Comparison of various ggplot2 geoms for visualizing distributions

plot_dist.R

library(ggplot2)
library(cowplot)  # For better ggplot2 theme
library(ggbeeswarm)  # For geom_quasirandom()

set.seed(1)

data <- data.frame(value = c(rnorm(100, -1.8), rnorm(100, 1.8)))

extra <- list(scale_x_discrete(labels = NULL, name = NULL),
              scale_y_continuous(name = NULL))

base <- ggplot(data, aes("example", value))
p1 <- base + geom_boxplot(fill = "grey90") + extra + ggtitle("geom_boxplot")
p2 <- base + geom_jitter(size = 1) + extra + ggtitle("geom_jitter")
p3 <- base + geom_quasirandom(size = 1) + extra + ggtitle("geom_quasirandom")

p4 <- base + geom_violin(fill = "grey90") + extra + ggtitle("geom_violin")
p5 <- p4 + geom_boxplot(width = 0.1) + ggtitle("geom_violin +\ngeom_boxplot")
p6 <- p4 + geom_quasirandom(size = 1) + ggtitle("geom_violin +\ngeom_quasirandom")

plot_grid(p1, p2, p3, p4, p5, p6, nrow = 1, align = "h")

ggsave("~/Desktop/plot_dist.png", width = 13, height = 7, dpi = 150)