Customizing your pie chart

Once you have uploaded your dataset into Datawrapper and selected the pie chart, you can customize its appearance in step 3: Visualize.


The first thing you will notice is that the pie chart might be too small. You have two options to  resize the chart, either through resizing using your mouse or by specifying the exact size you want:

  • Click, hold, and drag the resize arrow in the bottom right corner of the chart:

  • specify the exact size of the chart by defining the height and width in pixels with the help of the boxes below the chart:
1

Refine

In the "Refine" tab, you'll see some options in four groups: Pie slices, Labels, Color Key and Grouping. Let's go through all four groups, step by step:

  • Select column: Here you can choose the column that you want to visualize. By default, your first numerical column is chosen. Please note: Your pie chart can only show one numerical column. If you've uploaded more than one column with numbers and want to show all, choose the "Multiple Pies" chart type instead. 
  • Slice color: Click on "customize colors" and then select each element to give each slice a specific color. 
  • Pie size: You can decide how much margin your pie should have to all sides with this Pie size. Choose a small percentage to keep the total chart height small. 
  • Sort by: By default, the slices in your pie are sorted from largest to smallest value. So even if your original values are not sorted, the final pie chart is. You can click on "keep order" if you want to have your pie slices sorted according to you original values.

  • Number format: This dropdown menu has multiple options. They will be especially important in case your numbers are very "long" (e.g. 1,992,394 or 0.4239291) and you want to display them abbreviated (e.g. 1.9m or 0.424). Choose e.g. "123.4k" to turn 1,992,394 into 1.9m. 
  • Convert values to percentages: You can upload absolute relative or absolute numbers to Datawrapper to create a pie chart. In case you uploaded absolute numbers (like we did for the chart above) and want to show percentages, make sure to enable this option. 
  • Inside labels and Outside Labels: There are two ways to display labels: Inside the pie slices or outside the pie slices. You can click on the little grey or blue switch to turn these options on and off. Inside these options hide some ways to style the labels, like "Show labels" or "Use slice color for labels":

    Inside labels with "Show labels" and "Show values" turned on, and color key enabled (scroll down to learn more about how to enable the color key):

    Outside labels with "Show values" turned on. The color key disabled itself automatically when you turn outside  labels,  since the available space wouldn't be enough to show both the outside labels and the color key.

If you enable the color key, you'll see the names of your pie slices listed in your chart: 

  • Position: You can decide if your color key should be at the top, bottom, left or right of your chart.
  • Stack labels: Instead of listing the pie slice names next to each, you can stack these labels. That's only possible if "position" is either "top" or "bottom". 
  • Show values: Click if you want to include the values of each slice in the color key (as in the example above). 

The last group in the Refine tab is "Grouping". If you upload more than five pie slices, the smallest pie slices will be automatically grouped in one slice with a label. Here you can define that maximum number of slices, and what that slice label should be.

These are all the options you can find in the Refine tab. Let's move on to the Annotate tab. Here you'll find two options: "Describe chart" and "Highlight elements".


2

Annotate

Describe chart

If you've created a Datawrapper chart or map before, you already know this feature. Here we can give your chart a title, a description, add notes and a source:

  • We recommend using the title to tell your readers what's interesting about this chart – the one key statement that you want to show on this chart, e.g. "Unemployment highest in the south"
  • The description should have as much information about the data as possible: What do we see exactly? E.g. "Unemployment rates in % in all US states, 2016"
  • Think of notes as footnotes, where we want to specify any abnormalities about your data. E.g. "California unemployment rates from Jan and Feb 2016 not included in the calculation."
  • The source name will give our readers the information how trustworthy our data is. Does it come from a government institution or another trustworthy organization? The source URL lets our reader dig even deeper and have a look at the underlying data themselves. Both, source name and source URL, should be filled out on every map or chart to increase transparency. E.g. US Bureau of Labour Statistics, August 2017

Highlight element

In the 2nd panel in the "Annotate" tab, you can emphasize certain pie slices. All the other pie slices will then tone down in their color. To remove added elements, click on the little "x" left of the text in the blue button:

After the Annotate options, there's only one tab left: Design. 


3

Design

In this last step, you can select a preset layout and enable social sharing functions to spread your work. 

  • Users of the free plan or Single users have two options: One layout with and one without the "Get the data" link
  • Users of Datawrapper Team are able to select a custom layout here 

4

Publish

After we worked through the four tabs of step 3: Visualize, we can now proceed to step 4: Publish & Embed. Here we can select a preset layout and enable social sharing functions to spread your work. Click on "Publish" and you'll be directed to the "Publish & Embed" page.

The best way to use a Datawrapper chart is by embedding it directly on your website. To do that, click the big blue button that says " Embed chart on website". Then, copy & paste the embed code snippet into your website or CMS. You can also download your chart as a PNG or PDF by upgrading to a paid Single or Team account. Click here for more information on the different pricing plans of Datawrapper.

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