Book Image

Network Science with Python and NetworkX Quick Start Guide

By : Edward L. Platt
Book Image

Network Science with Python and NetworkX Quick Start Guide

By: Edward L. Platt

Overview of this book

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. If you’re a data scientist, engineer, or computational social scientist, this book will guide you in using the Python programming language to gain insights into real-world networks. Starting with the fundamentals, you’ll be introduced to the core concepts of network science, along with examples that use real-world data and Python code. This book will introduce you to theoretical concepts such as scale-free and small-world networks, centrality measures, and agent-based modeling. You’ll also be able to look for scale-free networks in real data and visualize a network using circular, directed, and shell layouts. By the end of this book, you’ll be able to choose appropriate network representations, use NetworkX to build and characterize networks, and uncover insights while working with real-world systems.
Table of Contents (15 chapters)

The circular layout

Perhaps the simplest network layout, the circular layout, places the nodes of a network evenly around a circle. The benefits of this layout include the following points:

  • Highlighting local structure
  • Clearly showing each individual edge

Because the circular layout places all nodes around the outside of a circle, it leaves much space unused, and is best-suited for small networks.

Similarly, the center of the circle provides an excellent space to visualize edges, as long as the network is sparse enough to prevent crowding the available space.

NetworkX provides a circular layout through the circular_layout() function. As with all NetworkX layouts, it creates a dictionary that maps node labels to (x, y) tuples, which can then be passed as the pos argument to any of the drawing functions.

Applying the default circular layout to the Zachary karate club network creates...