Based on this feature in the New Yorker and this project by Dan Grover.
Source data consists of a csv of tube station coordinates from Chris Bell, an adjacency list representation of the tube network graph from wikimedia, and the latest MSOA-level model-based income estimates from the neighbourhood statistics website. Data from 2007/08.
Thanks to Ben Barnett for the original version of the SVG tube map used above, and to John Galantini for the tube map font taken from his CSS tube map project.
First, run
pip install -r requirements.txt
npm install -g coffee-script uglify-js
This project uses Cactus to generate a static site from a bunch of django
templates and other source files. Data processing scripts are in bin/,
templates are in pages/ and templates/, static assets are in static/.
Pretty straightforward.
To build the frontend:
make
This will put everything in .build/.
To re-run the data processing scripts:
make data
To serve the frontend at localhost:8000 for development:
make serve