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Clusterfy Clusterfy extracts songs from a user’s Spotify playlists and applies k-means clustering to group songs based on fundamental features such as tempo and key signature. It then provides a visualization of this data by extracting the first 3 principal components from each song’s features and plotting the songs on a 3D chart. Finally, it recommends a playlist based on these clusters and inserts it into the user's Spotify account. How to Use: 1) Start Clusterfy - Run the command "python music_clustering.py" - Go to "http://localhost:5000/" in your web browser 2) Request an OAuth Token from https://developer.spotify.com/web-api/console/post-playlists/ - Fill in your Spotify username and press "Get OAuth Token" - Check "playlist-modify-public" and "playlist-modify-private" and press "Request Token" *Note: OAuth tokens expire after a certain period of time and you will have to request a new one* 3) Enter User Information into Clusterfy - Enter your Spotify username into the text field "Username" - Copy and Paste the OAuth token from the previous step into the text field "Auth Token" - Wait for Clusterfy to finish processing your songs 4) Add Playlists - Check out our cool data visualization of your songs! - If you want to add a playlist built around one of the clusters, click on the corresponding button on the right side of the plot
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Visualization of user's music on spotify app
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