Music and Skateboarding

by Jared Wilber · October 2017

Note - if you're on mobile the visualization won't properly line up with text - sorry!


I grew up in San Diego, California, and, like many other kids from Southern California, skateboarding was a huge part of my childhood. One of the biggest draws to skateboarding for me was the music associated with it. It seemed different than what they played on the radio. It felt counterculture. It felt cool.

Of course, I was in no way unique with this sentiment - skateboarding and music have been intrinsically linked since the inception of skateboarding in the 1950s and 1960s, with many artists (e.g. Morrissey, Black Flag, Dinosaur Jr. etc.) heavily associated with skate culture.

And therein lives the purpose of this blog post:

Which music artists and genres are featured the most in skateboarding videos?

In the visualization below, each node corresponds to a separate artist, with size encoding the number of times that artist has been used in skate videos. The larger the area of circle, the more popular is the artist in skateboarding. Each node is color-coded by music genre. The toggle options allow you to arrange the data by various levels.

This piece is exploratory: hover over each node to get artist specific information, and feel free to drag them around (it's pretty fun).


Artists By Genre By Popularity

A Closer Look At Genres

Below we view the distribution of music genres across all collected skate videos.
At 20%, indie music is the most popular genre. This is pretty expected. However, that Classic Rock is used more than hip hop and punk, two genres typically associated with skateboarding, is quite surprising. Spearheading this genre's dominance are The Beatles, Bowie, and The Rolling Stones. Hip Hop and Punk follow with values at 15% and 14%, respectively. The remaining genres are used less frequently, which, in my opinion, is a result of them being associated with specific skating aesthetics.


Data and Methodology

The data was scraped from skatevideosite.com. I wrote a quick Python script to grab the soundtracks for the top 2,000 most-viewed skate videos. To maintain data integrity, I manually removed niche, unknown videos that aren't a part of popular skate culture (e.g., random skate videos from South America). Genres were obtained via the Spotify API. After this step, the data cleaning, preprocessing, and plot prototypes were created using R.

To produce the final visualizations, I used Javascript's amazing D3 libary. The bubble chart was created via library's force-directed graph layout (without utilizing edges), and the plots were styled the nodes using CSS. The visualizations were inspired by work from the New York Times and Jim Vallandingham.

All code is available in the associated GitHub repository.