Complete Doughnut Chart Guide

A doughnut chart, also known as a donut chart or ring chart, is a modern evolution of the pie chart. It hollows out the center of the pie chart to form a ring structure, representing the proportion of each part to the total through arc length.

The core principle of doughnut charts is the same as pie charts—using area proportions to show part-to-whole relationships—but the hollow design brings unique advantages: the center area can be used to display total values, core metrics, or key conclusions, greatly improving information density.

Doughnut charts have become increasingly popular in the data visualization field in recent years, especially in scenarios like dashboards, KPI cards, and mobile interfaces. With their modern appearance and efficient information delivery, they are gradually becoming the first choice for proportion display.

Our online doughnut chart generator is built on the industry-leading ECharts library, offering rich styles and configuration options. You can create professional-grade doughnut charts without writing a single line of code.

As an evolution of pie charts, doughnut charts bring more advantages while maintaining the intuitiveness of proportion display:

• Center Information Display: This is the biggest advantage of doughnut charts. Displaying totals, core KPIs, or key conclusions in the center—one chart with multiple uses—greatly improves information density.
• More Modern Visual Style: Doughnut charts look lighter and more modern, conforming to current minimalist and flat design trends, and appear more professional in reports and presentations.
• Reduced Area Misjudgment: Research shows that the arc length of doughnut charts is more easily perceived accurately than the sector area of pie charts, reducing misreading caused by area illusion.
• Better Multi-Ring Nesting Capability: Multi-layer doughnut charts can display hierarchical proportion data, with clearer visual effects than multiple pie charts.
• More Efficient Space Utilization: The hollow design makes doughnut charts visually "lighter" and better able to combine with other elements, suitable for dashboards and card layouts.

For these reasons, mastering the correct use of doughnut charts is an essential skill for modern data visualization.

Doughnut charts have a very wide range of applications, especially in modern data visualization design, where they are gradually replacing the position of traditional pie charts.

Doughnut charts are particularly suitable for:

• Dashboard-style KPI Display: Displaying key metric values (such as completion rate, conversion rate, proportion) in the center, with the ring part showing progress or composition—one chart with multiple uses and excellent visual effect.
• Market Share Analysis: Showing the proportion of each brand and channel in the overall market, clearly presenting the competitive landscape and market position.
• User Composition Analysis: Showing demographic characteristics such as age distribution, geographic distribution, membership level distribution, and device distribution of users.
• Income/Expense Composition: Showing financial data such as company revenue source structure, personal expenditure category proportions, and project budget allocation.
• Sales Category Proportion: Showing the contribution proportion of different product categories in total sales, identifying core businesses.
• Survey Result Display: Showing the selection proportion of each option in questionnaires, quickly understanding mainstream opinions.
• Progress/Completion Rate Display: Using the fill proportion of the doughnut chart to show task completion, project progress, goal achievement rate, etc.

Scenarios where doughnut charts are NOT suitable: Precise numerical comparison (use bar charts), showing change trends (use line charts), more than 7 categories, data containing negative values.

Not sure which chart to use? Try our doughnut chart tool, preview effects in real time, and find the best way to present your data.

Good doughnut chart design combines aesthetics with information delivery efficiency, while poor design may confuse readers. Follow these principles to make your doughnut charts more professional:

• Control the Number of Categories: It is recommended to keep within 5-7 categories. Too many categories will result in too small sectors that are difficult to identify. Merge the smallest proportions into an "Other" category.
• Reasonably Use the Center Area: Display totals, core metrics, or key conclusions in the center, letting readers grasp the key points at a glance and improving information density. But don't put too much center content—1-2 core numbers are best.
• Scientific Sorting: Starting from the 12 o'clock direction, arrange clockwise in descending order of value, conforming to natural reading habits.
• Color Scheme: Use color schemes with moderate contrast, with clear distinction between adjacent sector colors; avoid using overly bright and glaring colors.
• Labels and Legends: When data volume is small, directly annotate names and percentages next to sectors; when data volume is large, use legends配合 to keep it clear.
• Ring Width Ratio: Ring width is recommended to be 30%-50% of the radius. Too wide looks bulky, too narrow makes it difficult to identify proportion differences.
• Avoid 3D Effects: 3D perspective distorts sector areas and causes visual misjudgment. Flat 2D doughnut charts are more accurate and more modern.
• Total of 100%: Ensure all categories add up to 100% of the total. Data integrity is the lifeline of proportional charts.

Want to put these principles into practice? Use our doughnut chart generator to adjust parameters in real time and compare the effects of different designs.

Although doughnut charts are beautiful and practical, they are also easy to misuse. Here are the 8 most common mistakes and solutions:

• Too Many Slices: When there are more than 7 categories, small sectors will be crowded together and difficult to identify. Recommendation: consider bar charts when there are more than 6 categories, or merge small items into "Other."
• Similar Values Hard to Distinguish: When the proportions of each part are close (such as 30%, 28%, 25%), the human eye has difficulty accurately judging size. Recommendation: switch to bar charts for more intuitive comparison through height differences.
• Including Negative Numbers: Doughnut charts cannot display negative values. If there are negative numbers in the data, choose bar charts or line charts.
• Incomplete Data: The sum of all categories must equal the whole (100%). Showing only partial categories will mislead readers into thinking these are all.
• Center Area Abuse: Putting too much text or decorative elements in the center will steal the show. Recommendation: only put 1-2 core numbers, keep it concise.
• Doughnut Chart Abuse: When you need to compare trends, precise values, or ranking order, doughnut charts are not the best choice. Choosing the right chart type according to data characteristics is important.
• Chaotic Labels: Forcing labels on too-small sectors will cause text overlap. Recommendation: use legend guidance, or pull out labels and connect them with leader lines.
• Ring Width Proportion Imbalance: Too wide a ring looks like a pie chart with a hole, too narrow looks like a line. Recommendation: keep the ring width between 30%-50% of the radius for the most comfortable viewing.

Remember: doughnut charts are for elegantly showing proportional relationships, not for showing off skills. Simplicity and clarity are always the first priority.

Our doughnut chart tool has built-in design optimizations to help you easily avoid these common pitfalls.

Faced with different data and presentation needs, choosing the right chart type is crucial. Here's a comparison of doughnut charts with common chart types to help you make the right choice:

Doughnut Charts vs. Pie Charts. Both are essentially the same, both showing proportional relationships. Doughnut charts are more modern visually and can display information in the center; pie charts have a stronger "sense of wholeness." Most modern design scenarios recommend using doughnut charts.

Doughnut Charts vs. Bar Charts. Doughnut charts excel at showing proportional relationships; bar charts excel at precise numerical comparison. Use doughnut charts when you want to answer "what percentage does each represent"; use bar charts when you want to answer "who's bigger and by how much."

Doughnut Charts vs. Gauges. Both can display completion rate/progress. Gauges are more suitable for showing the sense of progress of a single metric; doughnut charts are more flexible, able to show both progress and multi-category proportions.

Doughnut Charts vs. Stacked Bar Charts. Doughnut charts are suitable for proportion display of a single group; stacked bar charts are suitable for proportion comparison of multiple groups of data. When you need to compare the composition of multiple wholes, use stacked bar charts.

Single-Layer vs. Multi-Layer Doughnut Charts. Single-layer doughnut charts show one set of proportion data; multi-layer doughnut charts can display hierarchical structures or multiple sets of comparison data, but the number of layers should not be too many (2-3 layers is appropriate).

The principle for choosing chart types: prioritize accurate information delivery, then visual appeal. Always choose the simplest, most intuitive way to present your data.

Not sure which chart works best? Start with doughnut charts—they're the most modern choice for showing proportions.

In the era of data-driven decision-making, we work with all kinds of data every day. Sales data, user data, financial data... these often contain business secrets or personal sensitive information.

Many online chart tools require you to upload your data to a server to generate charts. This brings several risks: your data might be stored, it might be leaked, or it might be used for other purposes. For business and sensitive data, these risks are unacceptable.

One of the core design principles of this tool is "100% frontend-only operation." All data editing, chart rendering, and image export happen locally in your browser. The tool never sends your data content to any server, and it never saves your input data anywhere.

You can use all features of this tool even with your internet disconnected—that's the best proof of pure frontend operation. Your data never leaves your browser—you are in control of your security.

Even so, for data containing highly sensitive information—such as complete production business data or personal user information—we still recommend using the tool in a fully offline or controlled environment, or manually desensitizing sensitive fields before use.

Security is never a trivial matter; caution is always the right choice. Experience the secure and reliable online doughnut chart generator now.