[rug-basic] Basic Rug Plot

[MarkusNeusinger]

Description

A rug plot displays individual data points as small tick marks along an axis, typically at the bottom or side of another plot. It shows the actual data distribution without binning, complementing histograms, density plots, or scatter plots.

Key Features

• Small vertical or horizontal ticks for each observation
• Shows exact data point locations
• Reveals clustering and gaps in data
• Minimal visual footprint, perfect as supplement to other plots

Applications

• Showing underlying data in density/histogram plots
• Revealing data concentration and gaps
• Displaying marginal distributions in scatter plots
• Identifying potential outliers at distribution edges

Data Requirements

• values (numeric) - Continuous variable
• Size: Works with any sample size (5 to 1000+ observations)

Visual Elements

• Short tick marks along axis edge
• Consistent tick height/width
• Semi-transparent for overlapping observations
• Positioned along x-axis, y-axis, or both

[claude]

✅ Spec ID: rug-basic

Rationale: A rug plot is a distinct visualization type displaying individual data points as tick marks along an axis - not covered by existing specs.

Add label approved to begin generation.

[github-actions]

✅ Specification Ready: rug-basic

PR: #1004

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specification.md

rug-basic: Basic Rug Plot

Description

A rug plot displays individual data points as small tick marks along an axis, typically at the bottom or side of another plot. Unlike histograms or density plots that bin data, rug plots show the exact location of every observation. They reveal clustering patterns, gaps in data, and the precise distribution of values with minimal visual footprint.

Applications

• Showing the underlying data points alongside a kernel density estimate or histogram
• Revealing gaps and clusters in continuous data that binning would hide
• Displaying marginal distributions along the axes of scatter plots
• Identifying potential outliers at the edges of a distribution

Data

• values (numeric) - Continuous variable to display as tick marks
• Size: 5-1000+ observations (works well at any sample size)
• Example: Measurement data, response times, or any continuous variable

Notes

• Use semi-transparency (alpha) when observations overlap
• Tick height should be consistent and small relative to the plot
• Position along x-axis by default, but can be placed on y-axis
• Works best as a complement to histograms, density plots, or scatter plots

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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: rug-basic
PR: #1004 (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

Or use workflow dispatch for bulk operations.

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🤖 spec-create workflow