I’ve been meaning to write a bit about data visualisation for the last few months, but to be honest, brewing beer is far more fun to do and write about. Beer is something that is quite close to my heart, I love the stuff, it’s the best drink in the world as far as I’m concerned. You might be wondering why I’m going on about beer, when I’m supposed to be talking about data visualisation though. It just happens that I use a website/mobile app called Untappd, to log what beer I drink and where and when I drank it. It also so happens that Untappd have a public API for interacting with their database, so I have a readily accessible dataset that I’m intimately familiar with.
I had a half hearted fiddle with the dataset of my beer drinking habits at the turn of the year, but I didn’t really do it properly, or to the extent I wanted to. I made a load of bubble graphs of various things, like which breweries had I drunk most beers from, that sort of thing. There wasn’t really any in depth analysis of when I drink beer, or how my beer drinking habits have changed since I started using the service though.
I’ve decided it’s about time to have a proper go at it and to learn a bit of Python while we’re at it. There will be a number of posts after this dealing with extracting the data with the Untappd API, mining the corpus to produce usable data sets and finally about how to visualise those sets. The posts will come when they come, hopefully there wont be too much of a gap between them.