DSA Python - Graph Representation in Python | Adjacency Matrix, List & Dictionary - Part 118 [Hindi]

🚀 Welcome to Part 118 of Code & Debug’s DSA Python Course 2025! In this lecture, we explore how to represent graphs in Python using different data structures. Understanding these representations is essential before implementing graph traversal and shortest path algorithms. 📚 What you’ll learn in this video: ✅ Difference between Adjacency Matrix vs. Adjacency List ✅ When to use which representation based on problem constraints ✅ Adjacency Matrix using 2D lists ✅ Adjacency List using lists of lists ✅ Adjacency Dictionary using Python dict for dynamic graphs ✅ Real-world use cases and memory implications 💡 Why is this important? The choice of graph representation directly affects the efficiency of your traversal algorithms like DFS, BFS, Dijkstra, Prim’s, and Kruskal’s. A solid understanding of this helps in both interview prep and building graph-based systems. 👉 📄 Access the full YouTube DSA Playlist Sheet (All Questions in Order): 🔗 https://docs.google.com/spreadsheets/d/1AWE15Fy3wD2iqu2vjK_R7cCiuvSsjYQclcdZmHpF66o/edit?usp=sharing 👉 Enroll in this FREE DSA Python course here: 🔗 https://codeanddebug.in/course/master-dsa-with-leetcode 👉 Enroll for Self-Paced Advanced DSA course here: 🔗 https://codeanddebug.in/course/zero-to-hero-python-dsa 🙏 Thank you for supporting Code & Debug! Don’t forget to like, share, and subscribe to our channel. Hit the 🔔 bell icon to stay updated with our latest lectures. #GraphRepresentation #AdjacencyMatrix #AdjacencyList #PythonGraphs #GraphDSA #CodeAndDebug #DSAPythonCourse #DSA2025 #GraphTheory #Part118 #PythonDSA #CodingInterviews