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If we assign variable names (e.g., , , etc) to visual properties (e.g., , , , etc) within , as done in Figure 2.1, it tries to find a sensible geometric representation of that information for us. Shortly we'll cover how to specify these geometric representations (as well as other visual encodings) to create different kinds of charts... The function has numerous arguments that are unique to the R package (e.g., , , , , , etc) and make it easier to encode data variables (e.g., diamond clarity) as visual properties (e.g., color). By default, these arguments map values of a data variable to a visual range defined by the plural form of the argument. For example, in the bottom panel of 2.1, is used to map each level of diamond clarity to a different color, then is used to specify the range of colors (which, in this case, the color palette from the RColorBrewer package, but one can also supply custom color codes or a color palette function like ). Figure 2.2 provides a visual diagram of how..

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