areevesman/spotify-wrapped
Using Python to perform data visualization and machine learning on the annual Spotify wrapped top songs playlists
This project helps music enthusiasts and Spotify users explore their listening habits in more detail than the annual Spotify Wrapped. By analyzing your top songs from Spotify Wrapped, it generates new visualizations and insights into your musical preferences. The output helps you understand trends in your taste over time.
No commits in the last 6 months.
Use this if you're a Spotify user curious to dive deeper into your listening history and discover patterns beyond what Spotify Wrapped provides.
Not ideal if you're looking for real-time analytics or integration with other music platforms besides Spotify.
Stars
39
Forks
12
Language
Jupyter Notebook
License
—
Category
Last pushed
Mar 24, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/areevesman/spotify-wrapped"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
ucalyptus/Spotify-Recommendation-Engine
Music Recommender System
ronibandini/reggaetonBeGone
Detects reggaeton genre with Machine Learning and sends packets to disable BT speakers (hopefully)
pooranjoyb/BeatBridge
A Music Player with a Clustering based Recommendation Engine utilizing Spotify API
mattmurray/music_recommender
Music recommender using deep learning with Keras and TensorFlow
maurocastermans/now-playing
Raspberry Pi application that detects music with ML, identifies it using Shazam, and shows the...