# What Is Graph and Types of Graph in Data Structure?

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Angela Bailey

Data structures are essential concepts in computer science and play a crucial role in organizing and manipulating data efficiently. One such data structure is a graph, which consists of a set of vertices or nodes connected by edges. In this article, we will explore what a graph is and delve into its different types.

## What is a Graph?

A graph is a non-linear data structure that represents relationships between various objects. It consists of two main components:

• Vertices: Also known as nodes, vertices are the fundamental units of a graph. Each vertex can hold data or be empty.
• Edges: Edges are the connections or relationships between vertices. They can be directed or undirected, indicating the flow or absence of direction between two vertices.

Graphs are widely used to represent complex systems such as social networks, computer networks, transportation networks, and more. They provide an intuitive way to visualize connections and analyze relationships between objects.

## Types of Graphs

There are several types of graphs based on their properties and characteristics. Let’s explore some of the most commonly encountered ones:

### 1. Undirected Graph

An undirected graph is a type of graph where edges have no direction associated with them. In other words, the relationship between any two vertices is symmetric and bidirectional.

To represent an undirected graph visually, we usually draw lines connecting the vertices without any arrowheads indicating direction.

### 2. Directed Graph (Digraph)

A directed graph, also known as a digraph, is a type of graph where edges have a specific direction associated with them. The relationship between two vertices in a digraph can be unidirectional or bidirectional.

In visual representation, directed edges are usually depicted using arrows indicating the direction of the relationship.

### 3. Weighted Graph

A weighted graph is a type of graph where each edge has an associated weight or value. These weights can represent various factors such as distance, cost, time, etc.

In visual representation, weights are often displayed alongside or above the edges to indicate their values.

### 4. Cyclic Graph

A cyclic graph is a type of graph that contains at least one cycle, which is a path that starts and ends at the same vertex. In other words, it is possible to traverse through the edges of a cyclic graph and return to the starting vertex.

Cyclic graphs can be either directed or undirected and may have multiple cycles within them.

### 5. Acyclic Graph

An acyclic graph is a type of graph that does not contain any cycles. In other words, it is not possible to traverse through the edges of an acyclic graph and return to the starting vertex.

Acyclic graphs can also be either directed or undirected.

### 6. Connected Graph

A connected graph is a type of graph where there exists a path between any two vertices in the graph. In other words, there are no isolated vertices in a connected graph.

The concept of connectivity applies to both directed and undirected graphs.

### 7. Disconnected Graph

A disconnected graph is a type of graph where there exist one or more isolated vertices that do not have any connections with other vertices in the graph.

In other words, it is not possible to reach certain vertices from others in a disconnected graph.

### 8. Bipartite Graph

A bipartite graph is a type of graph whose vertices can be divided into two disjoint sets in such a way that there are no edges between vertices within the same set.

Bipartite graphs find applications in various fields, including scheduling problems, network flow analysis, and more.

## Conclusion

Graphs are versatile data structures that allow us to represent and analyze relationships between objects. Understanding the different types of graphs and their characteristics is crucial when working with complex systems or solving problems related to connectivity, optimization, and network analysis.

Remember to utilize the appropriate type of graph based on your requirements and consider their properties when designing algorithms or data models for your applications!