tunequest

A rambling, self-indulgent, inconsequential post about habits, statistics, speculations, accumulation and missing data. :: I can't help but be disappointed that I can't see lifetime stats for my music listening habits. In these days of play count-tracking programs and websites like iTunes and Last.fm, it's easy to get caught up in the musical trends of your life. It's especially interesting when you look at the numbers and discover that you perhaps ...

Read the rest of this post.

I spent part of the past weekend doing some basic statistical analysis of my iTunes Library. I've been collecting music for 16ish years now, so I decided to see what kind of historical trends I could find. One task I assigned myself was to look at the variety of the time span of the releases in my collection. Now I don't have to do any fancy calculations to tell ...

Read the rest of this post.

My original High Impact formula had a fundamental flaw, which I think I may have fixed. I spent the last post talking about the albums that made the biggest "impact" on me during 2007, but what exactly does that mean? Over the summer, I came up with the general concept, which basically defined impact as the average number of times any particular song from an album or artist in my ...

Read the rest of this post.

I've spent the past couple days playing around with Alex King's iTunes Stats program. It's written in PHP/MYSQL and requires a web server to run. With the MAMP one-click server running on my PowerBook, I had little trouble installing the program (though I did have to substantially increase the PHP timeout setting so it could handle my large library). iTunes Stats reads XML files, one can load an entire iTunes ...

Read the rest of this post.

The vast array of listening information available at Last.fm probably had a great deal to do with CBS's decision to purchase the company. Though I'm wary of the deal, I've not lost all hope for the site. The Audioscrobbler technology behind it is some pretty fascinating stuff and the data it collects is open and available be analyzed, interpreted, shared and displayed in a lot of diverse applications. Hopefully, ...

Read the rest of this post.

When it comes to my iTunes library, I'm a regular statistics nut. Sure, my library exists primarily for my own enjoyment, but it contains so much organically-compiled data about my habits and tastes that I can't help but want to take a look at it and find out what the data says about my interests. But for a while now, I've struggled to quantify, tabulate and analyze the overall sense ...

Read the rest of this post.

The ultimate in iTunes statistics and library analysis is once again live and on faster/better hardware. Yes, my music-listening friends, the iTunesRegistry is back and better than ever. Faster processing, more graphs, interesting facts. The works. It's open source to boot. The site runs on PHP+MYSQL and now you too can grab the code, muck with it and enhance it on your own. Mac users can probably run it locally using ...

Read the rest of this post.

Anyone who has been reading the tunequest for a while knows that statistics, numbers, figures and graphs have played a large part in its progress. In fact, it was the discovery that 10% of my songs were responsible for 49% of my total play counts that prompted me to set out on this endeavor in the first place. To this day, I'm still surprised by the lack of sophisticated options ...

Read the rest of this post.

According to Super Analyser for iTunes, the most common word in the song titles of my library is "love." Unfortunately, the program doesn't tell how it generates that number. Does it include variations like "lovely," "loves" and "lover"? Probably not. It's probably a straight-up word-pattern match. Still, that result surprises me. Certainly it filters out "a," "an," "the," "that," etc, but I would have expected some kind of standard nomenclature to ...

Read the rest of this post.