Spotify Data

The Music Atlas is based entirely off of Spotify data . Three separate, but related, sets of data were collected. The first set of data collected information about Spotify curated playlists, the second set gathered artist-level data, and the third set collected a wider range of playlist data by removing the Curated by Spotify constraint. All data was collected and accessed through Spotify's public API between March 20th and April 14th. To use Spotify's API, you will need an access token, which can be acquired by creating a Spotify Developer Account . The data I collected is available here: Spotify Data for the Music Atlas (under construction).

"License to Developer. Subject to and conditional upon your compliance at all times with these Developer Terms, particularly the limitations in Section IV below, Spotify grants to you a limited, non-exclusive, non-transferable, non-sublicensable, revocable right during the Term (as defined in Section IX.10)...". For non-streaming SDAs (e.g., Music Atlas) Spotify Grants permission to develop and distribute Non-Streaming SDAs that comply with the Branding Guidelines for use with the Spotify Service.".

Overview of the data:

Total Combined Rows:  ~2.5mil Data is updated: Daily

# Dataset Description size (# rows) Relevant Columns Relevant Visualization(s)
1 Genre Dataset Track-level metadata from popular Spotify Curated Genre Playlists ~822k track_id, album_id, artist_id, track_audio_features, genre Genre Map Playlist Relationship Map
2 Playlist Dataset Track-level metadata from popular playlists on Spotify. Note, this is not the same as the Genre Dataset because we aren't requiring the playlist to be a Spotify Curated Playlist. ~1.67mil playlist_id, track_id, artist_id, track_audio_features Genre Map Playlist Relationship Map
3 Artist Dataset Track and Album-level metadata for a small set of hand picked artists. ~1k artist_id, track_id, album_id, track_audio_features, release_date Artist Sound Progression Map

Acknowledgments

I am grateful to Chris Olah and the rest of the Distill Pub team for there insightful blog posts. Also, a big thank you to Sophie Engle for formally introducing me to data visualization.

Contributions

Work was complete by Kai unless noted otherwise.

Concepts & Writting: Kai introduced and wrote the central concept and structure of this article.

Figures & Code: Some figures were drafted in RawGraphs. For all figures, the final version was implemented in D3. All code was written by Kai.

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