Understanding Graphs

Shreyas Naphad
4 hours ago
2 min read

Graphs are everywhere. Imagine a city map, or a social media network.

All these systems can be represented using a graph—a data structure made up of nodes (also called vertices) and edges (connections between nodes).

What Makes Up a Graph?

Nodes: Think of these as people, places, or points. Each node represents an individual entity.
Edges: These are the connections between nodes. For example, a road between two cities or a friendship on social media.

Types of Graphs

Graphs can be classified based on their structure:

Undirected Graph: Edges have no direction. A connection is mutual.
Directed Graph (Digraph): Edges have direction. Think of one-way streets or followers on Instagram.
Weighted Graph: Edges have weights or values. For instance, the distance between two cities.
Unweighted Graph: Edges are equal. No weights are assigned.

Why Do We Need Graphs?

Graphs help solve real-world problems like:

Finding Shortest Paths: Algorithms like Dijkstra’s help you find the fastest route (think Google Maps).
Social Network Analysis: Suggesting friends or connections.
Web Crawling: Exploring connections between web pages.

Basic Operations in Graphs

Add Nodes: Introduce new points.
Add Edges: Connect nodes.
Traversal: Visit nodes using:
- Depth-First Search (DFS): Explore as deep as possible before backtracking.
- Breadth-First Search (BFS): Explore all neighbors level by level.

Fun Way to Remember Graphs

Think of a group of friends planning a trip.

The nodes are your friends.
The edges are their relationships.
A directed graph shows who likes whom (but maybe not mutually).
A weighted graph could represent the cost of travel between them.

Conclusion

Graphs may sound technical, but they’re just a way to represent relationships and solve problems. They’re used in navigation apps, social media, and even AI systems. Understanding them can help you tackle problems with ease.