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Fitting a curve to a ggplot histogram

I know that I can fit the density curve to my histogram in ggplot as follows.

df = data.frame(x=rnorm(100))
ggplot(df, aes(x=x, y=..density..)) + geom_histogram() + geom_density()

histogram

However, I want my yaxis to be frequency (counts) instead of density and keep a curve that matches the distribution. How to do it?

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Depending on your goals, something like this might work by simply scaling the density curve using multiplication:

ggplot(df, aes(x=x)) + geom_histogram() + geom_density(aes(y=..density..*10))

or

ggplot(df, aes(x=x)) + geom_histogram() + geom_density(aes(y=..count../10))

Choose other values ​​(instead of 10) if you want to scale things differently.



Edit:

Since you are defining your scale factor in the global environment, you can define it in aes

:

ggplot(df, aes(x=x)) + geom_histogram() + geom_density(aes(n=n, y=..density..*n)) 
# or
ggplot(df, aes(x=x, n=n)) + geom_histogram() + geom_density(aes(y=..density..*n))

or another less pleasant way using get

:

ggplot(df, aes(x=x)) + 
  geom_histogram() + 
  geom_density(aes(y=..density.. * get("n", pos = .GlobalEnv)))
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