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Welcome

Hey, thanks for stopping by!

Network Analysis Made Simple is a collection of Jupyter notebooks designed to help you get up and running with the NetworkX package in the Python programming langauge. It's written by programmers for programmers, and will give you a basic introduction to graph theory, applied network science, and advanced topics to help kickstart your learning journey. There's even case studies to help those of you for whom example narratives help a ton!

We hope you enjoy learning from it.

Introduction Videos

At the beginning of each "chapter", there's an introduction video just like the one you'll see embedded below. Those videos will give you an overview of the chapter, particularly what to look out for and what the learning goals are, and are designed to orient you on the right path. If you're not the audio/visual kind, feel free to skip past them :). Because they're hosted on YouTube, if you need captions, hit the captions button to get access to them.

Using the book

There are three ways to use this website/web book.

Firstly, you can view everything online at this site. Use the navigation to help you get around, or search for a specific topic that you're interested in.

Secondly, you can launch a binder session. Binder lets you execute the notebook code inside the book. Click on the Binder button below to get started!

Binder

Finally, you can pick up the official EPUB/MOBI/PDF version of the book on LeanPub! Purchasing a copy helps support the authors, and funds future improvements and updates to the book, which you will continue to receive as we make updates!

Feedback

If you have feedback for the eBook, please head over to our GitHub repository and raise an issue there.

Support us!

If you find the book useful, you can support the creators in the following ways:

  1. Star the repository! It costs you nothing, and helps raise the profile of the book.
  2. Share the website with your colleagues! It also costs you nothing, and helps share the good stuff with those you think might benefit from it.
  3. Take the official companion courses and projects on DataCamp! It does cost some money, so we totally understand if you'd prefer not to, but it does buy us coffee :).
  4. Support Eric Ma on Patreon with a monthly coffee pledge to keep him caffeinated, which helps him make other good material to share.
  5. Follow Eric and Mridul on Twitter at @ericmjl and @Mridul_Seth
  6. Purchase the companion book on LeanPub and fund coffee that way too!