![]() There’s a strand of the data viz world that argues that everything could be a bar chart. As we will see, there are many more choices to make when drawing histograms. An analyst can choose the ordering of the categories, the color of the bars, and the aspect ratio. The categories for painting elements are discrete choices, so Walt Hickey (the author of the chart) counted how many paintings contained each element and displayed the counts.īecause of their discrete nature, there's not much to decide when drawing a bar chart. For example, fivethirtyeight created the bar chart at right to show the features of Bob Ross paintings. Bar charts show how many items are counted in each of a set of categories. ![]() To visualize the distribution of one categorical variable, we use what is called a bar chart (or bar graph). For example, gender is a common categorical variable, perhaps with categories "male," "female," and "gender non-conforming." Categorical variables and their distributionsĬategorical variables take on only a few specific values. The way you visualize a distribution depends on whether the variable of interest is categorical or numeric. ![]() In this essay, we are focusing on distributions of a single variable. Since visualizations rely on humans to make and interpret them, they can be fraught with possibilities for misrepresentation, including perceptual issues and problems with axes. When thinking about data, it is often useful to produce visualizations to better understand distributions and relationships between variables.
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