Beat Trends

About This App

How did you build this? Where did you get your data from? The data for this graph was not freely available, so my first step was to code a custom web scraper with Python and Selenium. This scraper crawled a site with historical rankings of the Beatport, capturing all the tracks on the Beatport Top 100 on the first of each month over a decade-long span. After collecting the data in a CSV, I used Pandas to clean it up and organize it into JSONs. Finally, to build the app I combined React and the powerful graph library D3.js to design the UI and visualize the data.

What is the Beatport Top 100? Beatport is a website where dance music DJs can download new music. The most downloaded songs are ranked on their "Top 100" list, which is basically the Billboard Hot 100 of dance music. While it's by no means representative of the entire electronic music scene, it is a solid baseline for understanding the overall popularity of different genres over time.

Beatport's genre classifications are inaccurate: I agree that they are not always perfect. Their recent division of techno into "Raw / Deep / Hypnotic" and "Peak-Time" is so laughably bad I condensed everything to just "Techno" for this graph. But overall, I find their labels to be pretty accurate, and I tend to take way more issue with genre gatekeepers who love nothing more than condescendingly explaning why a track is not "real" techno.

Is the data weighted in any way? Tracks were not given any preference for having a higher rank, and tracks were still counted if they were on the chart for multiple months.

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