Title: Categorical variable: pie charts
Course: UGQuants (SSPS) > Section: Data Visualisation

Categorical variable: pie charts

Pie charts are used to provide a visual representation of the relative prevalence of different categories in a nominal or ordinal variable.  Consider the pie-chart below which shows how interested the UK respondents of the 2010 European Social Survey were in politics.

Figure 6: Pie chart of interest in politics

Source: ESS 2010 (UK).

In the above figure, the relative size of the pie slices represents the relative prevalence of the different answers in the dataset.  In this case, it is relatively clear which answer is most common in the data (quite interested).  However, this is only because of the high popularity of that answer.  Human perception is generally poor at distinguishing between the relative size of 2D spaces which are broadly similar, or in identifying small difference between angles.  For instance, it is much more difficult to place the categories in the variable below in order from most common to least common based on the graph.  A problem which becomes more difficult when the information about which category is represented by which slice of the pie is provided in a legend separate from the graph.

Figure 7: Pie chart of subjective health

Source: ESS 2010 (UK)

It is possible to overcome some of the difficulties mentioned above through redesigning the pie chart.  Notably, rather than relying on perception of the different slices, the values represented by each slice in the graph can be written directly on to the visualisation.  Likewise, rather than including the labels for the different responses in a legend, they can be added directly to the graph, finally, if the intention is to talk about one specific category, this can be separated from the rest of the graph.

Figure 8: Pie chart of subjective health

Source: ESS 2010 (UK).

Overall, the second graph is easier to interpret, and draws particular attention to the most popular answer.  This helps to illustrate how the layout of a visualisation can go a long way to deciding the successfulness of a graph is imparting information to the reader.  However, it is worth asking the question to what extent is it worth using a particular visualisation if the only way we can ensure its reliable interpretation is to write figures on it directly?  Would a table not be more appropriate?