HTML is a powerful markup language that allows us to create visually engaging and organized content. In this tutorial, we will explore the concept of graphs in data structures and discuss 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) and a set of edges that connect these vertices. It is used to represent relationships between different elements in a dataset. Graphs are widely used in various fields such as computer science, mathematics, and social networks.

__Types of Graphs:__

There are several types of graphs commonly used in data structures. Let’s dive into each type and understand their characteristics:

## 1. Undirected Graph

An undirected graph is a type of graph where edges do not have any direction associated with them. In other words, the relationship between vertices is symmetric. For example, if vertex A is connected to vertex B, then vertex B is also connected to vertex A.

## 2. Directed Graph

A directed graph, also known as a digraph, is a type of graph where edges have an associated direction. In this type of graph, the relationship between vertices can be asymmetric. For example, if vertex A is connected to vertex B, it does not necessarily mean that vertex B is connected to vertex A.

## 3. Weighted Graph

In a weighted graph, each edge has an associated weight or cost associated with it. These weights represent some kind of value or measurement between the vertices connected by the edge. Weighted graphs are commonly used when there are varying degrees of connection strengths between vertices.

## 4. Tree

A tree can be considered as a special type of directed acyclic graph (DAG). It consists of nodes connected by edges in such a way that there are no cycles or loops.

Trees have a hierarchical structure with a single root node and multiple child nodes. They are commonly used to represent hierarchical relationships or organized data.

## 5. Bipartite Graph

A bipartite graph is a type of graph where the vertices can be divided into two distinct sets such that there are no edges between vertices within the same set. In other words, every edge connects a vertex from one set to a vertex in the other set.

## 6. Complete Graph

A complete graph is a type of graph where every pair of distinct vertices is connected by an edge. In other words, there is an edge between every pair of vertices in the graph. Complete graphs are useful in certain algorithms and mathematical proofs due to their highly connected nature.

## 7. Sparse Graph

A sparse graph is a type of graph where the number of edges is significantly lower than the maximum number of possible edges. This means that most pairs of vertices in the graph are not connected by an edge. Sparse graphs are often encountered in real-world scenarios where connections between elements are limited.

### In Conclusion

In this tutorial, we explored the concept of graphs in data structures and discussed several types of graphs such as undirected graphs, directed graphs, weighted graphs, trees, bipartite graphs, complete graphs, and sparse graphs. Each type has its own unique characteristics and applications.

By using HTML styling elements like ** for bold text, for underlined text, **

- and
- for lists, and

## ,

### , etc. for subheaders, we can create visually engaging content that not only informs but also grabs the reader’s attention.

Remember to utilize these HTML styling elements effectively in your own content to make it more engaging and organized!