Plotting two densities with vertical lines and correct legend - r

Question

I want to draw two densities with two vertical lines for the averages.
The legend is once to denote the densities and once the vertical
lines.
I tried the code below. However, only one legend appears and the labeling is wrong.
Can anyone help me?
set.seed(1234)
data <- data.frame(value = rnorm(n = 10000, mean = 50, sd = 20),
type = sample(letters[1:2], size = 10000, replace = TRUE))
data$value[data$type == "b"] <- data$value[data$type == "b"] + 50
mean.a <- mean(data$value[data$type == "a"])
mean.b <- mean(data$value[data$type == "b"])
library(ggplot2)
gp <- ggplot(data = data, aes(x = value))
gp <- gp + geom_density(aes(fill = type), color = "black", alpha=0.3, lwd = 1.0, show.legend = TRUE)
gp <- gp + scale_fill_manual(breaks = 1:2, name = "Density", values = c("a" = "green", "b" = "blue"), labels = c("a" = "Density a", "b" = "Density b") )
gp <- gp + geom_vline(aes(color="mean.a", xintercept=mean.a), linetype="solid", size=1.0, show.legend = NA)
gp <- gp + geom_vline(aes(color="mean.b", xintercept=mean.b), linetype="dashed", size=1.0, show.legend = NA)
gp <- gp + scale_color_manual(name = "", values = c("mean.a" = "red", "mean.b" = "darkblue"), labels = c("mean.a" = "Mean.A", "mean.b" = "Mean.B"))
gp <- gp + theme(legend.position="top")
gp

Answer 1

Here are a couple ways to do it. I'm not sure, but I think some of the difficulty comes from having more than one geom_vline and trying to hard-code values in the aes. You're building three scales here: fill for the density curves, and color and linetype for the vertical lines. But you're aiming (correct me if I'm misreading) for two legends.
The easiest way to deal with getting the proper legends is to make a small data frame for the means, rather than individual values for each mean. You can do this easily with dplyr to calculate means for each type.
library(tidyverse)
set.seed(1234)
data <- data.frame(value = rnorm(n = 10000, mean = 50, sd = 20),
type = sample(letters[1:2], size = 10000, replace = TRUE))
data$value[data$type == "b"] <- data$value[data$type == "b"] + 50
means <- group_by(data, type) %>%
summarise(mean = mean(value))
means
#> # A tibble: 2 x 2
#> type mean
#> <fct> <dbl>
#> 1 a 50.3
#> 2 b 99.9
Then when you plot, you can make a single geom_vline call, assigning the means data frame and allowing the aesthetics you want—color and linetype—to be scaled based on this data. The trick then is reconciling the names and labels: if you don't set the same legend name and labels for both the color and linetype scales, you'll have two legends for the lines. Set them the same, and you get a single legend for the mean lines.
ggplot(data, aes(x = value)) +
geom_density(aes(fill = type), alpha = 0.3) +
geom_vline(aes(xintercept = mean, color = type, linetype = type), data = means) +
scale_color_manual(values = c("red", "darkblue"), labels = c("Mean.A", "Mean.B"), name = NULL) +
scale_linetype_discrete(labels = c("Mean.A", "Mean.B"), name = NULL) +
scale_fill_manual(values = c(a = "green", b = "blue"), name = "Density")
The second way is to just add a step to creating the means data frame where you label the types the way you want later, i.e. "Mean.A" instead of just "a". Then you don't need to adjust labels, and you can skip the linetype scale—unless you want to change linetypes manually—and then just remove the name for that legend for both color and linetype in your labs.
means2 <- group_by(data, type) %>%
summarise(mean = mean(value)) %>%
mutate(type = paste("Mean", str_to_upper(type), sep = "."))
means2
#> # A tibble: 2 x 2
#> type mean
#> <chr> <dbl>
#> 1 Mean.A 50.3
#> 2 Mean.B 99.9
ggplot(data, aes(x = value)) +
geom_density(aes(fill = type), alpha = 0.3) +
geom_vline(aes(xintercept = mean, color = type, linetype = type), data = means2) +
scale_color_manual(values = c(Mean.A = "red", Mean.B = "darkblue")) +
scale_fill_manual(values = c(a = "green", b = "blue"), name = "Density") +
labs(color = NULL, linetype = NULL)
Created on 2018-06-05 by the reprex package (v0.2.0).