Graph Data Structures: Representing Graphs Using Matrices, Lists, & Sets

Python 3.7    |    Intermediate
  • 8 Videos | 52m 40s
  • Includes Assessment
  • Earns a Badge
In order to really understand how graphs work, it is important to know how they are implemented. There are multiple ways to represent graphs in code and each representation has its own advantages and disadvantages. In this course, you will implement graphs using three different representations - the adjacency matrix, the adjacency list, and the adjacency set. Learn how the adjacency matrix representation uses a square matrix to represent connections between the nodes of a graph and also edge weights. Next, explore how the adjacency list suffers from a major drawback: the same graph can have multiple representations. Finally, discover how the adjacency set representation has exactly one way in which a graph is represented. When you are finished with this course, you will be able to create and work with your own graph structures and optimize them for different purposes.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    model graphs using a square adjacency matrix to represent nodes and edges
    represent graphs using an adjacency matrix in Python
    represent different graph types - directed, undirected, weighted, and unweighted using adjacency matrices
  • model graphs using an adjacency list and adjacency set and compare the two representations
    represent graphs using an adjacency list in Python
    represent graphs using an adjacency set in Python
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 58s
    UP NEXT
  • Playable
    2. 
    Adjacency Matrix
    9m 59s
  • Locked
    3. 
    Representing Graphs Using an Adjacency Matrix
    9m 57s
  • Locked
    4. 
    Representing Other Graph Types Using an Adjacency Matrix
    5m 35s
  • Locked
    5. 
    Adjacency List and Adjacency Set
    8m 31s
  • Locked
    6. 
    Representing Graphs Using an Adjacency List
    8m 6s
  • Locked
    7. 
    Representing Graphs Using an Adjacency Set
    6m 42s
  • Locked
    8. 
    Course Summary
    1m 53s

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