Playlist Dynamics and Curation Behavior Dataset
Group Category: Dataset
Product Category: Database Design & Development
Sub Category: PostgreSQL
Understand playlist behavior, track user curation trends, and analyze music discovery patterns with structured, SQL-ready playlist datasets.
Business Overview:
This dataset captures playlist creation and interaction activity within a streaming platform. It includes data on users, playlists, songs in playlists, and playlist followers. It helps understand content discovery and curation patterns.
Product Highlights:
- Structured CSVs (
playlists,playlist_songs,users,songs,artists,playlist_follows) - Perfect for analyzing playlist popularity and trends
- Helps develop features like collaborative filtering
- Supports relational modeling of curated content
Learning Outcomes:
- Analyze user playlist behavior and engagement
- Track artist diversity and playlist follower trends
- Work with playlist-songs relationships and many-to-many joins
- Segment passive vs. active users based on playlist metrics
user_playlist_follows
| CSVCaptures user behavior around playlist following, indicating engagement with curated content. Useful for studying influence and playlist virality.
Key Features:
- 2,573 user-playlist follow events
- Tracks which users follow which playlists
- Ideal for engagement modeling and influence scoring
users
| CSVContains registered user profiles including username, email, subscription type, and profile metadata.
Key Features:
- 9000 user records
- Useful for segmentation, user behavior tracking, and personalization models
- Enables joins with playlists, follows, and listening behavior for comprehensive analytics
Dataset Document
| PDFThis documentation presents a dataset centered around playlist usage, user follows, and song curation. It helps explore how users interact with playlists, what drives playlist engagement, and how curated content spreads across a user base.
Highlights:
- Describes 6 CSV tables spanning playlists, user follows, song associations, and curators
- Suitable for recommendation systems, playlist popularity scoring, and collaboration detection
- Ideal for data engineers, feature teams, and personalization engine builders
artists
| CSVIncludes basic artist metadata such as name and bio. Useful for mapping content contributors and building artist-level profiles.
Key Features:
- 1,097 artist records
- Contains artist names, bios, and timestamps
- Ideal for linking songs or albums with creator identities
playlist_songs
| CSVMaps individual songs to playlists, enabling tracklist analysis, playlist depth checks, and user curation pattern studies.
Key Features:
- 10,658 mappings between playlists and songs
- Many-to-many relationship support for song inclusion
- Useful for playlist content ranking and overlap analysis
playlists
| CSVContains playlist metadata including title, description, creator info, and creation timestamp. Essential for user-generated content analytics.
Key Features:
- 3,228 playlists with user and metadata links
- Supports curation behavior analysis and theme categorization
- Enables trend monitoring in user or platform-generated playlists
songs
| CSVProvides detailed song information including title, duration, file reference, and artist association. Crucial for audio catalog and content metadata.
Key Features:
- 9,383 songs with complete metadata
- Includes artist and album references
- Suitable for playback analytics, popularity tracking, and catalog enrichment
$1.60 $1.00 37% OFF
About this Dataset:
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