Does the function work for other geom's as well? about ggrepel

[slowkow]

Thanks for the question! Please post a minimal code example and a figure.

[frajuegies]

Hi,
first of all... my example works, but it does not completely avoid overplotting.
Here is the code

averages <- aggregate(diamonds$price, list(diamonds$cut), mean)
colnames(averages) <- c("CUT_1","PRICE_1")
graph <- ggplot (averages)
graph <- graph + geom_vline(data=averages, aes(xintercept=PRICE_1, color = CUT_1))
graph <- graph + geom_text_repel (data=averages, aes(x=PRICE_1,y=Inf,label=paste ("mean = ",signif(PRICE_1,digits=4),sep=""),color = CUT_1),
size=6)

graph <- graph + geom_histogram(data= diamonds, aes(price, fill = cut),binwidth=10)

plot (graph)

The plot is attached as png.

Thank you for your effort making this package !
Best regards,
Jürgen

[slowkow]

How's this?

library(ggplot2)
library(ggrepel)

averages <- aggregate(diamonds$price, list(diamonds$cut), mean)
colnames(averages) <- c("CUT_1","PRICE_1")

ggplot(averages) +
  geom_vline(data=averages, aes(xintercept=PRICE_1, color = CUT_1)) +
  geom_histogram(data= diamonds, aes(price, fill = cut),binwidth=10) +
  geom_text_repel(
    data=averages,
    aes(
      x = PRICE_1,
      y = 350,
      label=paste("mean = ",signif(PRICE_1,digits=4),sep=""),
      color = CUT_1
    ),
    size=6
  )

[frajuegies]

Thank you very much....that Is a nice approach, but the position in y direction is changing with every new plot,..... The plots are defined within a shiny app....

[slowkow]

Ok, I searched Google for tips about this and found this StackOverflow post:

• https://stackoverflow.com/questions/14584093/ggplot2-find-number-of-counts-in-histogram-maximum

Based on that post, I came up with the following solution:

library(ggplot2)
library(ggrepel)

averages <- aggregate(diamonds$price, list(diamonds$cut), mean)
colnames(averages) <- c("CUT_1","PRICE_1")

p <- ggplot(averages) +
  geom_vline(data=averages, aes(xintercept=PRICE_1, color = CUT_1)) +
  geom_histogram(data= diamonds, aes(price, fill = cut),binwidth=10)

x <- ggplot_build(p)$data
p + geom_text_repel(
    data=averages,
    aes(
      x = PRICE_1,
      # Place the text at 90% of the maximum y value in the plot.
      y = max(x[[2]]$y) * 0.9,
      label=paste("mean = ",signif(PRICE_1,digits=4),sep=""),
      color = CUT_1
    ),
    size=6
  )

[frajuegies]

Thank you very much.... I was not at my desk to search the hint myself and you are reacting really fast .....
. Sorry for that
Best regards, Jürgen

[slowkow]

Thanks for the interesting use case! Feel free to re-open or make a new issue if needed.