Its Types?

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Heather Bennett

Data structures are an essential component of computer science and play a vital role in organizing and managing data efficiently. One such data structure is a graph. In this article, we will explore what a graph is, its uses, and the different types of graphs.

## What is a Graph?

A graph is a non-linear data structure consisting of a set of vertices (also known as nodes) connected by edges. It represents relationships between objects or entities. Graphs can be visualized as diagrams, where the nodes represent the objects, and the edges represent the connections between them.

## Types of Graphs

### 1. Undirected Graph

An undirected graph is a type of graph where edges have no direction.

The relationship between nodes is symmetric. If there exists an edge between node A and node B, it implies that there is also an edge between node B and node A.

### 2. Directed Graph

A directed graph (or digraph) is a type of graph where edges have direction.

This means that the relationship between nodes is asymmetric. If there exists an edge from node A to node B, it does not imply that there exists an edge from node B to node A.

### 3. Weighted Graph

A weighted graph assigns weights or costs to each edge in the graph. These weights can represent various attributes such as distance, cost, or capacity associated with the connection represented by the edge.

### 4. Unweighted Graph

An unweighted graph does not assign any weights to its edges. All edges are considered equal in terms of importance or cost.

## Graph Operations

Graphs support various operations that allow us to manipulate and analyze their structure. Some of the common operations include:

• Add Vertex: Adds a new node to the graph.
• Add Edge: Creates a connection between two nodes in the graph.
• Remove Vertex: Deletes a node from the graph.
• Remove Edge: Removes the connection between two nodes in the graph.
• Traverse Graph: Visits all nodes in the graph using different traversal algorithms such as depth-first search (DFS) or breadth-first search (BFS).

## Applications of Graphs

Graphs have numerous applications across various domains. Some common applications include:

• Social Networks: Graphs can represent social networks, where users are nodes and connections between them are edges. They help identify communities, recommend friends, and analyze network patterns.
• Road Networks: Graphs can represent road networks, where intersections are nodes and roads are edges. They assist in finding shortest paths, calculating distances, and optimizing traffic flow.
• Scheduling and Planning: Graphs can be used for scheduling tasks or planning routes by representing dependencies as edges between tasks or locations.
• Circuit Design: Graphs aid in designing electrical circuits by representing components as nodes and connections as edges.

In conclusion, graphs are versatile data structures that allow us to model relationships between objects or entities. Understanding different types of graphs and their applications is crucial for solving real-world problems efficiently.