hagarmar / Network-Analysis-Made-Simple

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Network-Analysis-Made-Simple

Getting Set Up

For this tutorial, you will need the following packages:

1. Python 3
2. matplotlib
3. networkx
4. pandas
5. hiveplot - do not do conda install hiveplot, but pip install hiveplot.
6. numpy

Clone the repository

1. $ cd /path/to/your/directory
2. Clone the repository to disk:
   1. $ git clone https://github.com/ericmjl/Network-Analysis-Made-Simple.git
3. $ cd Network-Analysis-Made-Simple

Easiest way: Anaconda Distribution of Python

If you have the Anaconda distribution of Python 3 installed, then follow this set of instructions.

1. $ conda env create -f environment.yml
2. $ source activate network

Finally, check your environment by running the following command:

1. $ 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.

If you're not using Python 3, then check out @jakevdp's talk at SciPy2015 to find out why!

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.

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 network 4. $ source network/bin/activate
2. $ pip install matplotlib networkx pandas hiveplot numpy

Finaly, check your environment:

1. $ python checkenv.py

Feedback

If you've attended this workshop, please leave feedback!.

Issues?

If you're facing difficulties, please report it as an issue on this repository.

Credits

1. Divvy Data Challenge: https://www.divvybikes.com/datachallenge

Resources

1. Jon Charest's use of Circos plots to visualize networks of Metal music genres. blog post notebook