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metadata
dataset_info:
  features:
    - name: analysis_sample_rate
      dtype: int32
    - name: artist_7digitalid
      dtype: int32
    - name: artist_familiarity
      dtype: float64
    - name: artist_hotttnesss
      dtype: float64
    - name: artist_id
      dtype: string
    - name: artist_latitude
      dtype: float64
    - name: artist_location
      dtype: string
    - name: artist_longitude
      dtype: float64
    - name: artist_mbid
      dtype: string
    - name: artist_mbtags
      sequence: binary
    - name: artist_mbtags_count
      sequence: int64
    - name: artist_name
      dtype: string
    - name: artist_playmeid
      dtype: int32
    - name: artist_terms
      sequence: binary
    - name: artist_terms_freq
      sequence: float64
    - name: artist_terms_weight
      sequence: float64
    - name: audio_md5
      dtype: string
    - name: bars_confidence
      sequence: float64
    - name: bars_start
      sequence: float64
    - name: beats_confidence
      sequence: float64
    - name: beats_start
      sequence: float64
    - name: danceability
      dtype: float64
    - name: duration
      dtype: float64
    - name: end_of_fade_in
      dtype: float64
    - name: energy
      dtype: float64
    - name: key
      dtype: int32
    - name: key_confidence
      dtype: float64
    - name: loudness
      dtype: float64
    - name: mode
      dtype: int32
    - name: mode_confidence
      dtype: float64
    - name: num_songs
      dtype: int64
    - name: release
      dtype: string
    - name: release_7digitalid
      dtype: int32
    - name: sections_confidence
      sequence: float64
    - name: sections_start
      sequence: float64
    - name: segments_confidence
      sequence: float64
    - name: segments_loudness_max
      sequence: float64
    - name: segments_loudness_max_time
      sequence: float64
    - name: segments_loudness_start
      sequence: float64
    - name: segments_pitches
      sequence:
        sequence: float64
    - name: segments_start
      sequence: float64
    - name: segments_timbre
      sequence:
        sequence: float64
    - name: similar_artists
      sequence: binary
    - name: song_hotttnesss
      dtype: float64
    - name: song_id
      dtype: string
    - name: start_of_fade_out
      dtype: float64
    - name: tatums_confidence
      sequence: float64
    - name: tatums_start
      sequence: float64
    - name: tempo
      dtype: float64
    - name: time_signature
      dtype: int32
    - name: time_signature_confidence
      dtype: float64
    - name: title
      dtype: string
    - name: track_7digitalid
      dtype: int32
    - name: track_id
      dtype: string
    - name: year
      dtype: int32
  splits:
    - name: train
      num_bytes: 2365768621
      num_examples: 10000
  download_size: 1041881893
  dataset_size: 2365768621
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

Million Song Subset (Processed Version)

Overview

This dataset is a structured extraction of the Million Song Subset, derived from HDF5 files into a tabular format for easier accessibility and analysis.

Source

  • Original dataset: Million Song Dataset (LabROSA, Columbia University & The Echo Nest)
  • Subset used: Million Song Subset (10,000 songs)
  • URL: http://millionsongdataset.com

Processing Steps

  1. Extraction: Used hdf5_getters.py to retrieve all available fields.
  2. Parallel Processing: Optimized extraction with ProcessPoolExecutor for speed.
  3. Conversion: Structured into a Pandas DataFrame.
  4. Storage: Saved as a Parquet file for efficient usage.

Format

  • Columns: Contains all available attributes from the original dataset, including artist metadata, song features, and audio analysis.
  • File Format: Parquet (optimized for efficient querying & storage).

Usage

  • Load the dataset with Datasets:
    from datasets import load_dataset  
    ds = load_dataset("trojblue/million-song-subset")
    
  • Explore and analyze various musical attributes easily.

License

For more details, visit the Million Song Dataset website.