How to create a donut chart
A donut chart is useful when you want to show proportional parts of a whole and want to give the reader an extra data point in the middle. A donut chart should not have too many slices, as the chart otherwise gets cluttered and hard to read – if you want to show more than five parts, consider grouping them or use a bar chart instead.
Below is an example of a donut chart that makes good use of the part of the whole concept: We can see that more than half of German land is used for agriculture:
Preparing and importing the data
If you want to create this chart type, your data needs to be in a certain format. You'll need:
- One header row containing descriptive labels.
- One column containing at least two categories. This will determine the label in the donut slices. In our case, that's "Housing & traffic", "Other land" etc.
- One column containing numeric values. The values in the second column will define the size of the donut slices.
The most important thing you have to keep in mind is that a donut chart always represents a whole, i.e. 100%. Therefore, you can only use data that is based on exclusive values. Making a donut chart of a survey that allows multiple answers will lead to a misleading chart. Use a bar chart instead, but never a donut chart.
That's the data we used to create the chart at the top of the page:
Kind of land square km Housing & traffic 49254 Other land 11300 Agriculture 182637 Forest 106170 Water 8219
Once you prepared your data, create a new chart in Datawrapper. You can do so by going to our homepage and clicking on "Create a chart". In Step 1: Upload, copy & paste your dataset, upload it as a .csv or an Excel sheet. After pasting the data above into Datawrapper, it will look like this:
roceed" at the bottom right to go to the next step:
Check & Describe
In the second step, you can check if your dataset was imported correctly and make changes to it - if necessary. If you did not upload a header row, you have to untick "First row as label" to avoid losing your first row of data. Always remember to do this if you don't have descriptive row and column headers.
In step 2, your data looks like this. You can see that Datawrapper correctly recognized your numbers as numbers (and not as text or dates) because they are colored in blue and are right-alined. To learn more about the Datawrapper's automatic recognition of data formats, visit this article.
Click on "Proceed" at the bottom left to go to Step 3: Visualize:
In this step, you see a first chart. It's probably a line chart. We want to change that. To do so, click on the "Donut chart" symbol in the grid of available chart types:
You will now see a donut chart, without a title, descriptions or customized colors. Maybe you want to further refine, annotate & define this chart.
We cover this in a separate short tutorial found here