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.
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.
Some graph algorithms implemented in C/C++ and Python
It consists in basic metrics and functions to describe networks. I use as an example two synthetic networks.
CISER Workshop Materials - Social Network Analysis in Python
Materials for shortest paths problems with networkx
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