leriomaggio / network-analysis-mscx18

Network Analysis Tutorial for MSCX Summer School

Network Analysis Tutorial using Python & networkx

MSCX Ph.D. Summer School, Salina (ME) - Italy

Lecturer: Valerio Maggio

PostDoc Data Scientist @ FBK/MPBA

Contacts:

@leriomaggio

vmaggio_at_fbk_dot_eu

Get Started

Binder

(Consider this option only if your WiFi is stable)

If you don't want the hassle of getting setup, you can use the Binder service to participate in the live tutorial. Just click on the button below:

Set up the Environment

1. Clone this repo

git clone https://github.com/leriomaggio/network-analysis-mscx18.git

2. Install Requirements

This tutorial will use Python 3

This tutorial requires the following packages:

• Python version 3.6

  • Python 3.4+ should be fine as well
  • likely Python 2.7 would be also fine, but who knows? :P

• matplotlib==2.2.3

• networkx==2.1

• pandas==0.23.0

• hiveplot==2017.10.17.21.7

• nxviz==0.5.0

• numpy==1.14.3

• jupyter==1.0.0

• scipy==1.1.0

• python-louvain==0.11

• bokeh==0.13.0

Easiest way: Anaconda Distribution of Python

If you have the Anaconda distribution of Python 3 installed on a Unix-like machine (Linux, macOS, etc.), then run make conda, which wraps the commands below.

1. $ conda env create -f environment.yml
2. $ source activate mscx
3. $ python checkenv.py

If you do not have the Anaconda distribution, I would highly recommend getting it for Windows, Mac or Linux. It provides an isolated Python computing environment that will not interfere with your system Python installation, and comes with a very awesome package manager (conda) that makes installation of new packages a single conda install pkgname away.

Alternative to Anaconda: pip install

For those who do not have the capability of installing the Anaconda Python 3 distribution on their computers, please follow the instructions below.

Run make venv, which wraps up the commands below.

1. Create a virtual environment for this tutorial, so that the installed packages do not mess with your regular Python environment.
2. $ pip install virtualenv
3. $ virtualenv mscx
4. $ source mscx/bin/activate
5. $ pip install matplotlib networkx pandas hiveplot numpy jupyter

Check your environment:

1. $ python checkenv.py

Run the Jupyter Notebook

$ jupyter notebook

Dataset References

1. Divvy Data Challenge
2. Konect Network Analysis Datasets

Credits

This material has been adapted from the tutorial Network Analysis Made Simple created by Eric Ma @ericmjl and Mridul Seth @MridulS. The original material can be found at: https://github.com/ericmjl/Network-Analysis-Made-Simple/.