Tracking, Visualising and Cycling
Along with Martin Zaltz Austwick, who blogs as Sociable Physics, I led a workshop session as part of CASA’s annual conference. The topic was “Tracking, Visualising and Cycling” and focused on analysing and mapping bikeshare data. I concentrated on mapping the near-real-time docking station data, while Martin graphed journey data. Both of us used Google Drive as a quick an easy platform to map spatial data and graph it. The techniques that the participants were led through are relatively rudimentary, but hopefully acheived our main purposes of demonstrating the availability of such data and the utility of Google Drive for quick analysis, without leaving anyone on the course behind.
After short presentations by Martin and myself, presenting our recent related output, there were two practical sessions. In the first session, I led participants through downloading the live dock locations/status JSON data files from bikeshare systems in the US, before hacking the JSON into a CSV suitable for upload to Google Drive and showing on a map as a Google Fusion Table. A calculated column was then added to show the empty/full ratio and the docking stations on the maps were coloured appropriately. The result looked a bit like this (if the New York dataset was picked):
A couple of gotchas we ran into: (1) If using Notepad, don’t save the JSON text, as that will “burn in” linebreaks that break it. (2) If you don’t see Google Fusion Tables in your Google Drive apps menu, you need to add it as an app using the button at the bottom of the popup.
Martin then followed by showing participants how to download journey data from the Washington DC “Capital Bikeshare” website, extracting just the data for Saturday 30 June 2012, extracting the number of minutes each journey took in Excel, binning the journeys by minute and then plotting it on a Google Speadsheet chart. An additional section was breaking down the plots by user type – showing a pronounced difference between Subscriber and Casual hires – the latter generally taking much longer for their journeys.