R: ggplot2, how to annotate summary statistics on each panel of a panel plot

Question

How would I add a text annotation (eg. sd = sd_value) of the standard deviation in each panel of the following plot using ggplot2 in R?

library(datasets)
data(mtcars)
ggplot(data = mtcars, aes(x = hp)) + 
        geom_dotplot(binwidth = 1) + 
        geom_density() + 
        facet_grid(. ~ cyl) + 
        theme_bw()

I'd post an image of the plot, but I don't have enough rep.

I think "geom_text" or "annotate" might be useful but I'm not sure quite sure how.

Answer 1

If you want to vary the text label in each facet, you will want to use geom_text. If you want the same text to appear in each facet, you can use annotate.

p <- ggplot(data = mtcars, aes(x = hp)) + 
  geom_dotplot(binwidth = 1) + 
  geom_density() + 
  facet_grid(. ~ cyl)

mylabels <- data.frame(cyl = c(4, 6, 8), 
                       label = c("first label", "seond label different", "and another"))

p + geom_text(x = 200, y = 0.75, aes(label = label), data = my labels)

### compare that to this way with annotate

p + annotate("text", x = 200, y = 0.75, label = "same label everywhere")

Now, if you really want standard deviation by cyl in this example, I'd probably use dplyr to do the calculation first and then complete this with geom_text like so:

library(ggplot2)
library(dplyr)

df.sd.hp <- mtcars %>%
  group_by(cyl) %>%
  summarise(hp.sd = round(sd(hp), 2))

ggplot(data = mtcars, aes(x = hp)) + 
  geom_dotplot(binwidth = 1) + 
  geom_density() + 
  facet_grid(. ~ cyl) +
  geom_text(x = 200, y = 0.75, 
            aes(label = paste0("SD: ", hp.sd)), 
            data = df.sd.hp)

Answer 2

I prefer the appearance of the graph when the statistic appears within the facet label itself. I made the following script, which allows the choice of displaying the standard deviation, mean or count. Essentially it calculates the summary statistic then merges this with the name so that you have the format CATEGORY (SUMMARY STAT = VALUE).

   #' Function will update the name with the statistic of your choice
AddNameStat <- function(df, category, count_col, stat = c("sd","mean","count"), dp= 0){

  # Create temporary data frame for analysis
  temp <- data.frame(ref = df[[category]], comp = df[[count_col]])

  # Aggregate the variables and calculate statistics
  agg_stats <- plyr::ddply(temp, .(ref), summarize,
                           sd = sd(comp),
                           mean = mean(comp),
                           count = length(comp))

  # Dictionary used to replace stat name with correct symbol for plot
  labelName <- mapvalues(stat, from=c("sd","mean","count"), to=c("\u03C3", "x", "n"))

  # Updates the name based on the selected variable
  agg_stats$join <- paste0(agg_stats$ref, " \n (", labelName," = ",
                           round(agg_stats[[stat]], dp), ")")

  # Map the names
  name_map <- setNames(agg_stats$join, as.factor(agg_stats$ref))
  return(name_map[as.character(df[[category]])])
}

Using this script with your original question:

library(datasets)
data(mtcars)

# Update the variable name
mtcars$cyl  <- AddNameStat(mtcars, "cyl", "hp", stat = "sd")

ggplot(data = mtcars, aes(x = hp)) + 
  geom_dotplot(binwidth = 1) + 
  geom_density() + 
  facet_grid(. ~ cyl) + 
  theme_bw()

The script should be easy to alter to include other summary statistics. I am also sure it could be rewritten in parts to make it a bit cleaner!