This dataset contains information on 6,000 tracks from Spotify, categorized by one of six genres. It includes various audio features, metadata about the tracks, and an indicator of popularity. The dataset is useful for analysis of music trends, popularity prediction, and genre-specific characteristics.
Format
A data frame with 6,000 rows and 21 columns:
- track_id
character. Spotify ID for the track. See: https://developer.spotify.com/documentation/web-api/- artists
character. Names of the artists associated with the track.- album_name
character. Name of the album on which the track appears.- track_name
character. Name of the track.- popularity
numeric. Popularity score of the track (0-100). See: https://developer.spotify.com/documentation/web-api/reference/#/operations/get-track- duration_ms
numeric. Duration of the track in milliseconds.- explicit
logical. Whether the track has explicit content.- danceability
numeric. Danceability score of the track (0-1). See: https://developer.spotify.com/documentation/web-api/reference/#/operations/get-audio-features- energy
numeric. Energy score of the track (0-1).- key
numeric. The key the track is in (0-11 where 0 = C, 1 = C#/Db, etc.).- loudness
numeric. The loudness of the track in decibels (dB).- mode
numeric. Modality of the track (0 = minor, 1 = major).- speechiness
numeric. Speechiness score of the track (0-1).- acousticness
numeric. Acousticness score of the track (0-1).- instrumentalness
numeric. Instrumentalness score of the track (0-1).- liveness
numeric. Liveness score of the track (0-1).- valence
numeric. Valence score of the track (0-1), indicating the musical positiveness.- tempo
numeric. Tempo of the track in beats per minute (BPM).- time_signature
numeric. Time signature of the track (typically 3, 4, or 5).- track_genre
character. Genre of the track (country, deep-house, dubstep, hip-hop, metal, and rock).- popular_or_not
character. Indicates whether the track is considered popular ("popular") or not ("not popular"). Popularity is defined as a score of 50 or higher which corresponds to the 75th percentile of thepopularitycolumn.
Examples
data(spotify_by_genre)
head(spotify_by_genre)
#> # A tibble: 6 × 21
#> track_id artists album_name track_name popularity duration_ms explicit
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <lgl>
#> 1 2wrJq5XKLnmhRXH… Dan + … 10,000 Ho… 10,000 Ho… 78 167693 FALSE
#> 2 6AHJTA1BN7ePfCh… Luke B… Country U… Country On 0 236455 FALSE
#> 3 5eUtyONoPyfZYGr… Thomas… Mientras … Die A Hap… 1 228320 FALSE
#> 4 1e3QZ42GsP8cTy5… Zach B… New Count… Something… 3 228013 FALSE
#> 5 5Vnx0s7H73V3l6q… Zach B… Easy Coun… Something… 4 228013 FALSE
#> 6 0aEPP6wdKf2uBYE… Zach B… Relaxing … Something… 4 228013 FALSE
#> # ℹ 14 more variables: danceability <dbl>, energy <dbl>, key <dbl>,
#> # loudness <dbl>, mode <dbl>, speechiness <dbl>, acousticness <dbl>,
#> # instrumentalness <dbl>, liveness <dbl>, valence <dbl>, tempo <dbl>,
#> # time_signature <dbl>, track_genre <chr>, popular_or_not <chr>