Listening habits using LastFM data V1.
August 19, 2014
It turns that out I’ve listened to Justin Beiber for a total of just over 45 minutes, across 2 albums and 5 unique tracks. This somehow happened in December 2012 and thankfully has never been repeated since.
It’s been a while since my last post, (apologies on that front), but today’s post follows on from that and continues my journey into visualising my personal music habits using LastFM data. A couple of weeks ago on Thursday, I was fortunate enough to be speaking at the London Quantified Self Meetup about that, video to follow shortly.
NB: the Wikipedia web view seems to not load for some people. Download the workbook and view it in Tableau Reader or Tableau Desktop.
Exporting the data
After quite a bit of FAQ hunting and scripting here and there, I finally managed to get an export of my LastFM data in a format that I could do something with. The export included: Time in the form of an epoc time stamp, Track name, Artist Name, Album Name, Track MBID, Artist MBID and album Album MBID. Wondering what MBID’s are? they’re mega useful. In short they allow you to uniquely identify an attribute in the event that say two artists have the same name or two albums have the same title, more here. Once exported, the rest of the process is described in rough detail in the QS presentation above. Feel free to drop questions below.
Originally published at timngwena.com.
