These include the variables Gender (which has values 0=male, 1=female), Athlete (which has values 0=non-athlete, 1=athlete), and Smoking (which has values 0=nonsmoker, 1=past smoker, 2=current smoker).
Let's create formats for each of these sets of labels.
This can either be done temporarily, by adding the labels during a PROC step, or be done permanently, by applying the labels in a data step.
Our sample dataset has several categorical variables that, without formats, are hard to look at and know what the value represents.
All observations would have a value of 1 for factype2.