微软Edx R数据科学MOOC中ggplot的..density..语法含义咨询

Great question—those double-dot wrapped variables can feel confusing at first, especially since they’re different from the ... parameter placeholders you’ve seen elsewhere. Let’s break this down clearly:

What Are ..variable.. Tokens? #

• These are computed variables (sometimes called "stat variables") that ggplot2 generates internally when rendering statistical layers like histograms or density plots. The double dots are a deliberate syntax to distinguish them from columns in your original data frame.
• Unlike the ... used in function parameters (which act as a placeholder for variable-length arguments), these double-dot names refer to values calculated on-the-fly by ggplot’s statistical transformations.

What Does ..density.. Specifically Do? #

• For geom_histogram() (which uses stat_bin() under the hood), ..density.. represents the probability density of each bin. By default, geom_histogram uses ..count.. (the number of observations in each bin) for the y-axis.
• Setting y=..density.. scales the histogram’s height so that the total area under the histogram equals 1. This matches the scale of the density curve created by geom_density(), letting you overlay both elements on the same plot with aligned axes—critical for comparing the shape of your distribution.

Breaking Down Your Code #

Looking at your plot definition:

p = ggplot(df, aes_string(col)) + 
  geom_histogram(binwidth = bw, aes(y=..density..), alpha = 0.5) + 
  geom_density(aes(y=..density..), color = 'blue') + 
  geom_rug() + 
  facet_grid(. ~ drive.wheels)

• The geom_histogram uses y=..density.. to swap from count-based height to density-based height.
• The geom_density explicitly uses y=..density.. (though it defaults to this, writing it out makes your code more readable).
• This alignment lets you easily compare how well the smooth density curve fits the binned histogram data, split by the drive.wheels category via facet_grid.

Finding Other Computed Variables #

If you’re curious about other values you can access this way, check the documentation for the underlying stat function:

• For histograms, look at ?stat_bin—it lists variables like ..count.., ..freq.., ..density.., and ..width...
• For density plots, ?stat_density will show its available computed variables.

内容的提问来源于stack exchange，提问作者user2193946