**What Are the Different Types of Graph in Data Structure?**

A graph is a non-linear data structure that consists of a set of vertices(or nodes) and a set of edges connecting these vertices. Graphs are widely used in computer science and have various applications, such as representing networks, social relationships, web pages, and much more. In this article, we will explore the different types of graphs commonly used in data structures.

## 1. Undirected Graph:

An undirected graph is a type of graph where the edges do not have any direction associated with them. This means that if there is an edge connecting vertex A to vertex B, then there is also an edge connecting vertex B to vertex A. Undirected graphs are often represented using adjacency lists or matrices.

## 2. Directed Graph:

A directed graph (also known as a digraph) is a type of graph where the edges have a specific direction associated with them.

This means that if there is an edge connecting vertex A to vertex B, it does not necessarily imply the existence of an edge from B to A. Directed graphs can be represented using adjacency lists or matrices as well.

## 3. Weighted Graph:

In a weighted graph, each edge has a weight or cost associated with it.

These weights can represent various properties such as distance, time, cost, etc. Weighted graphs are commonly used in algorithms like Dijkstra’s algorithm for finding the shortest path between two vertices.

## 4. Unweighted Graph:

An unweighted graph is a type of graph where all edges have equal weight or cost associated with them. Unlike weighted graphs, unweighted graphs do not consider any specific property for their edges.

## 5. Cyclic Graph:

A cyclic graph is a type of graph that contains at least one cycle.

A cycle is a path that starts and ends at the same vertex, passing through different vertices in between. Cyclic graphs can have both directed and undirected edges.

## 6. Acyclic Graph:

An acyclic graph is a type of graph that does not contain any cycles. Acyclic graphs are often used in various applications, such as representing hierarchical structures (e.g., family trees) or dependency relationships between tasks.

## 7. Connected Graph:

A connected graph is a type of graph where there is a path between every pair of vertices. In other words, there are no isolated vertices in a connected graph.

## 8. Disconnected Graph:

A disconnected graph is a type of graph where there are one or more isolated vertices, i.e., vertices that do not have any edges connecting them to other vertices.

## 9. Complete Graph:

A complete graph is a type of graph where there is an edge between every pair of distinct vertices. In other words, all the vertices in a complete graph are directly connected to each other.

### Conclusion:

In conclusion, graphs are versatile data structures with various types suited for different applications. Understanding these types can help you choose the most appropriate representation and algorithm for solving specific problems efficiently.