[density-rug] Density Plot with Rug Marks

[MarkusNeusinger]

A kernel density estimation plot with rug marks (small tick marks) along the x-axis showing individual data point locations. Combines smoothed distribution visualization with raw data visibility.

[claude]

✅ Spec ID: density-rug

Rationale: This combines a kernel density estimation plot with rug marks as a primary feature, bridging the existing density-basic (which has rug as optional) and rug-basic (standalone) specs into a dedicated visualization that emphasizes both the smoothed distribution and raw data visibility.

Add label approved to begin generation.

[github-actions]

✅ Specification Ready: density-rug

PR: #3506

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specification.md

density-rug: Density Plot with Rug Marks

Description

A kernel density estimation (KDE) plot combined with rug marks along the x-axis, showing both the smoothed probability distribution and the exact location of each individual data point. This combination provides the best of both worlds: the KDE reveals the overall shape, modality, and smoothed density of the distribution, while the rug marks preserve transparency about where actual observations fall, highlighting data density and potential gaps.

Applications

• Exploratory data analysis where understanding both distribution shape and raw data placement matters
• Comparing sample distributions while maintaining visibility of actual observation counts and clustering
• Quality control analysis to identify process variations alongside individual measurement locations
• Academic and research presentations requiring both statistical summaries and data transparency

Data

• values (numeric) - The continuous variable to visualize
• Size: 30-500 observations recommended (rug marks become cluttered with very large samples)
• Example: Response times, measurement errors, test scores, or any continuous variable

Notes

• Display the KDE curve with fill for visual weight and the rug marks as small tick marks along the x-axis
• Use semi-transparent fill under the density curve to avoid obscuring the rug
• Rug marks should be subtle but visible, with slight transparency for overlapping points
• Consider jittering rug marks vertically if using thick ticks to reduce overplotting

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Next: Add approved label to merge this specification to main.

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🤖 spec-create workflow

[github-actions]

🚀 Specification Merged!

Specification: density-rug
PR: #3506 (merged)

The specification is now in main and synced to PostgreSQL.

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Next: Add generate:{library} labels to start generating implementations.

Available libraries: matplotlib, seaborn, plotly, bokeh, altair, plotnine, pygal, highcharts, letsplot

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🤖 spec-create workflow