What music do I actually like?
Welcome to the ultimate genre-tagged music dataset, meticulously crafted by a data-loving curator with a passion for clean formats, deep analysis, and playlist perfection.
This sheet isn't just a list—it's a launchpad for music discovery, genre exploration, and dashboard-ready insights. Here's what I've done:
- ✅ Cleaned and de-duplicated hundreds of tracks for consistency and clarity
- 🎯 Tagged genres with precision, using modular formatting for easy filtering and clustering
- 🧼 Removed hidden characters and formatting glitches that mess with Excel workflows
- 📊 Prepped for dashboarding, with genre overlap analysis and playlist clustering in mind I've seperated artists from featuring
- 🧠 Prepped for Logical Analysis,column creation for duration, high/low danceability, sub-genre and featuring artists for deeper analysis.
I’m passionate about music discovery and data design. This dashboard is part of a larger initiative to:
- Consolidate genre tags for clustering and visualization
- Map subgenres for deeper insight
- Build modular, Excel-ready formats for future dashboards- Understanding my music taste
- Highlight the different genres to further explore said genres
- Explore historical musical behaviour
- Discovery of any cause and effect; Do I just like it because it's loud?
Welcome to my genre-fueled data universe! This dashboard is a visual symphony of my Spotify listening habits—curated, cleaned, and crafted with precision. Built in Tableau, it’s where music meets metrics and playlists become patterns. Spotify wrapped wasn't enough for me and I wanted to really delve deeper into the historical shifts in my listening habits.
This dashboard transforms raw Spotify data into rich, interactive visuals. Here's a peek at the highlights:
- A vibrant breakdown of genres across my library—from Neo-Soul to Afroswing, each slice reveals the diversity of my musical taste.
- Color-coded for clarity and impact, this chart is your gateway to my sonic landscape.
- I wanted to find my most listened to artists, not just this year but for every year since I first used Spotify.
2017 Data
2025 Data
All Time
- Similarly to my top artists i wanted to discover how my genre consumption has changed over the years- Spoiler Alert, it hasn't changed much
**2017 Data **
2025 Data
All-Time
- I wanted to explore the valence of my liked songs across genre and by year to find out the general vibes of my music from an unbiased and statistical view.
Welcome to my data playground! This Power BI dashboard is a deep dive into my Spotify listening habits, genre preferences, and musical quirks—curated, cleaned, and visualized with love and a whole lot of Excel magic. I used PowerBI to explore the numerical analytics of my listening data and to explore how my habits have changed over time, particularly by genre.
https://app.powerbi.com/links/QqgrsP3MT_?ctid=3ea7c128-c601-4479-a003-e14d00c0b5cb&pbi_source=linkShare
- From Ambient Pop to Afro-Brazilian, the dashboard maps a wide spectrum of genres and subgenres.
- Explore how my taste spans decades—60s Soul, 80s Rock, and modern gems like Alté and Afroswing.
- Ever wondered how energetic my playlists are? This chart plots Danceability and Energy against Tempo, revealing the pulse of my music collection.
- A scatterplot showing how mellow or intense my tracks are—perfect for spotting ambient chill-outs vs. high-octane bangers.
- See how my music choices evolved from 2017 to 2025, with average popularity scores mapped by year.
- A cheeky look at how many tracks are marked Explicit vs. Clean. Spoiler: I don’t shy away from lyrical honesty.
If you’re into music data, genre taxonomy, or just love a good dashboard, let’s chat! I’m always open to collaboration, feedback, or playlist swaps.
“Data is the new vinyl. Curate it, clean it, and spin it with style.” — Meg
📬 Let’s connect: Whether you're building a music app, researching genre trends, or just love a good playlist, I’m open to collaboration.