An end-to-end data analysis project exploring Spotify track trends across 7 years.
Live Demo: https://z1yuguo.github.io/spotify-analysis/ Tableau Dashboard: https://public.tableau.com/app/profile/ziyu.guo/viz/spotify_analysis_17762366860580/Dashboard1
- SQL — SQLite, GROUP BY, CTE, Window Functions (RANK, SUM OVER)
- Python — pandas, Plotly (interactive visualizations)
- Tableau — Dashboard with 3 charts
- HTML/CSS/JS — Single-page web deployment via GitHub Pages
- Dataset contains 1,701 tracks across 5 mood categories (sad, rock, remix, night, love)
- 2016 was the peak year with 303 tracks
- Sad music dominated 2014–2019, consistently ranking #1 in annual share
- Remix surged to 34.5% in 2020 — a notable shift possibly linked to pandemic listening habits
- Lil Peep leads all artists with 21 appearances, followed by Twenty One Pilots (17) and Post Malone (14)
├── spotify_analysis.ipynb # SQL + Python analysis ├── spotify_analysis.twb # Tableau workbook └── docs/ └── index.html # Web dashboard
Data source: Spotify API via Kaggle