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prototype version 2.0.0

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@JaehoonSong12 JaehoonSong12 released this 08 Dec 23:32
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v2.0.0
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Prototype v2 Release Notes

Prototype v2 introduces exciting new visualizations and enhancements to our music analytics project, highlighting the evolution of genres and their relationship with listener demographics. These updates provide deeper insights into music preferences, showcasing trends across generations.

Students Working on Prototype v2

  • Jaehoon Song
  • Yashman Singh
  • Devika Rangnath Papal

Updated Features & Visualizations

1. Genre Evolution Tree

  • Description: A tree diagram that visualizes how music genres like pop and rock have diversified into sub-genres over time.
  • Key Features:
    • Interactive genre nodes.
    • Hover-over functionality for exploring songs, artists, and genre characteristics.
    • A timeline tracking music trends across decades.
  • Purpose: Celebrates the diversity and evolution of music genres, showing how they adapt and branch into new styles.

2. Music Genre Preferences by Age

  • Description: A visualization exploring how music genre preferences vary across different age groups (teens to seniors).
  • Key Features:
    • Stacked bar chart representing genre popularity across age brackets (12-20, 20-35, 35-60, 60+).
    • Hover-over interaction for detailed insights on listener behavior.
  • Purpose: Highlights generational music preferences, providing a deeper understanding of how different audiences connect with music.

Dataset Update

The visualizations are powered by cleaned data from Spotify user research, with sample data as follows:

  • spotify_user_research_cleaned_file.csv:
    Age 12-20 | Fav Music Genre: Pop, Rock, Jazz
    Age 20-35 | Fav Music Genre: Rock, Rap, Melody
    Age 35-60 | Fav Music Genre: Jazz, Melody, Rap

Known Issues

  • The layout of Visualization 5 is currently misaligned, particularly with spacing between bars and axis labels. This will be addressed in the next update.

Screenshot of Updated Page

Next Steps for Prototype v3

  1. Fix layout bugs for Visualization 5.
  2. Expand interactivity by adding filtering options (e.g., by decade or sub-genre).
  3. Implement personalized recommendations based on user preferences derived from the visualized data.
Assets 2
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