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https://ericmjl.github.io/Network-Analysis-Made-Simple/
An introduction to network analysis and applied graph theory using Python and NetworkX
https://ericmjl.github.io/Network-Analysis-Made-Simple/
graph graph-theory live-tutorial network-analysis networkx networkx-graph networkx2 python tutorial
Last synced: 3 months ago
JSON representation
An introduction to network analysis and applied graph theory using Python and NetworkX
- Host: GitHub
- URL: https://ericmjl.github.io/Network-Analysis-Made-Simple/
- Owner: ericmjl
- License: mit
- Created: 2014-12-26T22:56:03.000Z (almost 10 years ago)
- Default Branch: master
- Last Pushed: 2024-09-23T18:12:22.000Z (3 months ago)
- Last Synced: 2024-09-25T01:16:32.626Z (3 months ago)
- Topics: graph, graph-theory, live-tutorial, network-analysis, networkx, networkx-graph, networkx2, python, tutorial
- Language: Jupyter Notebook
- Homepage: https://ericmjl.github.io/Network-Analysis-Made-Simple/index.html
- Size: 299 MB
- Stars: 1,033
- Watchers: 44
- Forks: 402
- Open Issues: 16
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome_network_science - Network Analysis Made Simple
README
# Network Analysis Made Simple
[![Build Status](https://travis-ci.org/ericmjl/Network-Analysis-Made-Simple.svg?branch=master)](https://travis-ci.org/ericmjl/Network-Analysis-Made-Simple)
Welcome to the GitHub repository for Network Analysis Made Simple!
This is a tutorial designed to teach you
the basic and practical aspects of graph theory.
It has been presented at multiple conferences (PyCon, SciPy, PyData, and ODSC)
in a variety of formats (ranging from 1.5 hr to 4 hour long workshops).
The material is designed for a live tutorial presentation,
with the code available for you to reference afterwards.## Getting Started
Head over to [the official website][nams]!
[nams]: https://ericmjl.github.io/Network-Analysis-Made-Simple
## Support the project!
If you enjoy the material, please consider doing one of the following:
1. Share it around on Twitter!
2. Purchase a copy of the [LeanPub eBook](https://leanpub.com/nams)
3. Share it with your colleagues.