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Spotify Top 2000 Tracks Audio Features
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About
This dataset features audio characteristics of the top 2000 songs on Spotify from all time. It includes approximately 15 columns that detail various qualities of each track, offering insights into their audio properties and overall context.
Columns
- Index: A unique identifier assigned to each track.
- Title: The name of the specific song.
- Artist: The name of the performing artist.
- Top Genre: The primary genre associated with the track.
- Year: The release year of the song.
- Beats per Minute (BPM): Represents the tempo of the song.
- Energy: An indicator of the song's intensity; higher values denote a more energetic track.
- Danceability: Measures how easy it is to dance to the song; higher values suggest greater danceability.
- Loudness (dB): The overall loudness level of the song; higher values mean a louder track.
- Valence: Reflects the positive mood of the song; higher values indicate a more positive emotional tone.
- Length: The duration of the song.
- Acousticness: Indicates the extent to which the song is acoustic; higher values imply more acoustic elements.
- Speechiness: Measures the amount of spoken words in the song; higher values suggest more spoken content.
- Popularity: Reflects the song's popularity; higher values signify greater popularity.
Distribution
The dataset is available in CSV format, specifically as "Spotify-2000.csv", with a file size of approximately 169.92 kB. It comprises 15 columns and contains 1994 distinct records, representing the featured top songs.
Usage
This dataset is ideal for a variety of analytical tasks related to music and audio features. Potential applications include:
- Analysing the evolution of genre popularity from the 1950s to the 2000s.
- Identifying which genres most frequently feature in the Top 2000s.
- Determining artists who are more likely to produce top-charting songs.
- Investigating trends in average song tempo over different years.
- Exploring historical shifts in the popularity of acoustic songs.
- Understanding how genre preferences have changed over time.
Coverage
The dataset encompasses songs released between 1956 and 2019. It focuses exclusively on the Top 2000 tracks available on Spotify, including contributions from several notable and famous artists. There are no specific geographic or demographic notes regarding data availability.
License
CC0: Public Domain
Who Can Use It
This dataset will be of interest to:
- Music Researchers and Academics: For detailed studies on music evolution, characteristics of popular songs, and genre dynamics.
- Data Scientists and Analysts: To perform statistical analysis, identify correlations between audio features and popularity, and develop predictive models for music trends.
- Application Developers: For creating tools that leverage audio features for music recommendation systems or playlist generation.
- Music Enthusiasts: To explore the attributes of their favourite popular songs and uncover interesting patterns within a large collection of top tracks.
Dataset Name Suggestions
- Spotify Top 2000 Tracks Audio Features
- Global Spotify Hit Songs Dataset
- Historical Spotify Music Trends
- Popular Spotify Tracks Analysis Data
Attributes
Original Data Source: Spotify Top 2000 Tracks Audio Features
QUALITY