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Spotify Public Playlists (November 2025)

This repository contains an open dataset with 91,906 Spotify playlists. Each row represents a playlist and includes high-level metadata (name, owner, follower count), cover image URLs, JSON payloads with the full Spotify response, and various bookkeeping columns (status, popularity histograms, history, etc.). The release ships as a ready-to-use CSV (playlists.csv, ~9 GB) plus a small preview file for browsing.

Files

Path Description
playlists.csv Final 91,906-row CSV (17 columns, ~9 GB) with one playlist per row.
playlists_preview.csv 200-row slice (64 MB) for quick inspection / Hugging Face preview.
LICENSE CC BY 4.0 license text covering this dataset.

Schema

Column Type Notes
id integer Autoincrement primary key from the source database.
playlist_id string Spotify playlist ID.
name string Playlist display name.
description string Spotify-provided description (HTML/emoji possible).
followers_count integer Followers when the snapshot was taken.
owner_id string Spotify user ID of the owner.
owner_name string Display name of the owner.
is_public boolean Whether the playlist was publicly visible.
tracks_total integer Number of tracks reported by Spotify.
snapshot_id string Snapshot token returned by Spotify for change tracking.
image_url string Primary cover image URL.
raw_data JSON (string) Full Spotify playlist payload as JSON (can exceed 1 MB).
created_at timestamp When this playlist was inserted into the source DB.
updated_at timestamp Last time the playlist row was updated.
followers_history JSON (string) Historical follower counts (if tracked).
status string ETL status flag from the upstream system.
popularity_distribution JSON (string) Histogram of track popularity buckets.

Loading the Dataset

Once the CSV is available (locally or via Hugging Face), you can load it with your favorite data tooling. For quick experiments or to power the Hugging Face table preview, use playlists_preview.csv (200 rows). When you need the full corpus, switch to playlists.csv:

import pandas as pd

df = pd.read_csv(
    "playlists.csv",
    dtype={"playlist_id": str, "owner_id": str},
    converters={"raw_data": lambda x: x},  # keep JSON as raw strings
)
print(len(df))  # 91906

For streaming workflows (due to the 9 GB size), consider pyarrow.dataset or chunked pandas.read_csv(..., chunksize=10_000).

Publishing to Hugging Face

  1. Create dataset repo: huggingface-cli repo create <namespace>/spotify-playlists-2025 --type dataset.
  2. Clone with Git LFS: GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/datasets/<namespace>/spotify-playlists-2025 then cd into it and run git lfs install.
  3. Copy assets: Bring over playlists.csv, playlists_preview.csv, README.md, and LICENSE (track the large CSVs with Git LFS).
  4. Track large files: git lfs track "*.csv" "*.sql". Commit the updated .gitattributes.
  5. Push: git add . && git commit -m "Add Spotify playlists dataset" && git push.
  6. Add metadata: The README.md you are reading doubles as the Hugging Face dataset card, so it will render on the hub automatically.

Optional: Add any additional metadata files (schema diagrams, notebooks, etc.) to enrich the dataset card and help users onboard faster.

License

Creative Commons Attribution 4.0 International (CC BY 4.0). See LICENSE for the full text. When using the dataset, credit “Spotify Public Playlists (Nov 2025)” and include a link back to the Hugging Face dataset page or this repository.

Citation

@dataset{spotify_public_playlists_nov2025,
  title        = Spotify Public Playlists (November 2025),
  author       = Max max@losthills.io,
  year         = 2025,
  howpublished = Hugging Face Datasets,
  note         = CC-BY 4.0
}

Contact

Questions or takedown requests? Open an issue or reach out via the contact info on your Hugging Face profile.

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