r - Plotting normal curve over histogram using ggplot2: Code produces straight line at 0

Question

this forum already helped me a lot for producing the code, which I expected to return a histogram of a specific variable overlayed with its empirical normal curve. I used ggplot2 and stat_function to write the code. Unfortunately, the code produced a plot with the correct histogram but the normal curve is a straight line at zero (red line in plot produced by the following code).

For this minimal example I used the mtcars dataset - the same behavior of ggplot and stat_function is observed with my original data set.

This is the code is wrote and used:

library(ggplot2)
mtcars
hist_staff <- ggplot(mtcars, aes(x = mtcars$mpg)) + 
  geom_histogram(binwidth = 2, colour = "black", aes(fill = ..count..)) +
  scale_fill_gradient("Count", low = "#DCDCDC", high = "#7C7C7C") +
  stat_function(fun = dnorm, colour = "red")
print(hist_staff)

I also tried to specify dnorm:

stat_function(fun = dnorm(mtcars$mpg, mean = mean(mtcars$mpg), sd = sd(mtcars$mpg))

That did not work out either - an error message returned stating that the arguments are not numerical.

I hope you people can help me! Thanks a lot in advance!

Best, Jannik

Answer 1

Your curve and histograms are on different y scales and you didn't check the help page on stat_function, otherwise you'd've put the arguments in a list as it clearly shows in the example. You also aren't doing the aes right in your initial ggplot call. I sincerely suggest hitting up more tutorials and books (or at a minimum the help pages) vs learn ggplot piecemeal on SO.

Once you fix the stat_function arg problem and the ggplot``aes issue, you need to tackle the y axis scale difference. To do that, you'll need to switch the y for the histogram to use the density from the underlying stat_bin calculated data frame:

library(ggplot2)

gg <- ggplot(mtcars, aes(x=mpg))
gg <- gg + geom_histogram(binwidth=2, colour="black", 
                          aes(y=..density.., fill=..count..))
gg <- gg + scale_fill_gradient("Count", low="#DCDCDC", high="#7C7C7C")
gg <- gg + stat_function(fun=dnorm,
                         color="red",
                         args=list(mean=mean(mtcars$mpg), 
                                  sd=sd(mtcars$mpg)))

gg