This package allows you to connect R to Spotify's API and get information about Songs, Albums, Artists and Users.
This is an experimental package built up with functions that I've created to attend my specific needs (meaning I wasn't really concerned with errors different than ones I got when it was written). Please, use it with caution.
So far I haven't uploaded a stable version to CRAN but you can download from GitHub using devtools, type:
In order to access many of the functions you need an authenticated token. You can get one accessing this link to create a Spotify app and get app_id, client_id and client_secret. (Don't forget to put http://localhost:1410/ in Redirect URIs)
# id name popularity genres type followers# 3z6Gk257P9jNcZbBXJNX5i Regina Spektor 67 anti-folk artist 613837
To get information from an artist using the artist id:
To get information the albums available at spotify from a specific artist:
regina.albums$name#name of the albums#  "Kubo and the Two Strings" #  "What We Saw From The Cheap Seats" #  "What We Saw From The Cheap Seats (Deluxe Version)"#  "Live In London" #  "Far" #  "Far (Deluxe DMD)" #  "Begin To Hope" #  "Begin To Hope (Special Edition)" #  "Begin To Hope (U.S. Version)" #  "Soviet Kitsch (U.S. Version)"
To get the songs from a specific album:
# getting the songs from the album "what we saw from the cheap seats"#from Regina Spektorregina.whatwesaw<-getAlbum("3Etyu2JmgiQTQztLz6RxDX") #"3Etyu2JmgiQTQztLz6RxDX" is theid for the album.
To get the features from a specific song:
# getting the song features from "Don't Leave Me [Ne Me Quitte Pas]" #from the album "what we saw from the cheap seats" from Regina Spektorsong<-getFeatures("0y5HWbAnJ6qrjeBuFL52hO",token=keys) #"0y5HWbAnJ6qrjeBuFL52hO" is the id for the album.
To get the playlists from a specific user:
wh.playlist<- getPlaylist("thewhitehouse",token=keys) #playlist from the White Housewh.playlist#id name ownerid tracks#1 6ujhXmg8SXjdkdCZ2TchTY The Bidens' 2016 Summer Playlist thewhitehouse 15#2 2Zve7PqFSlGl0ojgGnhFTm The President's 2016 Summer Playlist: Day thewhitehouse 17#3 0BczR7bDaoKvn3MGPxS9Lx The President's 2016 Summer Playlist: Night thewhitehouse 18#4 4FDHBIdHPNHCPBqftDc3lk Holidays with the Bidens thewhitehouse 17#5 4qu9a0vwTMyTPpc2YI1GPw Holidays with the Obamas thewhitehouse 14#6 3R2DGCLfGdVqqqN6rdQYr5 The First Lady's Day of the Girl Playlist thewhitehouse 20#7 4RGLH5YuS6ldp7aCKaTWas The President's Summer Playlist: Day thewhitehouse 20#8 3fAriv8eMWELCwbWrhMKy2 The President's Summer Playlist: Night thewhitehouse 20
To get the songs from a specific playlist:
#E.g. getting the songs from "Top 100 tracks currently on Spotify" playlisttopsongs<- getPlaylistSongs("spotify","4hOKQuZbraPDIfaGbM3lKI",token=keys)
To get a dataframe with related artists:
related# sourceID sourceName names popularity followers id#1 3z6Gk257P9jNcZbBXJNX5i Regina Spektor Feist 63 336016 6CWTBjOJK75cTE8Xv8u1kj#2 3z6Gk257P9jNcZbBXJNX5i Regina Spektor Kate Nash 57 158098 5vBKu1igxFo6g1sHADkIdg#3 3z6Gk257P9jNcZbBXJNX5i Regina Spektor Imogen Heap 56 183372 6Xb4ezwoAQC4516kI89nWz#4 3z6Gk257P9jNcZbBXJNX5i Regina Spektor Fiona Apple 59 239789 3g2kUQ6tHLLbmkV7T4GPtL#5 3z6Gk257P9jNcZbBXJNX5i Regina Spektor She & Him 55 234354 3CIRif6ZAedT7kZSPvj2A4#6 3z6Gk257P9jNcZbBXJNX5i Regina Spektor Ingrid Michaelson 68 355511 2vm8GdHyrJh2O2MfbQFYG0#7 3z6Gk257P9jNcZbBXJNX5i Regina Spektor A Fine Frenzy 54 130989 5dTYaRzOn4rXGBLH052EeQ#8 3z6Gk257P9jNcZbBXJNX5i Regina Spektor Anya Marina 44 23523 6xYBLeSMu1AqPsnUzEvx5n#9 3z6Gk257P9jNcZbBXJNX5i Regina Spektor Rachael Yamagata 48 44269 7w0qj2HiAPIeUcoPogvOZ6#10 3z6Gk257P9jNcZbBXJNX5i Regina Spektor Jenny Owen Youngs 44 12299 52mkFCABBeP3KjkWFA4M2H#11 3z6Gk257P9jNcZbBXJNX5i Regina Spektor Yael Naim 57 60798 3cHwmcXlo7XvovQcl5YxlQ#12 3z6Gk257P9jNcZbBXJNX5i Regina Spektor Frou Frou 46 48835 6MUyqmIQ35inLjch0YzIEG#13 3z6Gk257P9jNcZbBXJNX5i Regina Spektor the bird and the bee 53 60498 65XA3lk0aG9XejO8y37jjD#14 3z6Gk257P9jNcZbBXJNX5i Regina Spektor The Pierces 48 51210 1ET1wIkDmuCBC80XcTr3Sg#15 3z6Gk257P9jNcZbBXJNX5i Regina Spektor Tegan and Sara 65 274481 5e1BZulIiYWPRm8yogwUYH#16 3z6Gk257P9jNcZbBXJNX5i Regina Spektor Lenka 57 91001 5g3uG8zZZANGT6YOssgjfC#17 3z6Gk257P9jNcZbBXJNX5i Regina Spektor KT Tunstall 59 99006 5zzrJD2jXrE9dZ1AklRFcL#18 3z6Gk257P9jNcZbBXJNX5i Regina Spektor Rufus Wainwright 57 118372 2PfBzriIMRsCXPDtSy9vg8#19 3z6Gk257P9jNcZbBXJNX5i Regina Spektor Laura Marling 59 181458 7B2edU3Q7btJoNsoHCNohM#20 3z6Gk257P9jNcZbBXJNX5i Regina Spektor Cat Power 61 288064 6G7OerKc3eBO9sVkRNopFC
One nice idea is to create networks of related artists. Eg. This is a network of related artists from the top 100 artists at spotify (Basically all you need to do is use getPlaylistSongs and getRelated to get the data).
Another example is to use getFeatures to extract features and play with that. In this example I use getFeatures and getPlaylistSongs to extract song features from the "What we saw from the cheap seats" from Regina Spektor and the song features from the Top 20 songs at spotify (extracted in august 2016). I assume that Reginas' songs are not very similar to the ones that make a lot of success...This is sad because her songs are awesome =( . Then I use Hierarchical cluster to see if Reginas' songs would stay in a different cluster based on its features.
Apparently it does! 8 out 11 of her songs would be in the same cluster (cluster on the right). From the 3 "misclassified" 2 were singles ("Don't Leave Me [Ne Me Quitte Pas]" and "All the Rowboats"). So it is not strange to see them in a cluster with the top 20 songs.