Race categories from a survey:

Marital status:

Gender:

Cloud categories:

Computer type:

Operating system:

Continents:

Currencies:

Languages:

Car types:

Sports:

Categories can be any type of expression, such as strings:

Entities:

Colors:

Pictures:

Numeric categories do not use a numeric scale:

Assign labels and an order to numeric values:

Automatically detected categories are shown in the order they appear in the data:

Specify the categories and what order they should appear in:

Categories that are omitted from the scale are treated as missing and are not shown:

By default, the categories are used as labels:

Specify labels to use in place of the categories:

Provide labels for individual categories:

Labels can be any type of expression:

Obtain a list of properties for a nominal scale:

Extract the list of categories:

Sort the categories alphabetically and create a new scale:

Extract the mapping between categories and labels:

Determine the label for a single category:

Determine the labels for a list of categories:

By default, labels are oriented horizontally:

Rotate the tick labels for better reading:

Use NominalScale in a BubbleChart:

Use it in GroupBy:

Use ParallelAxisPlot to plot multi-categorical orange wholesale data from the USDA:

Visualize the electrical type of a class of chemical elements:

Visualize the natural state of the elements:

Plot which blocks the elements are in:

Use ParallelAxisPlot to plot car specifications with NominalScale:

Plot types of precipitation for a couple months:

Show grades for students in a classroom:

Plot the DNA sequence for part of a chromosome:

Plot the political parties of US presidents over time:

Model the process of tossing a coin repeatedly, using a discrete Markov process where the probability of getting heads is 0.6 and getting tails is 0.4:

Simulate 50 coin tosses: