Donut Chart
A ring-shaped chart that shows proportions of a whole — like a pie chart with a hollow center. The center space can display a total, label, or icon.
// 01 — The chart
What it looks like
A donut chart showing website traffic sources. The center displays the total visitor count, while each arc represents a traffic channel’s share.
// 02 — Definition
What is a donut chart?
A donut chart (also called a doughnut chart) is a circular chart that represents proportions of a whole, just like a pie chart — but with a hollow center. Each arc’s angular size is proportional to the value it represents: a larger arc means a bigger share of the total.
The blank center is the key advantage over a standard pie chart. It can be used to display a summary statistic (like the total), an icon, or a label — making the chart more informative without adding clutter. The ring shape also reduces the emphasis on comparing individual slice areas, which humans are not naturally good at estimating.
Donut charts are especially popular in dashboards and infographics where space is limited and visual elegance matters. They work best with 3–6 categories — beyond that, the arcs become too thin to distinguish.
Origin: The donut chart is a modern variation of the pie chart, which was invented by William Playfair in 1801. The hollow-center design became popular in the early 2000s with the rise of data dashboards and infographic design, offering a sleeker, more modern look than the traditional filled pie.
// 03 — Anatomy
Parts of a donut chart
// 04 — Usage
When to use it — and when not to
- Showing proportions of a whole with 3–6 categories
- You want to display a key metric (total, percentage) in the center
- Building dashboards where space is at a premium
- Comparing one dominant category against several smaller ones
- Creating infographics where visual elegance matters
- Your audience needs a quick, high-level overview of composition
- You have more than 6–7 categories — arcs become too thin to read
- Precise comparison between slices is important — use a bar chart instead
- Your data doesn't represent parts of a meaningful whole
- Multiple small slices are nearly equal in size — differences will be invisible
- You need to show change over time — use a line or area chart
- You're comparing across multiple wholes — use stacked bars instead
// 05 — Reading guide
How to read a donut chart
Follow these steps whenever you encounter a donut chart in the wild.
Read the title and center label first
Understand what "whole" the chart represents. If there's a number in the center, that's usually the total. Make sure you know the units — dollars, users, percentage points.
Identify the largest arc
Your eye will naturally gravitate to the biggest segment. This is the dominant category. Read its label and percentage to anchor your understanding of the data.
Scan the remaining arcs clockwise
Most donut charts order arcs from largest to smallest starting at the 12 o'clock position. Follow them around to understand the relative contribution of each category.
Look for the legend or data labels
Arcs alone don't tell you exact values. Check for percentage labels on or near each arc, or a legend that maps colors to categories. Without these, the chart is hard to interpret precisely.
Compare relative sizes, not exact areas
Donut charts are best for showing 'roughly half,' 'about a quarter,' or 'a small sliver.' Don't try to read exact differences between similarly sized arcs — use a bar chart for that level of precision.
// 06 — Common mistakes
Mistakes to watch out for
Too many slices
Beyond 6–7 arcs, individual segments become too thin to distinguish visually. Tiny slivers are meaningless to the reader. Group small categories into an "Other" slice, or switch to a bar chart for many categories.
Slices that don't add up to 100%
Every donut chart must represent a complete whole. If your categories are overlapping or don't sum to 100%, the chart is fundamentally misleading. Double-check your data before plotting.
Using 3D or exploded effects
Pulling slices away from the center or adding perspective distortion makes it impossible to compare arc sizes accurately. The front-facing slices look larger than they really are. Always use flat, 2D donuts.
Comparing across multiple donuts
Placing two donut charts side by side and asking readers to compare individual slices between them is extremely difficult. Use a grouped or stacked bar chart for cross-group comparisons.
Missing labels or legend
Without percentage labels or a color legend, readers cannot identify which arc represents which category. Always include clear labeling — relying on memory of colors alone is unreliable.
// 07 — Real-world examples
Where you’ll see donut charts used
Dashboards: Revenue by product line
A SaaS company's executive dashboard showing how total annual revenue breaks down across four product tiers. The center displays total ARR ($24M), while each arc shows a product line's contribution. Leadership can see at a glance that Enterprise accounts for over half of revenue.
Business AnalyticsInfographics: Global energy mix
A climate report infographic showing what percentage of world energy comes from fossil fuels, renewables, and nuclear. The donut format lets the designer place a globe icon in the center, creating a visually compelling composition that tells the story instantly.
Data JournalismPortfolio analysis: Asset allocation
A financial advisor's report showing a client's investment portfolio broken into stocks, bonds, real estate, and cash. The center displays total portfolio value, and the ring makes it easy to see that equities dominate the allocation at roughly 60%.
Finance// 08 — At a glance
Quick reference
// 09 — Variations
Types of donut charts
The basic donut has several variations that serve different design and data needs.
Gauge / progress donut
Shows a single value as progress toward a goal. Common in KPI dashboards for metrics like completion rate or quota attainment.
Nested donut (sunburst)
Concentric rings that show hierarchical part-to-whole relationships, such as category and sub-category breakdowns.
Semi-donut (half donut)
Uses only the top half of the ring. Saves vertical space and gives a gauge-like feel while still showing multiple categories.
Small multiples donut
Multiple small donuts side by side, each showing the same metric for a different group. Good for comparing composition across segments.
// 10 — FAQs
Frequently asked questions
What is a donut chart?+
A donut chart (also called a doughnut chart) is a circular chart that represents proportions of a whole, just like a pie chart — but with a hollow center. Each arc's angular size is proportional to the value it represents: a larger arc means a bigger share of the total.
When should you use a donut chart?+
Use a donut chart when showing proportions of a whole with 3–6 categories. It also works well when you want to display a key metric (total, percentage) in the center, and when building dashboards where space is at a premium.
When should you avoid a donut chart?+
Avoid a donut chart when you have more than 6–7 categories — arcs become too thin to read. It is also a poor fit when precise comparison between slices is important — use a bar chart instead, or when your data doesn't represent parts of a meaningful whole.
How is a donut chart different from a pie chart?+
Both a donut chart and a pie chart can look similar at first glance, but they answer different questions. Reach for a donut chart when the comparisons and patterns it was designed to reveal match what you need to communicate, and choose a pie chart when its particular strengths better fit your data and audience.
Is a donut chart suitable for dashboards?+
Yes — a donut 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 donut chart?+
Donut Chart belongs to the Part-to-whole 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.