ggplot split violin plot with horizontal mean lines - r

Question

I've created these split half violin plots using ggplot.
However, instead of including the boxplot, which shows the median, I'd like to include a horizontal line with the mean.
This means each colored half would have its own mean line: the gold half would have a mean line which would not exactly align with the mean line on the grey half. Importantly, I'd like the mean line to reside only inside the density plot.
How can I achieve this? I can't figure it out and I'd appreciate any help!
Here's some example data:
set.seed(20160229)
my_data = data.frame(
y=c(rnorm(1000), rnorm(1000, 0.5), rnorm(1000, 1), rnorm(1000,
1.5)),
x=c(rep('a', 2000), rep('b', 2000)),
m=c(rep('i', 1000), rep('j', 2000), rep('i', 1000))
)
Here's the extension for geom_violin to create split_geom_violin:
GeomSplitViolin <- ggproto("GeomSplitViolin", GeomViolin, draw_group = function(self, data, ..., draw_quantiles = NULL){
data <- transform(data, xminv = x - violinwidth * (x - xmin), xmaxv = x + violinwidth * (xmax - x))
grp <- data[1,'group']
newdata <- plyr::arrange(transform(data, x = if(grp%%2==1) xminv else xmaxv), if(grp%%2==1) y else -y)
newdata <- rbind(newdata[1, ], newdata, newdata[nrow(newdata), ], newdata[1, ])
newdata[c(1,nrow(newdata)-1,nrow(newdata)), 'x'] <- round(newdata[1, 'x'])
if (length(draw_quantiles) > 0 & !scales::zero_range(range(data$y))) {
stopifnot(all(draw_quantiles >= 0), all(draw_quantiles <=
1))
quantiles <- ggplot2:::create_quantile_segment_frame(data, draw_quantiles)
aesthetics <- data[rep(1, nrow(quantiles)), setdiff(names(data), c("x", "y")), drop = FALSE]
aesthetics$alpha <- rep(1, nrow(quantiles))
both <- cbind(quantiles, aesthetics)
quantile_grob <- GeomPath$draw_panel(both, ...)
ggplot2:::ggname("geom_split_violin", grid::grobTree(GeomPolygon$draw_panel(newdata, ...), quantile_grob))
}
else {
ggplot2:::ggname("geom_split_violin", GeomPolygon$draw_panel(newdata, ...))
}
})
geom_split_violin <- function (mapping = NULL, data = NULL, stat = "ydensity", position = "identity", ..., draw_quantiles = NULL, trim = TRUE, scale = "area", na.rm = FALSE, show.legend = NA, inherit.aes = TRUE) {
layer(data = data, mapping = mapping, stat = stat, geom = GeomSplitViolin, position = position, show.legend = show.legend, inherit.aes = inherit.aes, params = list(trim = trim, scale = scale, draw_quantiles = draw_quantiles, na.rm = na.rm, ...))
}
Here's the code for the graph:
library(ggplot2)
ggplot(my_data, aes(x, y, fill=m)) +
geom_split_violin(trim = TRUE) +
geom_boxplot(width = 0.25, notch = FALSE, notchwidth = .4, outlier.shape = NA, coef=0) +
labs(x=NULL,y="GM Attitude Score") +
theme_classic() +
theme(text = element_text(size = 20)) +
scale_x_discrete(labels=c("0" = "Control\nCondition", "1" = "GM\nCondition")) +
scale_fill_manual(values=c("#E69F00", "#999999"),
name="Survey\nPart",
breaks=c("1", "2"),
labels=c("Time 1", "Time 5"))

Answer 1

You can use stat_summary & geom_crossbar while setting all fun.y, fun.ymin & fun.ymax to mean only
library(ggplot2)
ggplot(my_data, aes(x, y, fill = m)) +
geom_split_violin(trim = TRUE) +
stat_summary(fun.y = mean, fun.ymin = mean, fun.ymax = mean,
geom = "crossbar",
width = 0.25,
position = position_dodge(width = .25),
) +
labs(x = NULL, y = "GM Attitude Score") +
theme_classic() +
theme(text = element_text(size = 20)) +
scale_x_discrete(labels = c("0" = "Control\nCondition", "1" = "GM\nCondition")) +
scale_fill_manual(
values = c("#E69F00", "#999999"),
name = "Survey\nPart",
breaks = c("1", "2"),
labels = c("Time 1", "Time 5")
)
Data & function used:
set.seed(20160229)
my_data <- data.frame(
y = c(rnorm(1000), rnorm(1000, 0.5), rnorm(1000, 1), rnorm(1000, 1.5)),
x = c(rep("a", 2000), rep("b", 2000)),
m = c(rep("i", 1000), rep("j", 2000), rep("i", 1000))
)
GeomSplitViolin <- ggproto(
"GeomSplitViolin",
GeomViolin,
draw_group = function(self, data, ..., draw_quantiles = NULL) {
data <- transform(data,
xminv = x - violinwidth * (x - xmin),
xmaxv = x + violinwidth * (xmax - x)
)
grp <- data[1, "group"]
newdata <- plyr::arrange(
transform(data, x = if (grp %% 2 == 1) xminv else xmaxv),
if (grp %% 2 == 1) y else -y
)
newdata <- rbind(newdata[1, ], newdata, newdata[nrow(newdata), ], newdata[1, ])
newdata[c(1, nrow(newdata) - 1, nrow(newdata)), "x"] <- round(newdata[1, "x"])
if (length(draw_quantiles) > 0 & !scales::zero_range(range(data$y))) {
stopifnot(all(draw_quantiles >= 0), all(draw_quantiles <= 1))
quantiles <- ggplot2:::create_quantile_segment_frame(data, draw_quantiles)
aesthetics <- data[rep(1, nrow(quantiles)), setdiff(names(data), c("x", "y")), drop = FALSE]
aesthetics$alpha <- rep(1, nrow(quantiles))
both <- cbind(quantiles, aesthetics)
quantile_grob <- GeomPath$draw_panel(both, ...)
ggplot2:::ggname(
"geom_split_violin",
grid::grobTree(GeomPolygon$draw_panel(newdata, ...), quantile_grob)
)
} else {
ggplot2:::ggname("geom_split_violin", GeomPolygon$draw_panel(newdata, ...))
}
}
)
geom_split_violin <- function(mapping = NULL,
data = NULL,
stat = "ydensity",
position = "identity", ...,
draw_quantiles = NULL,
trim = TRUE,
scale = "area",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE) {
layer(
data = data,
mapping = mapping,
stat = stat,
geom = GeomSplitViolin,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
trim = trim,
scale = scale,
draw_quantiles = draw_quantiles,
na.rm = na.rm, ...
)
)
}
Created on 2018-07-08 by the reprex package (v0.2.0.9000).