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Spotify Audio Features Dataset
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About
This dataset offers detailed information on all tracks featured in the Spotify Top 200 charts since 2016. It includes vital metrics such as the number of streams and weeks spent on the charts, alongside a rich collection of audio features. These features encompass characteristics like tempo, key, danceability, energy, and vocal presence, providing a deep insight into popular music characteristics and trends. The data originates from Spotify Top Songs Charts and the Spotify Web API.
Columns
- id: The unique Spotify ID for each track.
- artist_names: The name(s) of the artist(s) performing the track.
- track_name: The title of the song.
- source: The name of the record label associated with the track.
- key: The musical key the track is in (e.g., C, C#/Db).
- mode: Indicates whether the track is in a major or minor modality.
- time_signature: An estimated time signature, ranging from 3 to 7 beats per bar.
- danceability: A measure from 0.0 to 1.0 indicating how suitable a track is for dancing, based on tempo, rhythm stability, and beat strength.
- energy: A measure from 0.0 to 1.0 representing the perceptual intensity and activity of the track.
- speechiness: Detects the presence of spoken words; values closer to 1.0 indicate more speech-like content.
- acousticness: A confidence measure from 0.0 to 1.0 on whether the track is acoustic.
- instrumentalness: Predicts whether a track contains no vocals, with values closer to 1.0 indicating a higher likelihood of being instrumental.
- liveness: Detects the presence of an audience; higher values suggest an increased probability of a live performance.
- valence: A measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track (e.g., happy, sad).
- loudness: The overall loudness of a track in decibels (dB), typically ranging from -60 to 0 dB.
- tempo: The overall estimated tempo of a track in beats per minute (BPM).
- duration_ms: The duration of the track in milliseconds.
- weeks_on_chart: The number of weeks the track has appeared in the Spotify Top 200 charts.
- streams: The total number of streams the track accumulated during its period in the charts.
Distribution
The dataset is provided in CSV format and has a file size of 1.14 MB. It contains 19 columns and 6,513 unique records or rows, with all data points being valid.
Usage
This dataset is ideal for a variety of applications and use cases, including:
- Analysing global music trends and the evolution of popular music over time.
- Developing predictive models for song popularity and chart performance.
- Understanding the correlation between audio features and commercial success in the music industry.
- Building advanced music recommendation systems and discovery tools.
- Conducting academic research in musicology, digital humanities, and audio characteristics.
Coverage
The dataset's time range extends from 2016 onwards, covering all songs that appeared in the Spotify Top 200 charts since that year. The scope primarily focuses on tracks from these globally recognised charts.
License
CC BY-NC-SA 4.0
Who Can Use It
- Music Analysts and Researchers: To explore patterns in popular music and understand the characteristics that drive chart success.
- Data Scientists and Machine Learning Engineers: For training models to predict song popularity, classify genres based on audio features, or generate music recommendations.
- Music Industry Professionals: Including A&R representatives, marketing strategists, and business intelligence analysts, to gain insights into market trends and artist performance.
- Developers: To integrate music trend data and audio feature analysis into applications, platforms, or visualisations.
Dataset Name Suggestions
- Spotify Chart Tracks & Audio Features
- Global Music Popularity Trends
- Spotify Top Songs Analysis
- Chart-Topping Music Metrics
- Spotify Audio Features Dataset
Attributes
Original Data Source: Spotify Audio Features Dataset
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