http://forums.flowingdata.com/ Strength in Numbers en Sun, 12 Feb 2012 03:23:43 +0000 http://forums.flowingdata.com/topic/tracking-music-play-statistics-via-itunes#post-1956 Tue, 19 Oct 2010 15:51:42 +0000 JuliaJ 1956@http://forums.flowingdata.com/ <p>Have you seen this? <a href="http://www.leebyron.com/what/lastfm/" rel="nofollow">http://www.leebyron.com/what/lastfm/</a></p> <p>I absolutely love the idea of a stream graph and it's intriguing to see how musicians can fade and reappear across time. Just a thought.</p> <p>Julia </p> http://forums.flowingdata.com/topic/tracking-music-play-statistics-via-itunes#post-1733 Fri, 14 May 2010 10:32:44 +0000 carolinebeavon 1733@http://forums.flowingdata.com/ <p>Hey</p> <p>This sounds like a great project.</p> <p>I tackled the "genre/plays etc" question for my MA Online Journalism - using Manyeyes. At the time I had been looking into ways to capture live data from my iTunes library and I drew a blank. (although granted I am new to data visualization). </p> <p>In the end I resorted to a "snapshot" of my listening and analyzed the results, and the anomalies it threw up.</p> <p><a href="http://carolinebeavon.com/2010/03/18/looks-like-im-not-into-metal-any-more-toto/" rel="nofollow">http://carolinebeavon.com/2010/03/18/looks-like-im-not-into-metal-any-more-toto/</a></p> <p>I wonder if there is any opportunities now Spotify have started letting users import and sync their iTunes library/playlists - there must be some kind of data transfer going on - maybe it is something you could exploit?</p> <p>I'll be interested to see how your project develops - and good luck with it!</p> <p>Caroline </p> http://forums.flowingdata.com/topic/tracking-music-play-statistics-via-itunes#post-1283 Mon, 16 Nov 2009 16:33:23 +0000 nathany 1283@http://forums.flowingdata.com/ <p>i've thought about this too some. the tough part is getting patterns over time because, like you said, the iTunes XML only gives aggregates.</p> <p>the quick and dirty way i would go about it would be to write a script that parses your iTunes XML each day, and then sends the data over your.flowingdata using the Twitter API. Then you could run the script once a day or whatever.</p> <p>Or maybe you could try something with last.fm?</p> <p>@<a href="http://twitter.com/nairb774" rel="nofollow">nair77b</a> makes use of the last.fm API and then logs listening with YFD:</p> <p><a href="http://your.flowingdata.com/nairb774/page/291/" rel="nofollow">http://your.flowingdata.com/nairb774/page/291/</a> </p> http://forums.flowingdata.com/topic/tracking-music-play-statistics-via-itunes#post-1271 Wed, 11 Nov 2009 04:24:20 +0000 artik 1271@http://forums.flowingdata.com/ <p>I'm looking to analyze the music I listen to over a period of time. Not so much stats on artists, genres, ratings or song-lengths, but more as an exercise to discern a pattern in my listening preferences over time (say beginning of week vs end of week, particular times of the day, music to accompany my daily commute).</p> <p>I did find an article that had a few promising links (<a href="http://www.tunequest.org/a-look-at-itunes-statistics-options/20060904/" rel="nofollow">http://www.tunequest.org/a-look-at-itunes-statistics-options/20060904/</a>). </p> <p>The problem with most of the software linked to in the article was that it did not give me statistics or analysis over time. This could be a problem with the depth of data available in the iTunes XML file, but I'd be willing to sync my iPhone/iPod every day for a month or two, if that's what is needed. </p> <p>I considered using yfd, but I'm concerned that given the amount of time I listen to music at work, it might cause severe disruptions in my work day if I had to tweet every time I make a conscious song/artist/genre choice.</p> <p>Your thoughts? </p>