Programmers or analysts interested in studying Capital Bikeshare patterns or creating useful apps can now do a lot more. Capital Bikeshare has followed through on its promise and posted data files with individual (but anonymous) trip data.
The files, one for each quarter going back to late 2010, list individual trips, including the time each started and ended, duration, which station it started and ended at, and an identifying number for the individual bike. It doesn’t say anything about the member who used the bike, except whether they are a “registered” (annual or monthly) member or a “casual” member (daily or 3- or 5-day).
Now, people can generate tables or graphics showing the most popular station pairs, or where people most often go from an individual station, or what weather patterns make usage heavier or lighter, or where the nighttime activity is, and much more.
This data has been available for some time for London, allowing people to create animations of a day’s CaBi usage and diagrams of a single bike’s path over several days. The folks who built those and other tools can now even adapt their code to work for Capital Bikeshare, if they’re so inclined.
Arlington, DC and Alta officials agreed in November to offer the data, after discussions with Tom Fairchild of the Mobility Lab, lab collaborator and advisor Matt Caywood, and CaBi Tracker creator Daniel Gohlke. (I am working on projects for the Mobility Lab as well, but was not involved in this specific discussion.)
To make it even easier to work with the data, Dylan Barlett imported the files into Google Fusion Tables, a tool that lets people easily sort, manipulate and visualize data.
If you put together an interesting analysis or visualization, please send it to us! We’d love to post interesting things you come up with using this or other open data.