I would like to add vertical segments to a ridgeline plot whose histograms show customized quantiles.
I managed to get the vertical segments if I map fill color with ..x..
. But I would like to show quantiles in the density plots. I wrote the following code:
library(datasets)
library(ggplot2)
data("iris")
iris_lines <- data.frame(Species = c("setosa", "versicolor", "virginica"),
x0 = c(5, 5.9, 6.5))
Figure1 <- ggplot(iris, aes(x=Sepal.Length, y=Species, fill=(..quantile..))) +
geom_density_ridges_gradient(jittered_points = FALSE, calc_ecdf = TRUE, quantile_lines = c(TRUE), quantiles =c(0.1,0.25,0.75,0.9),scale=0.9, color='white')+
geom_segment(data = iris_lines, aes(x = x0, xend = x0, y = as.numeric(Species), yend = as.numeric(Species) + c(.9,.5,.5)), color = "red") + scale_y_discrete(expand = c(0.01, 0))
Figure1
The code works if I map fill color as fill = ..x..
I get three vertical lines representing the mean of each density plot; however, if I map fill color as fill = ..quantile..
I get the following error:
Error in data.frame(..., check.names = FALSE) :
arguments imply differing number of rows: 1, 3
Nice chart!
Add inherit.aes = F
to the second geom so it doesn't try to match your data with the fill calculation in the ggplot(aes()
call.
Figure1 <- ggplot(iris, aes(x=Sepal.Length, y=Species, fill=(..quantile..))) +
geom_density_ridges_gradient(jittered_points = FALSE,
calc_ecdf = TRUE,
quantile_lines = c(TRUE),
quantiles =c(0.1,0.25,0.75,0.9),
scale=0.9, color='white') +
geom_segment(data = iris_lines,
aes(x = x0, xend = x0,
y = as.numeric(Species), yend = as.numeric(Species) + c(.9,.5,.5)),
color = "red", inherit.aes = F) + #### HERE ####
scale_y_discrete(expand = c(0.01, 0))
Figure1
Edit:
OP asked in comment about selectively labeling some elements and adding a label for the median line. Here's an approach, probably not the pithiest.
Figure1 <- ggplot(iris, aes(x=Sepal.Length, y=Species,
fill = (..quantile..),
color = (..quantile..))) +
geom_density_ridges_gradient(jittered_points = FALSE,
calc_ecdf = TRUE,
quantile_lines = c(TRUE),
quantiles =c(0.1,0.25,0.75,0.9),
scale=0.9, color='white') +
geom_segment(data = iris_lines,
aes(x = x0, xend = x0, fill = "median",
y = as.numeric(Species),
yend = as.numeric(Species) + c(.9,.5,.5),
color = "median")) + #### HERE ####
scale_y_discrete(expand = c(0.01, 0)) +
scale_color_manual(name = "quantile",
limits = c(1:3, "median"),
values = alpha("firebrick1", c(0, 0, 0, 1)),
labels = c("<10%", "10-25%", "IQR", "median")) +
scale_fill_manual(name = "quantile",
limits = c(1:3, "median"),
values = c("cadetblue", "coral", "orange", "white"),
na.value = "gray30",
labels = c("<10%", "10-25%", "IQR", "median"))
Figure1