Some of you may have read my last article where I analyzed 59 sets from EDC Las Vegas 2017. This time, I put on my big boy pants and analyzed 236 sets from both weekends of Tomorrowland in Belgium. This means I had more than 14,000 tracks played by ~200 DJ’s over the course of 2 weekends to feed my analysis. Similar to last time, this data was web scraped from 1001tracklists.com and I have made the code available on my github page if you wish to do something similar yourself. In addition, I also created a summary dashboard on Tableau Public if you wish to explore the data in more detail yourself.
*Note: I have added links to some songs along the way for your enjoyment, so please read on!
1. DJ Snake
DJ Snake had the the most tracks played at Tomorrowland of any DJ by far (65), which was 23 more than the next highest artist (Axwell /\ Ingrosso). In addition, his songs were played by a wide variety of artists (38), far and away the broadest reach of any artist playing at the festival (the next highest was Calvin Harris with 23). The main drivers behind his popularity were his two biggest hits “Propaganda” and “Let Me Love You”, which were the #2 and #5 most played songs overall.
For those who may be interested in a new spin on these (already overplayed) hits, the most popular remixes were the “Propaganda (Nom de Strip & TJR Remix)” and “Let Me Love You (Don Diablo Remix)”.
2. Ed Sheeran
As amazing as it would be to see Ed Sheeran working the turntables and screaming for the crowd to “put their hands up in the air”, sadly he was not. However, he still ended up having his songs played (in one form or another) by 22 different artists at the festival. This puts him at tied for third alongside of Axwell /\ Ingrosso and Valentino Khan. Much like Kendrick Lamar was for EDC, Ed is the most popular artist not appearing in person to have his tracks played (given that they are such similar artists this should come as no surprise *sarcasm*).
“Shape of You” led the way as the most common song played, but if anyone is looking to impress their friends with their Ed Sheeran discology, I would recommend checking out the most popular remix of “Castle on the Hill” by Gareth Emery & Ashley Wallbridge.
3. Hardstyle
While trap music may be slowly taking hold of the Americas, its older cousin hardstyle is alive and well in Europe. By using Python scikit-learn K-Means clustering and my limited knowledge of a few hardstyle artists, I was able to decipher which other artists fell into this genre. For me personally, exploring cluster 12 on the Tableau dashboard led to some entertaining artist (“Phuture Noize“) and song (“Destination“) discoveries. Worth noting: hardstyle is very high energy and is definitely not for everyone.
Note: I plan on writing a post that goes into the clustering in more detail, drawing a few more insights from the data and explaining the methodology.
4. Heads Will Roll (A-Trak Remix)
While mining this data set for new and exciting remixes I ran across this track, which was tied for 2nd as the most commonly played remix at Tomorrowland 2017 (12 plays across 11 DJs). Personally, I found this incredibly amusing since it was released 8 years ago (2009, if you cannot find your calculator). Therefore, this track is a winner for its popularity and longevity at a festival well known for revealing tracks never heard before.
It is also be worth noting that Don Diablo Remixes were incredibly popular (as can be seen on the left).
What is Next?
As I alluded to before, I tested out whether I could use python to cluster various DJs based upon the the tracks and artists they played. I plan on providing a more detailed analysis of this output soon.
Spoiler Alert: The clusters are on the Tableau Dashboard already… if you agree/disagree, leave a comment!