Nightingale Rose Chart
A polar area chart where equal-angle wedges vary in radius, so area encodes the value — famously invented by Florence Nightingale to visualize wartime mortality causes.
// 01 — The chart
What it looks like
A Nightingale rose showing monthly rainfall. Larger wedges indicate wetter months; the highlighted wedge (January) is the wettest.
// 02 — Definition
What is a Nightingale rose chart?
A Nightingale rose chart (also called a coxcomb chart or polar area diagram) is a circular chart where categories occupy equal-angle wedges and the area of each wedge encodes the data value. Larger values produce wedges with a greater radius, and therefore more area.
It was invented in 1858 by Florence Nightingale, who used it to argue that preventable disease — not combat wounds — was the leading cause of death among British soldiers in the Crimean War. Her chart was one of history’s most effective data visualizations, directly influencing public health policy.
Unlike a pie chart (which uses angle to encode values), a Nightingale rose uses radius (and thus area). This makes large values visually exaggerated because area grows with the square of the radius — a doubling of value looks more than twice as big.
Origin: Florence Nightingale published her “Diagram of the Causes of Mortality” in 1858. It remains one of the most famous statistical graphics in history and helped establish modern nursing and public health practices.
// 03 — Anatomy
Parts of a Nightingale rose chart
// 04 — Usage
When to use it — and when not to
- Your data has a cyclical or periodic nature (months, hours, seasons)
- You want to make the chart itself visually memorable
- You have 6–12 categories of roughly equal angular importance
- The goal is to highlight dramatic differences in magnitude
- You want to combine comparison with a circular/temporal metaphor
- Exact value comparison is critical — area encoding is imprecise
- You have more than 12 categories — wedges become too thin to read
- Values are very similar — the differences will be nearly invisible
- Your audience is unfamiliar with polar charts
- You need a zero baseline — the radial distortion can be misleading
// 05 — Reading guide
How to read a Nightingale rose chart
Note the equal angles
Unlike a pie chart, every wedge spans the same angle. Differences in size come from radius, not angle.
Compare radii and areas
Larger wedges (more area) represent higher values. The radius determines the area — area grows as the square of the radius.
Use gridlines to estimate
Concentric circles act as your scale. Count rings to approximate values.
Look for patterns around the circle
If categories have a natural sequence (months, hours), the shape of the rose reveals seasonal or cyclical patterns.
Be aware of the area bias
A value that is twice as large will produce a wedge with four times the area (area ∝ r²). This exaggerates large differences.
// 06 — Data format
What your data should look like
| Column | Type | Description |
|---|---|---|
| Category | String | Label for each wedge (e.g., month, department) |
| Value | Number | The measured quantity that determines wedge radius/area |
Jan, 82
Feb, 65
Mar, 48
Apr, 34
May, 42
Jun, 56
// 07 — Construction
How to build a Nightingale rose chart
Divide the circle into equal slices
Each category gets an equal angular wedge. With 12 months, each slice is 30°.
Map values to radii
The radius of each wedge should be proportional to the square root of the value (so that area, not radius, is proportional to the data).
Draw concentric gridlines
Add 3–5 reference circles at equal intervals to help readers gauge the scale.
Fill each wedge
Use a colour palette that differentiates categories. Highlight the most important wedge.
Label around the perimeter
Place category names outside each wedge, aligned with the angle of the slice.
// 08 — Pitfalls
Common mistakes
Using radius instead of area for encoding
If you map values directly to radius (instead of √value), large values are quadratically exaggerated. Always use area-proportional mapping.
Too many categories
Beyond 12 wedges, labels overlap and slices become too thin. Aggregate small categories.
No gridlines
Without concentric rings, readers cannot estimate values. Always include a clear radial scale.
Confusing it with a pie chart
In a pie chart, angle encodes value. In a rose chart, radius/area encodes value while angles are equal. Make this clear in your legend.
// 09 — In the wild
Real-world examples
Florence Nightingale's mortality diagram (1858)
The original: showed that preventable diseases killed far more soldiers than battle wounds, directly leading to sanitary reforms.
Climate data visualizations
Monthly temperature anomalies or precipitation totals arranged around the calendar year, revealing seasonal patterns at a glance.
Wind rose diagrams
Meteorologists use a similar form to show wind speed and direction frequency, with each angular segment representing a compass bearing.
// 10 — Quick reference
Key facts
| Also known as | Coxcomb chart, polar area diagram |
| Invented by | Florence Nightingale (1858) |
| Encoding | Area (radius²) of equal-angle wedges |
| Best category count | 6 – 12 |
| Key weakness | Area grows with r², exaggerating large values |
// 11 — Accessibility
Accessibility notes
Include an accessible data table
Screen readers cannot interpret radial SVGs. Provide a table with the same data alongside the chart.
Add ARIA labels to each wedge
Every SVG path should have an aria-label like "January: 82mm rainfall" for assistive technology.
Use patterns in addition to colour
Colour-blind users may not distinguish wedges. Add stripes, dots, or hatching to differentiate slices.
Offer a linear alternative
Consider providing a toggle to view the same data as a bar chart for users who find radial layouts difficult to read.
// 12 — Variations
Variations
Stacked coxcomb
Multiple series stacked within each wedge to show composition within categories
Wind rose
A meteorological variant where direction is the angular axis and wind speed is the radial axis
Spiral rose
Multiple years overlaid on the same rose, with older data at the center and newer data at the rim
// 13 — FAQs
Frequently asked questions
What is a nightingale rose chart?+
A Nightingale rose chart (also called a coxcomb chart or polar area diagram) is a circular chart where categories occupy equal-angle wedges and the area of each wedge encodes the data value. Larger values produce wedges with a greater radius, and therefore more area.
When should you use a nightingale rose chart?+
Use a nightingale rose chart when your data has a cyclical or periodic nature (months, hours, seasons). It also works well when you want to make the chart itself visually memorable, and when you have 6–12 categories of roughly equal angular importance.
When should you avoid a nightingale rose chart?+
Avoid a nightingale rose chart when exact value comparison is critical — area encoding is imprecise. It is also a poor fit when you have more than 12 categories — wedges become too thin to read, or when values are very similar — the differences will be nearly invisible.
Are nightingale rose charts accessible to screen readers?+
Yes — a nightingale rose chart can be made accessible to screen readers by pairing it with a clear text summary of the key insight, ensuring color choices meet WCAG contrast guidelines, adding descriptive alt text or aria-label to the SVG, and offering the underlying data as an HTML table fallback for assistive technologies.
Is a nightingale rose chart suitable for dashboards?+
Yes — a nightingale rose chart can work well in dashboards as long as the panel is large enough for readers to perceive the encoded values, has a clear title, and includes the legend or axis labels needed to interpret it.
What category of chart is a nightingale rose chart?+
Nightingale Rose Chart belongs to the Comparison family of charts. Charts in that family are designed to answer the same kind of question, so they often work as alternatives when one doesn't quite fit your data.