FlowingData Forums » Statistics and Data

Tracking music-play statistics via iTunes?

Started 2 years ago by artik / 4 posts

  1. artik
    Member
    Posted 2 years ago #

    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).

    I did find an article that had a few promising links (http://www.tunequest.org/a-look-at-itunes-statistics-options/20060904/).

    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.

    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.

    Your thoughts?

  2. nathany
    FlowingData Editor
    Posted 2 years ago #

    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.

    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.

    Or maybe you could try something with last.fm?

    @nair77b makes use of the last.fm API and then logs listening with YFD:

    http://your.flowingdata.com/nairb774/page/291/

  3. carolinebeavon
    Member
    Posted 1 year ago #

    Hey

    This sounds like a great project.

    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).

    In the end I resorted to a "snapshot" of my listening and analyzed the results, and the anomalies it threw up.

    http://carolinebeavon.com/2010/03/18/looks-like-im-not-into-metal-any-more-toto/

    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?

    I'll be interested to see how your project develops - and good luck with it!

    Caroline

  4. JuliaJ
    Member
    Posted 1 year ago #

    Have you seen this? http://www.leebyron.com/what/lastfm/

    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.

    Julia


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