WattRank

A web application that ranks users based on their energy usage with "similar" users, utilizing machine learning clustering algorithms. Currently takes into account square footage of home, income, and region of the country where you live, to rank you among your similar peers by your energy bill.

Requirements

web.py
scikit-learn
numpy
scipy

Installing Requirements

sudo pip install lpthw.web
sudo pip install scikit-learn
sudo pip install numpy
sudo pip install scipy

How to Run

git clone https://github.com/rahulmohan/WattRank
cd WattRank
python bin/app.py

Then open up your browser to the address the app directs you to.

Additionally, check out WattRank-Readme.docx for more documentation on the code and algorithms being used.

Screenshots

Input Page:

Output Page:

Data Description and Link

The data being used is the RECS 2009 survey data. Find out more about it at the following link: http://www.eia.gov/consumption/residential/data/2009/index.cfm?view=characteristics