Austin's transit authority, CapMetro, recently rolled out real-time updates for all of it's buses. Fortunately for data lovers like me, they also opened up the data behind these updates! Obviously, my first thought upon learning this was to explore how I could visualize it.
I have always been inspired by Eric Fischer's work with Twitter data, and I thought that his techniques could work well with this data set. Fortunately for me, he was generous enough to document how he generated his maps. So, using Mapbox, I took a crack at it!
This map plots 515,296 data points generated by all buses running from March 5, 2015 to March 8, 2015. In order to collect the data, I hit the real-time data every 30 seconds using a tiny application I wrote in Go and added it to a Postgres database.
I initially mapped this using just D3, but I felt it really needed the benefits that Mapbox provided such as streets, points of interest, and zooming. While I could have taken care of the zooming with D3, the performance cannot match that of the tiles.
I hope you enjoy the map as much as I enjoyed making it! I am going to work on an article documenting how I created it soon. If you have any questions or comments, let me know here.