I love music, and it's ability to not only cater to your mood, but change it. ! In fact, when I realized that Spotify stored and shared song metrics including but not limited to danceability, tempo, duration, energry, and valence I knew I had to do something with it.
Therefore, I created a interactive music directory that lets users search + sort music using cool metrics, create playlists, and compare these created playlists via the listed metrics.
In order to develop this directory, I used a Kraggle dataset containg 600k+ Spotify songs and corresponding song data.
We first created a Figma wireframe to design the directory. Then, we used python to pre-process the data file, and load into PostgresSQL.
We devised various sorting algorithms to sort large data sets by the diverse metrics, and we displayed the results used HTML, CSS, and Javascript.
For the back-end we utlized Flask to integrate the API to connect to the database, and run the development server. The result was an interactive Spotify
music directory that not only allows users to search and sort, but create and compare playlists, and eventually download them as a csv file, which could be
imported into music platforms to convert into a listenable playlist.
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CSS 
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Javascript ,
Flask ,
Figma 
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Python 
