Position scales for discrete data
scale_x_discrete(..., expand = waiver(), guide = waiver(), position = "bottom") scale_y_discrete(..., expand = waiver(), guide = waiver(), position = "left")
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Arguments passed on to
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expand |
For position scales, a vector of range expansion constants used to add some
padding around the data to ensure that they are placed some distance
away from the axes. Use the convenience function |
guide |
A function used to create a guide or its name. See
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position |
For position scales, The position of the axis.
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You can use continuous positions even with a discrete position scale - this allows you (e.g.) to place labels between bars in a bar chart. Continuous positions are numeric values starting at one for the first level, and increasing by one for each level (i.e. the labels are placed at integer positions). This is what allows jittering to work.
Other position scales:
scale_x_binned()
,
scale_x_continuous()
,
scale_x_date()
ggplot(diamonds, aes(cut)) + geom_bar() # The discrete position scale is added automatically whenever you # have a discrete position. (d <- ggplot(subset(diamonds, carat > 1), aes(cut, clarity)) + geom_jitter()) d + scale_x_discrete("Cut") d + scale_x_discrete("Cut", labels = c("Fair" = "F","Good" = "G", "Very Good" = "VG","Perfect" = "P","Ideal" = "I")) # Use limits to adjust the which levels (and in what order) # are displayed d + scale_x_discrete(limits = c("Fair","Ideal")) # you can also use the short hand functions xlim and ylim d + xlim("Fair","Ideal", "Good") d + ylim("I1", "IF") # See ?reorder to reorder based on the values of another variable ggplot(mpg, aes(manufacturer, cty)) + geom_point() ggplot(mpg, aes(reorder(manufacturer, cty), cty)) + geom_point() ggplot(mpg, aes(reorder(manufacturer, displ), cty)) + geom_point() # Use abbreviate as a formatter to reduce long names ggplot(mpg, aes(reorder(manufacturer, displ), cty)) + geom_point() + scale_x_discrete(labels = abbreviate)
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