A wrapper for pulling track audio features from the 'Spotify' Web API < http://developer.spotify.com/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 audio features and track/album popularity metrics. You can also pull song and playlist information for a given 'Spotify' user (including yourself!).
spotifyr is a quick and easy wrapper for pulling track audio features 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!).
You'll have to 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
The easiest way to authenticate is to set your credentials to the System Environment variables
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(client_id = Sys.getenv('SPOTIFY_CLIENT_ID'), client_secret = Sys.getenv('SPOTIFY_CLIENT_SECRET'))
beatles <- get_artist_audio_features('the beatles')count(beatles, key_mode, sort = T)#> # A tibble: 22 x 2#> key_mode n#> <chr> <int>#> 1 C major 40#> 2 D major 38#> 3 G major 34#> 4 A major 33#> 5 E major 20#> 6 F major 13#> 7 B minor 9#> 8 C# minor 8#> 9 F# minor 8#> 10 A minor 7#> # ... with 12 more rows
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(10)#> # A tibble: 10 x 2#> track_name valence#> <chr> <dbl>#> 1 These Days 0.949#> 2 Passover - 2007 Remastered Version 0.946#> 3 Colony - 2007 Remastered Version 0.816#> 4 Atrocity Exhibition - 2007 Remastered Version 0.790#> 5 Wilderness 0.779#> 6 Twenty Four Hours 0.764#> 7 A Means To An End - 2007 Remastered Version 0.750#> 8 Interzone - 2007 Remastered Version 0.739#> 9 She's Lost Control - 2007 Remastered Version 0.731#> 10 Disorder - 2007 Remastered Version 0.728
Now if only there was some way to plot joy...
library(ggjoy)#> Loading required package: ggplot2#> Loading required package: ggridges#> The ggjoy package has been deprecated. Please switch over to the#> ggridges package, which provides the same functionality. Porting#> guidelines can be found here:#>ggplot(joy, aes(x = valence, y = album_name)) +geom_joy() +theme_joy() +ggtitle("Joyplot of Joy Division's joy distributions", subtitle = paste0("Based on valence pulled from Spotify's Web API with spotifyr"))#> Picking joint bandwidth of 0.113
This app, powered by spotifyr, allows you to visualize the energy and valence (musical positivity) of all of Spotify's artists and playlists.