Build interactive Beatles visuals

Build interactive Beatles visuals#

This page shows how to generate interactive charts from the Beatles dataset:

1) Download the data#

Download the Kaggle CSV and place it at:

projects/beatles-discography/data/beatles_spotify_dataset.csv

If Kaggle CLI is configured:

kaggle datasets download -d jarredpriester/the-beatles-spotify-dataset -p projects/beatles-discography/data --unzip

2) Generate the visual outputs#

Run from repository root:

python3 projects/beatles-discography/beatles_visuals.py

This script will create:

  • projects/beatles-discography/outputs/writer_popularity_by_writer.html

  • projects/beatles-discography/outputs/sunburst_discography_by_album.html

  • projects/beatles-discography/outputs/sunburst_discography_by_writer.html

3) What each visual shows#

Writer popularity by writer / writers#

  • Aggregates songs by writer (splits collaborations like “Lennon and McCartney”)

  • Computes average popularity score for each writer

  • Colors bars by number of unique songs

This answers: Which writers are associated with higher-popularity songs?

Sunburst: full discography by album#

  • Hierarchy: Album -> Song

  • Segment size and color reflect popularity score

  • Useful for album-level comparisons and hit concentration

Sunburst: full discography by writer#

  • Hierarchy: Writer -> Album -> Song

  • Highlights how writing contributions are spread across albums

  • Makes collaborations and writer dominance visually obvious

Implementation notes#

The script supports common schema variants:

  • Song columns: song, title, track_name, name

  • Writer columns: writer, writers, songwriter, songwriters

  • Popularity columns: popularity, track_popularity, top.50.billboard, etc.

If writer fields are missing, it attempts an enrichment join using a public Beatles songwriter reference dataset keyed by song title.

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