When we visualise categorical data, we often mean - implicitly - visualising counts of categories in the data, such as the numbers in categories like:
ControlandTreatmentNone,Weak,Moderate, andStrongEurope,North America,South America,Asia,Africa, andAustralasia.
Tables may often be clearer than visualisations for smaller datasets. Graphical options include bar charts, stacked bar charts and pie charts, though pie charts are rarely a good option to choose.
1 Visualisations for categorical variable types
The message we want to get across for a categorical variable is often declarative (“There were this many examples of each category”) or comparative (“There were this many examples of category A relative to category B”). This kind of data is well-represented by a dot chart (essentially, a univariate scatterplot with a single value) or bar chart.
But, if the data is proportion or percentage data, and we want to emphasise the proportion of the total, a more natural representation might seem to be the stacked/divided bar chart or pie chart. However, there is no data that can be represented by a bar chart or pie chart that cannot be represented by a dot chart, and a dot chart is often the clearest representation.