Network Science with Python and NetworkX Quick Start Guide, published by Packt
This is the code repository for Network Science with Python and NetworkX Quick Start Guide, published by Packt.
Explore and visualize network data effectively
NetworkX is a leading free and open source package used for network science with the Python programming language. NetworkX can track properties of individuals and relationships, find communities, analyze resilience, detect key network locations, and perform a wide range of important tasks. With the recent release of version 2, NetworkX has been updated to be more powerful and easy to use.
This book covers the following exciting features:
- Learn how to manage users, groups, and permissions
- Encrypt and decrypt disks with Linux Unified Key Setup /Luks
- Setup SSH for remote access, and connect it to other nodes
- Understand how to add, remove, and search for packages
- Use NFS and Samba to share directories with other users
If you feel this book is for you, get your copy today!
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
G_karate = nx.karate_club_graph()
mr_hi = 0
john_a = 33
Following is what you need for this book: Copy and paste the Audience section from the EPIC.
With the following software and hardware list you can run all code files present in the book (Chapter 1-12).
| Chapter | Software required | OS required |
|---|---|---|
| 1 - 12 | Python 3.4 | Windows, Mac OS X, and Linux (Any) |
-
Page 120: Understanding how network structure influences the spread of diseases and ideas makes it possible to
should be replaced with
Understanding how network structure influences the spread of diseases and ideas makes it possible to design policies and infrastructure that protect against disease and encourage innovation.
Edward L. Platt creates technology for communities and communities for technology. He is currently a researcher at the University of Michigan School of Information and the Center for the Study of Complex Systems. He has published research on large-scale collective action, social networks, and online communities. He was formerly a staff researcher at the MIT Center for Civic Media. He contributes to many free/open source software projects, including tools for media analysis, network science, and cooperative organizations. He has also done research on quantum computing and fault tolerance. He has an M.Math in Applied Mathematics from the University of Waterloo, as well as B.S degrees in both Computer Science and Physics from MIT.
If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.