Electronic Music Audio Features from Beatport Top 100 Songs, November 2018

November 2018 top 100 songs from over 20 electronic music subgenres on Beatport. The dataset contains audio features extracted from two-minute samples of each song using the pyAudioAnalysis library. It was used in a publication on automatic subgenre classification in electronic dance music.

Use Cases

• Train a music genre classifier based on audio features extracted from song samples.
• Analyze the acoustic characteristics that differentiate electronic music subgenres.
• Study trends and evolution in electronic dance music by comparing features across genres.
• Benchmark audio feature extraction and analysis pipelines using a curated music dataset.

Strengths

• Contains 100 songs for each of over 20 electronic music subgenres, providing genre-specific coverage.
• Audio features were extracted using a specific, documented library (pyAudioAnalysis).
• Data is associated with a published research paper on automatic subgenre classification.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

Beatport electronic music website.

Collection Method

Audio features extracted from two random minutes of each song file using pyAudioAnalysis.

Time Range

November 2018