https://dotdandotunderscore.github.io/Music as DataUsing the Spotify API to compare audio features of international Top 50 songs 2023-09-26T10:21:49+01:00 Daniel Woods https://dotdandotunderscore.github.io/ Jekyll © 2023 Daniel Woods /assets/img/favicons/favicon.ico /assets/img/favicons/favicon-96x96.png Aggregating data on Top 50 similarities2023-09-25T15:40:00+01:00 2023-09-26T10:16:43+01:00 https://dotdandotunderscore.github.io/posts/AggregateSharedSongs/ Daniel Woods Simplifying data exposes its value The previous post on this site used the Spotify API to produce a series of plots that contained data on how many songs are shared between the Top 50 playlists officially maintained by Spotify. The 30 plots in total presented an explicit and complete view of that data set, but in a way which was quite difficult to consume, especially on mobile. By instead plot... Extracting cultural groups from pop music2023-09-24T21:28:00+01:00 2023-09-26T10:09:16+01:00 https://dotdandotunderscore.github.io/posts/SharedSongs/ Daniel Woods In a more globalised world, pop music is more general If you spent some time exploring the plot in post about BPM values of international pop songs, you may have noticed that some songs made the Top 50 lists of multiple countries. This observations presents some obvious question: How many songs end up on multiple lists, how often does this happen, and why does this happen? If your national la... Variation in average BPM of pop songs in different countries2023-09-20T20:05:00+01:00 2023-09-25T17:01:24+01:00 https://dotdandotunderscore.github.io/posts/InternationalBPM/ Daniel Woods Music is complicated Comparing pieces of music from a scientific perspective has gained major traction with the popularity of Spotify and its powerful song suggestion algorithm. The Spotify API contains a wide variety of aggregated audio feature endpoints that let us get a glimpse into the data that Spotify’s algorithm uses for suggestions. In the first part of this project the tempo, or bea...