[rose-basic] Basic Rose Chart (Nightingale/Coxcomb)

[MarkusNeusinger]

Description

A rose chart (Nightingale or coxcomb diagram) displays data in a circular format where categories are arranged around the center and values are represented by the area of wedge-shaped segments extending from the center.

Key Features

• Circular layout with categories as angular segments
• Segment radius proportional to value (or sqrt for area)
• Can show multiple series as concentric rings
• Historical significance: Nightingale's mortality visualization

Applications

• Cyclical data (months, days of week, hours)
• Directional data (wind rose showing wind directions)
• Comparison of periodic patterns
• Multi-category data with natural circular ordering

Data Requirements

• category (categorical) - Angular positions (e.g., months)
• value (numeric) - Determines segment radius
• Categories often have natural circular ordering
• Size: 4-24 categories typical

Visual Elements

• Wedge-shaped segments from center
• Equal angular width per category
• Radius proportional to value
• Optional: stacked segments for multiple series
• Color coding for categories or series

[claude]

✅ Spec ID: rose-basic

Rationale: Rose chart (Nightingale/coxcomb) is a distinct polar visualization using wedge segments with area proportional to values, different from the existing polar-basic which uses point/line scatter on polar coordinates.

Add label approved to begin generation.

[github-actions]

✅ Specification Ready: rose-basic

PR: #1020

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specification.md

rose-basic: Basic Rose Chart

Description

A rose chart (also called Nightingale or coxcomb diagram) displays categorical data in a circular format where segments are arranged around the center like pie slices, but with radius proportional to the value rather than angle. This visualization excels at showing cyclical or directional patterns where the circular arrangement has natural meaning. The equal-angle wedges make comparison of values across categories intuitive while emphasizing the periodic nature of the data.

Applications

• Visualizing monthly sales, weather patterns, or other data with natural 12-month cycles
• Displaying wind direction frequency (wind rose) showing how often wind blows from each compass direction
• Comparing day-of-week patterns like customer visits, social media engagement, or energy consumption
• Showing hourly distributions where the circular clock face arrangement aids interpretation

Data

• category (categorical) - Angular positions representing periodic categories (e.g., months, directions, hours)
• value (numeric) - Determines segment radius; larger values extend further from center
• Size: 4-24 categories typical; 8-12 optimal for readability
• Example: Monthly rainfall amounts, wind direction frequencies, or hourly traffic counts

Notes

• Segment radius should be proportional to value (not area) for easier visual comparison
• Categories should have natural circular ordering (months, compass directions, hours)
• Use consistent color scheme; single color with varying saturation or distinct colors per category
• Start position typically at top (12 o'clock) for time data or north for directional data
• Include radial gridlines to aid value estimation

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