We here are very big fans of NetworkX as a graph library and its comprehensive set of graph algorithms. For many though, working with NetworkX involves a steep learning curve. This guide is designed as an aid for beginners and experienced users to find specific tips and explore the world of complex networks.
Some scripts/guides for working with Neo4j in Python.
Extended material of "Introduction to graph theory and complex network analysis". Master in Informatics program, Austral University of Chile.
This is a simple collection of scripts to visualize the art graph with NetworkX and Matplotlib.
Some graph algorithms implemented in C/C++ and Python
This repository is adapt from the course materials for Honors Engineering Analysis at Northwestern University. The course is designed for Engineering first-year undergraduate students to learn about linear algebra and its applications.
It consists in basic metrics and functions to describe networks. I use as an example two synthetic networks.
Materials for shortest paths problems with networkx
CISER Workshop Materials - Social Network Analysis in Python
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