Metrics and audio features
Dataset Description
Context
The Cure is one of my favourites groups, that's why I decided to analyze their discography.
Content
Popularity and audio features for every song and album:
-
track_popularity. The value will be between 0 and 100, with 100 being the most popular. -
duration_ms. The duration of the track in milliseconds. -
valence. A measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track. -
danceability. Danceability describes how suitable a track is for dancing based on a combination of musical elements including tempo, rhythm stability, beat strength, and overall regularity.A value of 0.0 is least danceable and 1.0 is most danceable. -
energy. Represents a perceptual measure of intensity and activity (from 0.0 to 1.0). -
acousticness. A confidence measure from 0.0 to 1.0 of whether the track is acoustic. -
loudness. The overall loudness of a track in decibels (typical range between -60 and 0 db). -
speechiness. Speechiness detects the presence of spoken words in a track. The more exclusively speech-like the recording, the closer to 1.0 the attribute value. -
instrumentalness. Predicts whether a track contains no vocals.The closer the instrumentalness value is to 1.0, the greater likelihood the track contains no vocal content. -
liveness. Detects the presence of an audience in the recording. A value above 0.8 provides strong likelihood that the track is live. -
key_mode. The key the track is in.
If you want more information about the metrics, please check here
Acknowledgements
I used the function get_artist_audio_features() from the spotifyr package, in order to retrieve the popularity and audio features for every song and album for a given artist on Spotify.
If you want more information about this package, please check here.
Inspiration
- Exploratory Data Analysis
- Data Visualization
Related Datasets
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Oasis Discography
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