Donut charts are one of the most versatile ways to display proportional data. Unlike pie charts, donut charts leave an open center that can display a key metric, total value, or label — making them a favorite for dashboards and reports. This guide walks you through creating donut charts from scratch, choosing the right data, and avoiding the most common mistakes.
What Is a Donut Chart?
A donut chart (also called a doughnut chart or ring chart) is a circular chart divided into segments that represent proportions of a whole. It works exactly like a pie chart, but with a hollow center. Each segment's arc length corresponds to its percentage of the total.
The key advantage of a donut chart is its center space. Designers use this area to display a total, a key metric, or an icon — adding context without cluttering the visualization. This is why donut charts are the default choice for KPI dashboards in eCommerce, marketing, and finance.
When Should You Use a Donut Chart Instead of a Pie Chart?
Both donut and pie charts show part-to-whole relationships, but they serve slightly different purposes. Here is a quick comparison to help you decide:
| Feature | Donut Chart | Pie Chart |
|---|---|---|
| Center space for KPI/label | Yes | No |
| Multiple rings (nested data) | Yes | No |
| Best for dashboards | Yes — compact with context | Adequate |
| Comparing exact slice sizes | Slightly harder | Slightly easier |
| Modern aesthetic | Preferred in UI/UX | Classic look |
Use a donut chart when:
- You need to show a total or key figure in the center (e.g., total revenue, completion percentage)
- Your dashboard has limited space and you want a compact, information-dense chart
- You want to display multiple levels of data using nested rings
- The design calls for a modern, clean look
Stick with a pie chart when:
- You have very few categories (2-3) and want the simplest possible visual
- Your audience is less data-literate and expects traditional chart formats
For a deeper look at choosing the right chart, see our chart types explained guide.
How to Create a Donut Chart Step by Step
Creating a donut chart with CleanChart's free donut chart maker takes just a few steps:
- Prepare your data. You need at least two columns: a category column (labels) and a value column (numbers). For example: department names and budget amounts. Supported formats include CSV, Excel, JSON, TSV, and Google Sheets — use our CSV to donut chart converter or Excel to donut chart converter to get started quickly.
- Upload or paste your data. Open the donut chart maker, then upload your file or paste data directly. CleanChart auto-detects headers and data types.
- Select your columns. Choose which column contains your category labels and which contains the values.
- Customize the appearance. Adjust colors, labels, legend position, and center text. See our color palette guide for choosing effective chart colors.
- Export your chart. Download as PNG or SVG for reports, presentations, or web use. You can also export directly to PowerPoint.
If your data is in JSON format, use the JSON to donut chart converter. For Google Sheets users, try the Google Sheets to donut chart converter. Working with TSV files? The TSV to donut chart converter handles tab-separated data seamlessly.
What Data Works Best for Donut Charts?
Donut charts work best when your data meets these criteria:
- Part-to-whole relationship. The segments should add up to a meaningful total (100%, total budget, total users, etc.).
- 3 to 7 categories. Fewer than 3 makes the chart trivial; more than 7 becomes hard to read. Group smaller categories into an "Other" slice.
- No negative values. Donut charts cannot represent negative numbers — use a bar chart or waterfall chart instead.
- Categorical data. Each segment represents a distinct category (regions, departments, product lines), not continuous data like time series.
Good examples of donut chart data:
| Use Case | Categories | Values |
|---|---|---|
| Marketing budget breakdown | Social, SEO, PPC, Email, Events | Spend in dollars |
| Website traffic sources | Organic, Direct, Referral, Social, Paid | Sessions or percentage |
| Survey responses | Strongly Agree, Agree, Neutral, Disagree | Number of respondents |
| Revenue by product line | Product A, Product B, Product C | Revenue in dollars |
Need to clean or reformat your data first? Our CSV to JSON converter and CSV to Markdown converter can help you prepare data for different workflows.
Donut Chart Best Practices
Follow these guidelines to create donut charts that communicate clearly:
1. Limit the number of slices
Keep your donut chart to 3-7 segments. If you have more categories, combine the smallest ones into an "Other" slice. Too many thin slices make the chart unreadable.
2. Use meaningful colors
Choose a color palette where each segment is easily distinguishable. Avoid using similar shades for adjacent slices. For accessible designs, follow our colorblind-friendly chart guide to ensure all users can read your chart.
3. Add direct labels
Display percentages or values directly on each segment rather than relying solely on a legend. This reduces the cognitive effort required to interpret the chart.
4. Use the center wisely
The center space is prime real estate. Use it for:
- The total value (e.g., "$1.2M Total Revenue")
- A key metric (e.g., "78% Complete")
- A descriptive title or icon
5. Order slices logically
Start the largest slice at 12 o'clock and arrange segments clockwise by size. This makes the proportions easier to compare at a glance.
6. Consider dark mode
If your dashboard supports dark mode, ensure your donut chart colors have enough contrast against dark backgrounds. CleanChart supports dark mode chart generation out of the box.
Common Donut Chart Mistakes to Avoid
Even experienced analysts make these errors. Here is what to watch out for:
- Too many slices. More than 7-8 segments turns a donut chart into a colorful mess. Use a bar chart for 10+ categories.
- 3D effects. Three-dimensional donut charts distort the perceived size of slices. Always use flat, 2D donut charts for accuracy.
- Missing labels. A donut chart without labels or a legend forces readers to guess. Always label your segments.
- Comparing across multiple donuts. Humans are bad at comparing arc lengths between separate charts. If you need to compare two data sets, use grouped or stacked bar charts instead.
- Using donuts for time-series data. Donut charts show a snapshot at one point in time. For trends over time, use a line chart or area chart.
- Exploded slices. Pulling slices apart for emphasis makes it harder to compare proportions. Use color or bold labels for emphasis instead.
Advanced Donut Chart Techniques
Nested donut charts
Nested (or multi-ring) donut charts display hierarchical data — for example, an outer ring showing sub-categories and an inner ring showing parent categories. This is useful for budget breakdowns where you want to show both department-level and team-level spending.
Progress indicators
A single-value donut chart (one filled segment + one empty segment) works perfectly as a progress indicator. Show the percentage complete in the center for an instantly readable KPI widget — common in dashboard design.
Combining with other charts
Donut charts pair well with other visualizations in dashboards. Use them alongside sparklines for trend context or gauge charts for threshold-based metrics. For a comprehensive data story, see our data storytelling guide.
Frequently Asked Questions
What is the difference between a donut chart and a pie chart?
A donut chart has a hollow center while a pie chart is completely filled. Both show part-to-whole proportions, but the donut chart's center space can display a total value, KPI, or label. Donut charts also support nested rings for hierarchical data, which pie charts cannot do.
How many slices should a donut chart have?
A donut chart should have between 3 and 7 slices for optimal readability. If you have more categories, group the smallest ones into an "Other" category. For more than 10 categories, consider using a bar chart instead.
Can I create a donut chart from a CSV file?
Yes. Use CleanChart's CSV to donut chart converter to upload your CSV file and generate a donut chart instantly. The tool also supports Excel, JSON, and Google Sheets formats.
When should I avoid using a donut chart?
Avoid donut charts when you have negative values, more than 7-8 categories, time-series data, or when you need precise value comparisons between categories. In those cases, bar charts, line charts, or tables are better choices.
Are donut charts accessible for colorblind users?
Donut charts can be made accessible by using a colorblind-friendly palette, adding direct labels to each segment, and using patterns or textures alongside colors. CleanChart's built-in palettes include colorblind-safe options.
Related CleanChart Resources
Chart Makers
- Donut Chart Maker — Create donut charts for free online
- Pie Chart Maker — The classic alternative for proportional data
- Bar Chart Maker — Best for comparing many categories
- Gauge Chart Maker — Single-value progress indicators
- Treemap Maker — Hierarchical part-to-whole visualization
Data Converters
- CSV to Donut Chart
- Excel to Donut Chart
- JSON to Donut Chart
- Google Sheets to Donut Chart
- TSV to Donut Chart
Related Blog Posts
- Pie Chart Guide — When to use pie vs donut charts
- Chart Types Explained — Find the right chart for your data
- Data Visualization Color Palettes — Choose effective chart colors
- Colorblind-Friendly Charts — Make your charts inclusive
- Data Dashboard Design — Layout principles for dashboards with donut charts
- Data Storytelling with Charts — Tell compelling stories with your data
- Visualize eCommerce KPIs — Donut charts for eCommerce dashboards
External Resources
- Wikipedia: Doughnut Chart — History and mathematical background of donut charts
- Data Viz Catalogue: Donut Chart — Visual reference and use case overview
- Google Material Design: Data Visualization — Design guidelines for charts in modern interfaces
- NerdSip — Micro-learning platform for data visualization and analytics
- Storytelling with Data — Best practices for communicating effectively with charts
Last updated: March 25, 2026