Skip to content

Latest commit

 

History

History
45 lines (33 loc) · 1.74 KB

README.md

File metadata and controls

45 lines (33 loc) · 1.74 KB
Raw

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.