I want my plot to display how many people/observations are within each group. How can I do this? I found this answer, however I had a hard time following it.
Modify x-axis labels in each facet
Raincloud <- iris %>%
dplyr::group_by(Species) %>%
dplyr::mutate(mean = mean(Petal.Length),
se = sd(Petal.Length)/sqrt(length(Petal.Length))) %>%
ungroup() %>%
ggplot(aes(x=Petal.Length, y=Species)) +
stat_slab(aes(fill = Species, )) +
stat_dots(aes(color = Species), side = "bottom", shape = 16) +
scale_fill_brewer(palette = "Set1", aesthetics = c("fill", "color")) +
geom_errorbar(aes(xmin = mean - 1.96 * se,
xmax = mean + 1.96 * se), width = 0.2) +
stat_summary(fun=mean, geom="point", shape=16, size=3.0) +
theme_bw(base_size = 10) +
theme(legend.position = "top")+
labs(title="Raincloud plot with ggdist")
print(Raincloud + labs(x = "Petal Length")) [![Result[1]][1]
RCsex <- uniquePeople %>%
dplyr::group_by(sex) %>%
dplyr::mutate(mean = mean(thresh.x),
se = sd(thresh.x)/sqrt(length(thresh.x))) %>%
ungroup() %>%
ggplot(aes(x=thresh.x, y=sex)) +
stat_slab(aes(fill = sex), scale = 0.5) +
stat_dots(aes(color = sex), side = "bottom", shape = 16) +
scale_fill_brewer(palette = "Set1", aesthetics = c("fill", "color")) +
geom_errorbar(aes(xmin = mean - 1.96 * se,
xmax = mean + 1.96 * se), width = 0.2) +
stat_summary(fun=mean, geom="point", shape=16, size=3.0) +
theme_bw(base_size = 10) +
theme(legend.position = "top")+
scale_x_continuous(name="Estimated Nominal Detection Threshold (log10 units)", limits=c(-4.5, 0.5),
breaks = seq(-4.5, 0.5, by = 0.5))+
labs(title="Raincloud plots showing odor detection thresholds stratified by sex")
print(RCsex + labs(y = "Sex"))
>Solution :
One option would be to add a new column to your dataset where you glue the number obs. per species to the species name. This column could then be mapped on y:
library(dplyr)
library(ggplot2)
library(ggdist)
iris %>%
dplyr::group_by(Species) %>%
dplyr::mutate(
mean = mean(Petal.Length),
se = sd(Petal.Length) / sqrt(length(Petal.Length)),
species_y = paste0(Species, "\n(", n(), ")")
) %>%
ungroup() %>%
ggplot(aes(x = Petal.Length, y = species_y)) +
stat_slab(aes(fill = Species)) +
stat_dots(aes(color = Species), side = "bottom", shape = 16) +
scale_fill_brewer(palette = "Set1", aesthetics = c("fill", "color")) +
geom_errorbar(aes(
xmin = mean - 1.96 * se,
xmax = mean + 1.96 * se
), width = 0.2) +
stat_summary(fun = mean, geom = "point", shape = 16, size = 3.0) +
theme_bw(base_size = 10) +
theme(legend.position = "top") +
labs(title = "Raincloud plot with ggdist", x = "Petal Length")
