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---
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](http://millionsongdataset.com/pages/getting-dataset/#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](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:
```python
from datasets import load_dataset
ds = load_dataset("trojblue/million-song-subset")
```
- Explore and analyze various musical attributes easily.
## License
- **Original License**: Refer to the [Million Song Dataset license](http://millionsongdataset.com/pages/terms-of-use/)
- **Processed Version**: Shared for research and non-commercial purposes.
For more details, visit the [Million Song Dataset website](http://millionsongdataset.com).
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