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I'd like to plot histogram and density on the same plot. What I would like to add to the following is custom y-axis label which would be something like sprintf("[%s] %s", ..density.., ..count..) - two numbers at one tick value. Is it possible to obtain this with scale_y_continuous or do I need to work this around somehow?

Below current progress using scales::trans_new and sec_axis. sec_axis is kind of acceptable but the most desirable output is as on the image below.

set.seed(1) var <- rnorm(4000) binwidth <- 2 * IQR(var) / length(var) ^ (1 / 3) count_and_proportion_label <- function(x) { sprintf("%s [%.2f%%]", x, x/sum(x) * 100) } ggplot(data = data.frame(var = var), aes(x = var, y = ..count..)) + geom_histogram(binwidth = binwidth) + geom_density(aes(y = ..count.. * binwidth)) + scale_y_continuous( # this way trans = trans_new(name = "count_and_proportion", format = count_and_proportion_label, transform = function(x) x, inverse = function(x) x), # or this way sec.axis = sec_axis(trans = ~./sum(.), labels = percent, name = "proportion (in %)") )

I've tried to create object with breaks before basing on the graphics::hist output - but these two histogram differs.

bins <- (max(var) - min(var))/binwidth hdata <- hist(var, breaks = bins, right = FALSE) # hist generates different bins than `ggplot2`

At the end I would like to get something like this:

enter image description here

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2 Answers 2

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Would it be acceptable to add percentage as a secondary axis? E.g.

your_plot + scale_y_continuous(sec.axis = sec_axis(~.*2, name = "[%]"))

Perhaps it would be possible to overlay the secondary axis on the primary one, but I'm not sure how you would go about doing that.

Example plot

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3 Comments

Above doesn't solve issue, second scale still lacks information about density. It is still a ..count...
Sorry, you are right - you would have to change the scaling factor to convert from count to density. The relevant change would be ... sec_axis(~.*SCALE, ....
Yes, it is still a acceptable solution. I'm trying to do this with trans_new but formatter is applied at the end and it only gets final breaks.
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You can achieve your desired output by creating a custom set of labels, and adding it to the plot:

library(tidyverse) library(ggplot2) set.seed(1) var <- rnorm(400) bins <- .1 df <- data.frame(yvals = seq(0, 20, 5), labels = c("[0%]", "[10%]", "[20%]", "[30%]", "[40%]")) df <- df %>% tidyr::unite("custom_labels", labels, yvals, sep = " ", remove = TRUE) ggplot(data = data.frame(var = var), aes(x = var, y = ..count..)) + geom_histogram(aes(y = ..count..), binwidth = bins) + geom_density(aes(y = ..count.. * bins), color = "black", alpha = 0.7) + ylab("[density] count") + scale_y_continuous(breaks = seq(0, 20, 5), labels = df$custom_labels)

enter image description here

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I can't assume y breaks and y values before. I've tried by using graphics::hist before but I can't reproduce the same output as in ggplot2

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