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spotifyr is an R wrapper for pulling track audio features and other information from Spotify’s Web API in bulk. By automatically batching API requests, it allows you to enter an artist’s name and retrieve their entire discography in seconds, along with Spotify’s audio features and track/album popularity metrics. You can also pull song and playlist information for a given Spotify User (including yourself!).


CRAN version 2.1.0 (recommended)


Development version



First, set up a Dev account with Spotify to access their Web API here. This will give you your Client ID and Client Secret. Once you have those, you can pull your access token into R with get_spotify_access_token().

The easiest way to authenticate is to set your credentials to the System Environment variables SPOTIFY_CLIENT_ID and SPOTIFY_CLIENT_SECRET. The default arguments to get_spotify_access_token() (and all other functions in this package) will refer to those. Alternatively, you can set them manually and make sure to explicitly refer to your access token in each subsequent function call.

Sys.setenv(SPOTIFY_CLIENT_ID = 'xxxxxxxxxxxxxxxxxxxxx')
Sys.setenv(SPOTIFY_CLIENT_SECRET = 'xxxxxxxxxxxxxxxxxxxxx')

access_token <- get_spotify_access_token()

Authorization code flow

For certain functions and applications, you’ll need to log in as a Spotify user. To do this, your Spotify Developer application needs to have a callback url. You can set this to whatever you want that will work with your application, but a good default option is http://localhost:1410/ (see image below). For more information on authorization, visit the offical Spotify Developer Guide.


What was The Beatles’ favorite key?

beatles <- get_artist_audio_features('the beatles')

beatles %>% 
    count(key_mode, sort = TRUE) %>% 
    head(5) %>% 
D major24
G major21
A major13
F major12
C major11

Get your most recently played tracks


get_my_recently_played(limit = 5) %>% 
    mutate(artist.name = map_chr(track.artists, function(x) x$name[1]),
           played_at = as_datetime(played_at)) %>% 
    select(track.name, artist.name, track.album.name, played_at) %>% 
Hardened Chord - Regis RemixStaveAfter the Social2019-07-12 19:04:29
CellsBlenkShelter2019-07-12 18:57:59
Suspension Of Consciousness - Original mixFlaminiaTHEOTHERSIDE 012019-07-12 18:52:32
KeralaBonoboMigration2019-07-12 18:46:58
LinkedBonoboLinked2019-07-12 18:45:31

Find your all time favorite artists

get_my_top_artists_or_tracks(type = 'artists', time_range = 'long_term', limit = 5) %>% 
    select(name, genres) %>% 
    rowwise %>% 
    mutate(genres = paste(genres, collapse = ', ')) %>% 
    ungroup %>% 
Radioheadalternative rock, art rock, melancholia, modern rock, oxford indie, permanent wave, rock
Flying Lotusalternative hip hop, escape room, experimental hip hop, glitch, glitch hop, hip hop, indietronica, intelligent dance music, jazztronica, wonky
Onraalternative hip hop, chillhop, trip hop, wonky
Teebsabstract beats, bass music, chillwave, wonky
Pixiesalternative rock, boston rock, garage rock, indie rock, modern rock, new wave, noise pop, permanent wave, rock

Find your favorite tracks at the moment

get_my_top_artists_or_tracks(type = 'tracks', time_range = 'short_term', limit = 5) %>% 
    mutate(artist.name = map_chr(artists, function(x) x$name[1])) %>% 
    select(name, artist.name, album.name) %>% 
Impossible KnotsThom YorkeANIMA
I Am a Very Rude PersonThom YorkeANIMA
TrafficThom YorkeANIMA
Not The NewsThom YorkeANIMA
RunwayawayThom YorkeANIMA

What’s the most joyful Joy Division song?

My favorite audio feature has to be “valence,” a measure of musical positivity.

joy <- get_artist_audio_features('joy division')
joy %>% 
    arrange(-valence) %>% 
    select(track_name, valence) %>% 
    head(5) %>% 
Passover - 2007 Remaster0.941
Colony - 2007 Remaster0.808
Atrocity Exhibition - 2007 Remaster0.787
A Means to an End - 2007 Remaster0.752
Interzone - 2007 Remaster0.746

Now if only there was some way to plot joy…

Joyplot of the emotional rollercoasters that are Joy Division’s albums


ggplot(joy, aes(x = valence, y = album_name)) + 
    geom_joy() + 
    theme_joy() +
    ggtitle("Joyplot of Joy Division's joy distributions", subtitle = "Based on valence pulled from Spotify's Web API with spotifyr")

Sentify: A Shiny app

This app, powered by spotifyr, allows you to visualize the energy and valence (musical positivity) of all of Spotify’s artists and playlists.

Dope stuff other people have done with spotifyr

The coolest thing about making this package has definitely been seeing all the awesome stuff other people have done with it. Here are a few examples:

Exploring the Spotify API with R: A tutorial for beginners, by a beginner, Mia Smith

Sentiment analysis of musical taste: a cross-European comparison, Paul Elvers

Blue Christmas: A data-driven search for the most depressing Christmas song, Caitlin Hudon

KendRick LamaR, David K. Laing

Vilken är Kents mest deprimerande låt? (What is Kent’s most depressing song?), Filip Wästberg

Чёрное зеркало Arcade Fire (Black Mirror Arcade Fire), TheSociety

Sente-se triste quando ouve “Amar pelos dois”? Não é o único (Do you feel sad when you hear “Love for both?” You’re not alone), Rui Barros, Rádio Renascença

Using Data to Find the Angriest Death Grips Song, Evan Oppenheimer

Hierarchical clustering of David Bowie records, Alyssa Goldberg

tayloR, Simran Vatsa

Long Distance Calling: Data Science meets Post-Rock…, Sebastian Kuhn

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Last Published

January 1st, 1970

Functions in spotifyr (2.1.1)