An interactive visualization of tracks from the most popular jazz artists from 1935–2020 using d3.js.
- compare song features of jazz artists in six different categories (e.g. I can see that the songs by artist x tend to be more uptempo than the average popular jazz song);
- Analyze the most popular jazz artists’ productivity by viewing their released songs over the years; see the number of jazz songs released over the years;
- explore jazz songs in a timeline, and compare their selected audio features; listen to a preview of the tracks;
- explore the temporal context of jazz songs (which tracks were released at this time); discover new jazz tracks from a specific time range.
| Dataset | |
|---|---|
| Title | Spotify Dataset 1921-2020, 600k+ Tracks |
| Subtitle | Audio features of 600k+ tracks, popularity metrics of 1M+ artists |
| Source | Spotify Web API |
| Creator | Yamac Eren Ay |
| Release Date | April 2021 (latest version) |
| Link | https://www.kaggle.com/yamaerenay/spotify-dataset-19212020-600k-tracks |
This project was developed as an assignment for the lecture Information Visualisation (MDM / FCTUC).
Students
- Alexandra Oliveira
- Jasper Blum
Supervisors
- Catarina Sofia Henriques Maçãs
- Evgheni Polisciuc
Created with ❤ at the DEI - University of Coimbra