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The distribution of a category variable is displayed using pie charts and bar graphs. Any set of quantities measured in the same units can be compared using bar graphs. It's a good idea to ask yourself, "What do I see?" when looking at any graph.

A bar graph is used to more vividly depict the distribution of a category variable. Each category is represented by a bar. The category count or percentage is represented by the height of the bar. The following is a bar graph of the supplied data:

Looking at the bar graph, we can see that as people get older, the percentage of persons who have seen a movie in the last $12$months decreases. We can deduce that as people get older, their interest in movies decreases.
As a result, older people seem to go to the movies less than younger people.

The pie chart is used to show the distribution of categorical variables as a "pie" with slices scaled by the categories' counts or percent. A pie chart must include all of the categories that make up the whole, which is not the case with the data provided. Furthermore, because each percentage in the table corresponds to a different age group rather than sections of a single total, a pie chart of these data would be incorrect. As a result, making a pie chart using these data would be incorrect.

Because each percentage in the table relates to a different percentage group, not portions of a single whole, the data does not answer the question if a movie studio wants to know what percent of the whole audience for movies is $18$ to $24$ years old. It is impossible to calculate the overall number of audience members for a film that is aimed at people aged $18$ to $24$, because it only gives the percentage of that age group's attendance, not the total audience. As a result, calculating the total number of audience members aged $18$ to $24$ is impossible.