NOTE: This repo will be updated before the tutorial so make sure to pull new changes.

For this tutorial, you will need Python 3 and the following packages:

• networkx
• pandas
• matplotlib
• numpy
• jupyter

Python2 may/may not work, no promises :)

Or you can use Binder (only if you have a stable WiFi connection)

and another deployment of Binder https://notebooks.gesis.org/binder/v2/gh/mriduls/pydata-networkx/master

If you have a microsoft account you can use Microsoft Azure notebooks too using https://notebooks.azure.com/MridulS/libraries/pydata-networkx, click on clone and you are good to do :)

HTML notebooks

• introduction-and-game-of-thrones-instructor
• US-aiports-instructor

• $ cd /path/to/your/directory
• Clone the repository from GitHub $ git clone https://github.com/mriduls/pydata-networkx
• $ cd pydata-networkx

OR

• Download the required notebooks from https://github.com/MridulS/pydata-networkx/archive/master.zip
• unzip the files and change the directory to $ cd pydata-networkx-master

• Create a virtual environment for this tutorial, so that the installed packages do not mess with your regular Python environment.
  • $ (sudo) pip install virtualenv
  • $ virtualenv -p python3 networkx
  • $ source networkx/bin/activate
• $ pip install -r requirements.txt

If you have the Anaconda distribution of Python 3 installed, then run the commands below.

• $ conda env create -f environment.yml
• $ source activate networkx

• $ python checkenv.py

$ jupyter notebook

Your browser will open to an index page where you can click on a notebook to run it.

There is an adpated version of this tutorial in Spanish, thanks to @iris9112 -> https://github.com/iris9112/pycon2019_iris9112

This tutorial is built on and inspired by the previous offerings of this tutorial at PyData LA 2018, PyData NYC 2018, PyData Delhi 2018, SciPy 2018, PyCon US 2018, PyData London 2018, PyData NYC 2017, PyConDE 2017, PyCon PL 2017, EuroSciPy 2017, EuroSciPy 2016, SciPy India 2015 and is a part of (notebooks 7 and 8) Eric Ma's tutorial Network Analysis made Simple https://github.com/ericmjl/Network-Analysis-Made-Simple