How to Display the Median Value in a Boxplot in Ggplot

Add median value for each boxplot

Problem is that you calculate median for all key's (the number you get 2131 when you use median(value)). You can use group_by to group records by key and only then calculate median (summarise function from dplyr package):

library(tidyverse)
dataInput  <- gather(df, key, value, -Chr, -Start, -End, -Name)
dataMedian <- summarise(group_by(dataInput, key), MD = median(value))
ggplot(dataInput, aes(key, value)) +
    geom_boxplot() + 
    geom_text(data = dataMedian, aes(key, MD, label = MD), 
              position = position_dodge(width = 0.8), size = 3, vjust = -0.5)

R: Displaying mean and median labels on boxplot ggplot

Looks like the problem is that when you calculate the mean and median values by both "Unit" and "Quarter" the variable the used to be called "Days" is in now called "x". So simply update your geom_text commands to reflect this.

ggplot(data = dset, aes(x = Quarter, y = Days, fill = Quarter))  +
  geom_boxplot(outlier.shape = NA) + 
  facet_grid(. ~ Unit) + # adding another dimension
  coord_cartesian(ylim = c(10, 60)) + #sets the y-axis limits
  stat_summary(fun.y=mean, geom="point", shape=20, size=3, color="red", fill="red") + #adds average dot
  geom_text(data = means, aes(label = round(x, 1), y = x + 1), size = 3) + #adds average labels
  geom_text(data = medians, aes(label = round(x, 1), y = x - 0.5), size = 3) + #adds median labels
  xlab(" ") +
  ylab("Days") +
  ggtitle("Days") +
  theme(legend.position = 'none')

Mean and median in r boxplot

You can create the summary statistics beforehand and pass them through to geom_boxplot using stat = 'identity'

library(tidyverse)

div %>%
  mutate(season = factor(season, level_order)) %>%
  group_by(season, site) %>%
  summarize(ymin = quantile(shannon, 0),
            lower = quantile(shannon, 0.25),
            median = median(shannon),
            mean = mean(shannon),
            upper = quantile(shannon, 0.75),
            ymax = quantile(shannon, 1)) %>%
  ggplot(aes(x = season, fill = site)) + 
  geom_boxplot(stat = 'identity', 
               aes(ymin = ymin, lower = lower, middle = mean, upper = upper,
                   ymax = ymax)) +  
  geom_point(aes(y = median, group = site), 
             position = position_dodge(width = 0.9)) +
  xlab("season") + 
  ylab("Shannon index")

How to display the median value in a faceted boxplot in ggplot?

Your question is full of syntax errors and references to variables and objects that don't exist.

If you want median values for each boxplot when the plots are faceted, then you need to ensure that the faceting variables exist in the data.frame (or calling environment) used each call to geom_....

A simple, reproducible example

set.seed(1)
library(plyr)
DF <- data.frame(TYPE = sample(letters[1:3], 500, replace = TRUE), 
  PROVIDER = letters[1:5], VALUE = rnorm(500))

# get the medians by type and provider (both columns
# will exist in the new data.frame

meds <- ddply(DF, .(TYPE, PROVIDER), summarize, med = median(VALUE))

ggplot(DF, aes(x=PROVIDER,y=  VALUE)) + 
   geom_boxplot() + facet_wrap(~TYPE) + 
   geom_text(data = meds, aes(y = med, label = round(med,2)),size = 3, vjust = -0.5)

Showing median value in grouped boxplot in R

library(dplyr)
dims=dims%>%
  group_by(Blog,Region)%>%
  mutate(med=median(Dim1))
plotgraph <- function(x, y, colour, min, max)
{
  plot1 <- ggplot(dims, aes(x = x, y = y, fill = Region)) +
    geom_boxplot()+
    labs(color='Region') + 
    geom_hline(yintercept = 0, alpha = 0.4)+
    scale_y_continuous(breaks=c(seq(min,max,5)), limits = c(min, max))+
    labs(x="Blog Type", y="Dimension Score") + scale_fill_grey(start = 0.3, end = 0.7) + 
    theme_grey()+
    theme(legend.justification = c(1, 1), legend.position = c(1, 1))+
    geom_text(aes(y = med,x=x, label = round(med,2)),position=position_dodge(width = 0.8),size = 3, vjust = -0.5,colour="blue")
  return(plot1)
}
plot1 <- plotgraph (Blog, Dim1, Region, -30, 25)

Which gives (the text colour can be tweaked to something less tacky):


Note: You should consider using non-standard evaluation in your function rather than having it require the use of attach()

Edit:
One liner, not as clean I wanted it to be since I ran into problems with dplyr not properly aggregating the data even though it says the grouping was performed.
This function assume the dataframe is always called dims

library(ggplot2)
library(reshape2)
plotgraph <- function(x, y, colour, min, max)
{
  plot1 <- ggplot(dims, aes_string(x = x, y = y, fill = colour)) +
    geom_boxplot()+
    labs(color=colour) + 
    geom_hline(yintercept = 0, alpha = 0.4)+
    scale_y_continuous(breaks=c(seq(min,max,5)), limits = c(min, max))+
    labs(x="Blog Type", y="Dimension Score") +
    scale_fill_grey(start = 0.3, end = 0.7) + 
    theme_grey()+
    theme(legend.justification = c(1, 1), legend.position = c(1, 1))+
    geom_text(data= melt(with(dims, tapply(eval(parse(text=y)),list(eval(parse(text=x)),eval(parse(text=colour))), median)),varnames=c("Blog","Region"),value.name="med"),
              aes_string(y = "med",x=x, label = "med"),position=position_dodge(width = 0.8),size = 3, vjust = -0.5,colour="blue")
  return(plot1)
}
plot1 <- plotgraph ("Blog", "Dim1", "Region", -30, 25)

How to print mean, median and sd on boxplots in ggplot?

You'll first need to calculate the summary statistics:

library(dplyr)

summ <- mpg %>% 
  group_by(class) %>% 
  summarize(mean = mean(cty), median = median(cty), sd = sd(cty))

Then use that data frame in your geom_label call.

ggplot(mpg, aes(x = class, y = cty)) + geom_boxplot() + 
  geom_label(data = summ, aes(x = class, y = mean, 
    label = paste("Mean: ", round(mean, 1), "\nMedian: ", median, "\nSD: ", round(sd, 1))))

Not a good looking chart, but you just need to play around with the size and colours to pretty it up, or maybe use geom_text instead of geom_label.

How to connect the median values of a boxplot with multiple groups using lines in ggplot2?

For this, you should specify the position parameters explicitly. geom_boxplot defaults to position_dodge, but you have to specify it for the line.

ggplot(airquality, aes(x = Month, y = Ozone, fill = Day)) +
  geom_boxplot(position = position_dodge(width = 0.9)) +
  stat_summary(
    fun.y = median,
    geom = 'line',
    aes(group = Day, colour = Day),
    position = position_dodge(width = 0.9) #this has to be added
  )

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