Laura DeCicco found that non-R users keep asking her what her box plots exactly mean or demonstrate. In a recent blog post, she therefore breaks down the calculations into easy-to-follow chunks of code. Even better, she included the source code to make boxplots that come with a very elaborate default legend:

As you can see, the above contains much more and easier to understand information than the original ggplot2 boxplot below.

Laura wrote the custom function `ggplot_box_legend()`

(see source code below and in Laura’s blog), which uses the `cowplot`

package to paste the explanation to the box plot. All you need to do is call the legend function just before you run your ggplot2 boxplot call.

ggplot_box_legend <- function(family = "serif"){
# Create data to use in the boxplot legend:
set.seed(100)
sample_df <- data.frame(parameter = "test",
values = sample(500))
# Extend the top whisker a bit:
sample_df$values[1:100] <- 701:800
# Make sure there's only 1 lower outlier:
sample_df$values[1] <- -350
# Function to calculate important values:
ggplot2_boxplot <- function(x){
quartiles <- as.numeric(quantile(x,
probs = c(0.25, 0.5, 0.75)))
names(quartiles) <- c("25th percentile",
"50th percentile\n(median)",
"75th percentile")
IQR <- diff(quartiles[c(1,3)])
upper_whisker <- max(x[x < (quartiles[3] + 1.5 * IQR)])
lower_whisker <- min(x[x > (quartiles[1] - 1.5 * IQR)])
upper_dots <- x[x > (quartiles[3] + 1.5*IQR)]
lower_dots <- x[x < (quartiles[1] - 1.5*IQR)]
return(list("quartiles" = quartiles,
"25th percentile" = as.numeric(quartiles[1]),
"50th percentile\n(median)" = as.numeric(quartiles[2]),
"75th percentile" = as.numeric(quartiles[3]),
"IQR" = IQR,
"upper_whisker" = upper_whisker,
"lower_whisker" = lower_whisker,
"upper_dots" = upper_dots,
"lower_dots" = lower_dots))
}
# Get those values:
ggplot_output <- ggplot2_boxplot(sample_df$values)
# Lots of text in the legend, make it smaller and consistent font:
update_geom_defaults("text",
list(size = 3,
hjust = 0,
family = family))
# Labels don't inherit text:
update_geom_defaults("label",
list(size = 3,
hjust = 0,
family = family))
# Create the legend:
# The main elements of the plot (the boxplot, error bars, and count)
# are the easy part.
# The text describing each of those takes a lot of fiddling to
# get the location and style just right:
explain_plot <- ggplot() + stat_boxplot(data = sample_df, aes(x = parameter, y=values), geom ='errorbar', width = 0.3) + geom_boxplot(data = sample_df, aes(x = parameter, y=values), width = 0.3, fill = "lightgrey") + geom_text(aes(x = 1, y = 950, label = "500"), hjust = 0.5) + geom_text(aes(x = 1.17, y = 950, label = "Number of values"), fontface = "bold", vjust = 0.4) + theme_minimal(base_size = 5, base_family = family) + geom_segment(aes(x = 2.3, xend = 2.3, y = ggplot_output[["25th percentile"]], yend = ggplot_output[["75th percentile"]])) + geom_segment(aes(x = 1.2, xend = 2.3, y = ggplot_output[["25th percentile"]], yend = ggplot_output[["25th percentile"]])) + geom_segment(aes(x = 1.2, xend = 2.3, y = ggplot_output[["75th percentile"]], yend = ggplot_output[["75th percentile"]])) + geom_text(aes(x = 2.4, y = ggplot_output[["50th percentile\n(median)"]]), label = "Interquartile\nrange", fontface = "bold", vjust = 0.4) + geom_text(aes(x = c(1.17,1.17), y = c(ggplot_output[["upper_whisker"]], ggplot_output[["lower_whisker"]]), label = c("Largest value within 1.5 times\ninterquartile range above\n75th percentile", "Smallest value within 1.5 times\ninterquartile range below\n25th percentile")), fontface = "bold", vjust = 0.9) + geom_text(aes(x = c(1.17), y = ggplot_output[["lower_dots"]], label = "Outside value"), vjust = 0.5, fontface = "bold") + geom_text(aes(x = c(1.9), y = ggplot_output[["lower_dots"]], label = "-Value is >1.5 times and"),
vjust = 0.5) +
geom_text(aes(x = 1.17,
y = ggplot_output[["lower_dots"]],
label = "<3 times the interquartile range\nbeyond either end of the box"),
vjust = 1.5) +
geom_label(aes(x = 1.17, y = ggplot_output[["quartiles"]],
label = names(ggplot_output[["quartiles"]])),
vjust = c(0.4,0.85,0.4),
fill = "white", label.size = 0) +
ylab("") + xlab("") +
theme(axis.text = element_blank(),
axis.ticks = element_blank(),
panel.grid = element_blank(),
aspect.ratio = 4/3,
plot.title = element_text(hjust = 0.5, size = 10)) +
coord_cartesian(xlim = c(1.4,3.1), ylim = c(-600, 900)) +
labs(title = "EXPLANATION")
return(explain_plot)
}
ggplot_box_legend()

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