Spotify Songs and Playlists Analysis Project

Overview

This project provides an analytical view of 30,000 songs extracted from Spotify playlists, highlighting album releases, genre distributions, and artist popularity trends.

Features

• Visualization of album releases over the years.
• Genre analysis displaying the count of tracks per genre.
• Artist popularity tracking over time.
• Interactive elements to filter data based on genres and artists.
• Average age of the artists at their first album release (currently not working)

Dataset Source

The data is based on a Kaggle dataset of 30,000 Spotify songs.

How to Use

1. Album Release Trends: View the graph showing the distribution of album releases over the years.
2. Genre Analysis: Explore the graph detailing the number of tracks per genre.
3. Artist Popularity: Search for artists to visualize their track popularity across different years.
4. Danceability and Speechiness: Compare these metrics across selected genres.

Technical Details

• Employs d3sparql.js for querying, handling SPARQL results and data visualization.
• Integrates with a SPARQL endpoint to fetch data.

Installation & execution

You need docker compose to build this project. To build the project, execute the following commands:

Note: Building the images can take a few minutes.

docker-compose build --no-cache fuseki
docker-compose build --no-cache d3_webserver

Then to start the project, execute :

docker compose up

The Fuseki web UI will be accessible on localhost:3030 and the web app for data visualization will be accessible on localhost:8080. The fuseki database endpoint is on localhost:3333.