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 impact of network science

As the world becomes increasingly interconnected, network science is proving to be a useful tool for understanding those connections. Network science is used regularly to do the following:

  • Predict and prevent the spread of contagious diseases
  • Evaluate and improve the electric grid, road network, and other infrastructure networks
  • Understand the economics of international trade
  • Understand the spread of information on social media

The preceding applications might give the impression that network science is an important tool for improving society, and it absolutely can be. However, the powerful techniques of network science also raise important ethical questions. Network techniques can be used to infer information about individuals—such as their political party or sexual orientation—without that individuals consent. Similarly, network...