Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Applying Math with Python

You're reading from   Applying Math with Python Over 70 practical recipes for solving real-world computational math problems

Arrow left icon
Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781804618370
Length 376 pages
Edition 2nd Edition
Languages
Concepts
Arrow right icon
Author (1):
Arrow left icon
Sam Morley Sam Morley
Author Profile Icon Sam Morley
Sam Morley
Arrow right icon
View More author details
Toc

Table of Contents (13) Chapters Close

Preface 1. Chapter 1: An Introduction to Basic Packages, Functions, and Concepts 2. Chapter 2: Mathematical Plotting with Matplotlib FREE CHAPTER 3. Chapter 3: Calculus and Differential Equations 4. Chapter 4: Working with Randomness and Probability 5. Chapter 5: Working with Trees and Networks 6. Chapter 6: Working with Data and Statistics 7. Chapter 7: Using Regression and Forecasting 8. Chapter 8: Geometric Problems 9. Chapter 9: Finding Optimal Solutions 10. Chapter 10: Improving Your Productivity 11. Index 12. Other Books You May Enjoy

Getting the basic characteristics of networks

Networks have various basic characteristics beyond the number of nodes and edges that are useful for analyzing a graph. For example, the degree of a node is the number of edges that start (or end) at that node. A higher degree indicates that the node is better connected to the rest of the network.

In this recipe, we will learn how to access the basic attributes and compute various basic measures associated with a network.

Getting ready

As usual, we need to import the NetworkX package under the nx alias. We also need to import the Matplotlib pyplot module as plt.

How to do it...

Follow these steps to access the various basic characteristics of a network:

  1. Create the sample network that we will analyze in this recipe, like so:
    G = nx.Graph()
    G.add_nodes_from(range(10))
    G.add_edges_from([
        (0, 1), (1, 2), (2, 3), (2, 4),
        (2, 5), (3, 4), (4, 5), (6, 7),
        ...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image