Posted in Data visualisation

Visualising distributions with pie charts, donut plots and stacked graphs

Pie charts can be used to display distribution of variables within datasets.

A pie chart is a chart that uses the pie slices to display the relative size or proportion of the different variables. In general, pie charts are easier to visualise if the pie has no more than 7 slices.

Consider the dataset where 10 patients are infected with virus X, 6 of which experience no symptoms. The remaining 4 patients are symptomatic, of which 2 of them experience headaches, 1 with fever and 1 with rashes. Here, you can simply use a pie chart to display the data:

I have used the Prism software to plot the pie chart. Note that you can use the colour variants to emphasise on the subjects with symptoms. It is a good habit to include the total counts when presenting pie charts, as these charts meant to only display relative sizes. Note that the pie chart always start at the 12 o’clock position for easy visualisation.

Sometimes, when pie charts are difficult to visualise, another way is to plot a donut plot. The advantage of donut plot is that you can provide additional information in the middle. However, it is important to make sure that the donut is not too thin that can make visualisation difficult. An example is as shown below:

Finally, sometimes it might be more useful to use a stacked bar chart to show the distribution of the data. The stacked bar chart may be more useful when you want to group variables with similar properties (In this case, you can group all the symptomatic patients together). An example is as follows:

There are no fixed rules to justify which of these charts are more suitable for data visualisation. When in doubt, there is no harm in trying to plot all of these graphs and then decide later which is the most suitable for publications or presentations!

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