About the Book
As the accompanying book to the popular Network Analysis Made Simple series created and taught by Eric Ma and Mridul Seth at Python, SciPy, ODSC and PyData conferences, come learn:
- about the NetworkX API
- about the basics and fundamentals of graph theory
- how to read and write graphs using modern data formats (e.g. pandas DataFrames)
- an introduction to advanced topics, including bipartite graphs, how matrices and linear algebra relate to graph theory, and statistical inference on graphs
- through two case studies to help you apply the concepts and ideas learned throughout the book
To aid your learning journey, we also have a GitHub repository with Jupyter notebooks that you can execute locally or on Binder! You can find it here on GitHub. Pick up this book for a self-paced introduction, or as a reference after taking the tutorial, or simply purchase it because you appreciate the work we've put in over the past five years to make and refine the material, and want to support further updates as the Python data science ecosystem evolves!
About the Authors
Eric is a data scientist at the Novartis Institutes for Biomedical Research. There, he conducts biomedical data science research, with a focus on using Bayesian statistical methods in the service of making medicines for patients. Prior to Novartis, he was an Insight Health Data Fellow in the summer of 2017, and defended his doctoral thesis in the Department of Biological Engineering at MIT in the spring of 2017.
Eric is also an open source software developer, and has led the development of pyjanitor, a clean API for cleaning data in Python, and nxviz, a visualization package for NetworkX. In addition, he gives back to the open source community through code contributions to multiple projects.
His personal life motto is found in the Gospel of Luke 12:48.