Network Science deals with modeling and analyzing networks. Politics, mathematics, law, computer science, finance data can be modeled as networks and in this tutorial will introduce the basic of network theory using the pydata ecosystem(NetworkX, Pandas, matplotlib) and we will use a Game of Thrones character network and the US Airport dataset to look at some real world network data.
This tutorial will introduce the basics of network theory and working with graphs/networks using python and the NetworkX package. This will be a hands on tutorial and will require writing a lot of code snippets. The participants should be comfortable with basic python (loops, dictionaries, lists) and some(minimal) experience with working inside a jupyter notebook.
Broadly the tutorial is divided into four parts:
Part A (20 mins) - Basics of graph theory, NetworkX and various examples of networks in real life.
Part B (35 mins) - Study the Game of Thrones network and find important characters and communities in the network.
Part C (35 mins) - Analyze the structure of the US Airport dataset and look at the temporal evolution of the network from 1990 to 2015.
By the end of the tutorial everyone should be comfortable with hacking on the NetworkX API, modelling data as networks and basic analysis on networks using python.
The tutorial and the datasets will be uploaded on github before the tutorial.