Interesting music statistics


Via Twitter I found an interesting tweet stating some statistics on music that this person played over the last week. A twitter integration allows you to display this information, that is collected via last.fm. I don’t know why, but I was always a bit sceptic, when it came to last.fm, which is why I never used it, but this statistics got me interested.

I know that iTunes (which is the tool I use to listen to music since I got that iPhone 3G – you are somehow forced to use iTunes when you have an iPhone…) collects a lot of statistic information (which song is played how often, when was it played last, etc.) and saves it into the iTunes library files, which is actually just available as a simple XML file. So, there must be a way to get some information out there for statistic purposes now, mustn’t there?

I googled a bit, and found two very interesting tools. The first one, Super Analyzer by Nosleep Software, is a tool written in Java, so it should work on nearly any platform (if it has a Java Virtual Machine, that is) – it allows some highly sophisticated analysis on different aspects, e.g. your tracks, your albums, your artists, your genres and your decades (i.e. the year of your tracks). Each of these groups have different analysis available and also graphical outputs. You can even export them to a HTML file and integrate them to your website.

The second tool is called iTunes Statistician (developers site is down). It’s quite easy, and unfortunately just for Mac OS X. All it does is to extract your Top 100 artists, albums, songs and genres. There’s a function to export them, but only to text file. And that’s all it does. Still, it does a good job and you get quite some interesting results (at least I consider them interesting).


So if you are interested, here are my results. Basis is my new iTunes library which I built on March 16th, while reorganizing all my music.
I’ll think I’ll update this regularly to see how my music taste variates. I think a quarterly view would be interesting, don’t you think?

So, here we go:

Some general Information

  • Track Count: 9,121 total tracks
  • Play Count: 3,858 tracks played
  • Total Time: 6,4 weeks of music
  • Total Play Time: 2,5 weeks playing
  • Artist Count: 583 total artists
  • Album Count: 635 different albums
  • Genre Count: 92 genres
  • Average Play Count: 0,4 plays per song
  • Songs Played per Day: 9,9
  • Most Songs Played At: 12:00 pm
  • Average Track Length: 7,18 minutes
  • Album Completeness: 30% complete
  • Complete Albums: 54% are complete
  • Average Bit Rate: 184,5 kbps

My Top 10 Artists

  1. ASP – 490
  2. Emilie Autumn – 286
  3. HIM – 283
  4. Staubkind – 226
  5. Linkin Park – 111
  6. Sally Shapiro – 100
  7. 2Pac – 93
  8. Evanescence – 72
  9. Nelly Furtado – 61
  10. Vanessa Carlton – 59

My Top 10 Albums

  1. Zu Weit (Staubkind) – 198
  2. Opheliac – The Deluxe Edition (Emilie Autumn) – 116
  3. Enchant (Emilie Autumn) – 102
  4. My Guilty Pleasure (Sally Shapiro) – 100
  5. Venus Doom (Limited Edition) (HIM) – 83
  6. Hybrid Theory (Linkin Park) – 81
  7. Werben (Limited Special Edition) (ASP) – 78
  8. Requiembryo (Der Schwarze Schmetterling V) (ASP) – 74
  9. Hast Du Mich Vermisst? (Der Schwarze Schmetterling I) (ASP) – 64
  10. Wer Sonst? (Limited Edition) (ASP) – 60

My Top 10 Songs

  1. Vergiss Nicht (Staubkind) – 31
  2. Juliet (Emilie Autumn) – 30
  3. Possession (ASP) – 29
  4. Zu Weit (Staubkind) – 25
  5. Miracle (Sally Shapiro) – 24
  6. Get Some Sleep (Exclusive Version) (Mono Inc.) – 22
  7. Intro (Staubkind) – 22
  8. Königin (Staubkind) – 21
  9. Looking At The Stars (Sally Shapiro) – 20
  10. Im Märchenland (Single Edit) (Asp) – 20

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