Network Analysis in Python

by John R. Ladd

This short book is intended as a guide to working with networks in Python. It includes tutorials for working with NetworkX, Pandas, Altair, and other libraries.

Mainly, these tutorials are meant as a companion to Advanced Data Analysis: Networks, my course at Washington & Jefferson College. But they’re general enough to be useful to anyone curious about how to include networks into a Python data science workflow.

Network Concepts

• Data Basics
  • Set Up Jupyter Lab
  • Python
  • Pandas
  • Altair
• Visualizing Networks
  • Network Visualization
  • Networks with Altair
• Analyzing Networks
  • Working with Graph Objects
  • Metrics
  • Homophily
  • Community Detection
  • Machine Learning
• Special Networks
  • Directed Networks
  • Bipartite Networks
  • Dynamic Networks
• Creating a Network

CIS 345/397

• Advanced Data Analysis: Networks
• Schedule & Readings
• Assignments
  • Project 1: Create a Visualization
  • Project 2: Descriptive Network Analysis
  • Project 3: Predictive Network Analysis
  • Presentation: Shared Challenges
• Homework
  • 01: Networks in Python
  • 02: College Football
  • 03: Game of Thrones Visualization
  • 04: High School Interactions
  • 05: Political Books
  • 06: International Relations
  • 07: The Shape of the Web
  • 08: Affiliation and History
  • 09: Medici Family Influence
  • 10: Epidemics in Social Networks
  • 11: Search and the Web
• Course Policies
  • Criteria for Good Reports
  • Ground Rules

Resources

• Where to Find Network Data
• Key Terms and Definitions