I presented this project during the Clean Energy Data Science Challenge, an event hosted by the U.S. State Department, Booz Allen Hamilton and the World Bank at Galvanize, San Francisco.
The goal was to create an open-source, user-friendly, data-driven application to facilitate the deployment of small-scale solar and micro-grids in Burma.
I munged census and geospatial data to create key indicators based on conversations with actual Burma engineers and locals. Some of the features were:
- Cellphone coverage
- Avg. Household Energy Demand
- A proxy for Potential Market Size by town in USD
- Governmental Expenditures as proxy for
The final product is an interactive application with slider widgets to filter specific market demographics, swappable axis for multi-angle visualization and the ability to hover over points for key information.
Here is an example of querying with sliders:
Swapping the axis:
- Python: Mainly using Pandas for data transformations
- Bokeh: Bokeh is an awesome visualization library for Python.
This app was served locally using Bokeh Server.
- HTML & CSS
Go you can fork this project and follow the code on this repo.