INTRODUCTION
In this article, we'll explore a personalized Spotify data visualization I created using Power BI. The visualization provides insights into my most played artists, top tracks, and other interesting metrics derived from my listening history.
PAGE 1
Insights into My Music Taste
The first page of the visualization focuses on my most frequently played artists and tracks each month, shedding light on my evolving music preferences.
Most Played Artists
Through a comprehensive display, I present the artists that dominate my playlist, revealing the frequency of my engagement with their music.
Monthly Play Counts
By breaking down my play counts on a monthly basis, I gain a deeper understanding of how my listening habits fluctuate over time.
Artistic Exploration
A dynamic slicer allows me to explore different artists, offering a granular view of my musical inclinations.
PAGE 2
Unveiling My Favorite Tracks
The second page delves into my top 30 tracks and explores the composition of my music taste through a decomposition tree.
Top 30 Tracks
Presented in order, these are the tracks that have resonated with me the most, giving a glimpse into my favourite songs.
Decomposition Tree
By visualizing the decomposition of play counts for both artists and tracks, I unravel the underlying patterns in my listening history.
PAGE 3
Artist-Centric Insights
The third page concentrates on the count of albums and tracks for each artist, revealing my level of engagement with their musical portfolio.
Artist Albums
This section provides a tally of albums by each artist, allowing for an assessment of their prolificacy.
Track Counts
By quantifying the number of tracks for each artist, I gain a more detailed understanding of their musical output and my listening preferences.
Fine-Tuning Preferences
A customizable slicer for artists empowers me to navigate through the data and tailor the visualization to suit my analytical needs.
Conclusion
In building this Spotify personal data visualization with Power BI, I've gained valuable insights into my musical tastes and listening habits. It's fascinating to see how my preferences change over time and how certain artists and tracks consistently make their way into my playlist. This visualization has not only been informative but has also added a layer of interactivity and excitement to my music exploration journey. I look forward to further refining this visualization and gaining even deeper insights into my musical world.