A sub-sample of the Spotify song data originally collected by Kaylin Pavlik (kaylinquest) and distributed through the R for Data Science TidyTuesday project.

spotify

Format

A data frame with 350 songs (or tracks) and 23 variables:

track_id

unique song identifier

title

song name

artist

song artist

popularity

song popularity from 0 (low) to 100 (high)

album_id

id of the album on which the song appears

album_name

name of the album on which the song appears

album_release_date

when the album was released

playlist_name

Spotify playlist on which the song appears

playlist_id

unique playlist identifier

genre

genre of the playlist

subgenre

subgenre of the playlist

danceability

a score from 0 (not danceable) to 100 (danceable) based on features such as tempo, rhythm, etc.

energy

a score from 0 (low energy) to 100 (high energy) based on features such as loudness, timbre, entropy, etc.

key

song key

loudness

song loudness (dB)

mode

0 (minor key) or 1 (major key)

speechiness

a score from 0 (non-speechy tracks) to 100 (speechy tracks)

acousticness

a score from 0 (not acoustic) to 100 (very acoustic)

instrumentalness

a score from 0 (not instrumental) to 100 (very instrumental)

liveness

a score from 0 (no live audience presence on the song) to 100 (strong live audience presence on the song)

valence

a score from 0 (the song is more negative, sad, angry) to 100 (the song is more positive, happy, euphoric)

tempo

song tempo (beats per minute)

duration_ms

song duration (ms)