In descriptive statistics, a box plot or boxplot (also known as a box and whisker plot) is a type of chart often used in explanatory data analysis. Box plots visually show the distribution of numerical data and skewness by displaying the data quartiles (or percentiles) and averages.

Instead of tediously adding the geom_line and annotate to your plot you just add a single layer geom_signif: library(ggplot2) library(ggsignif) ggplot(iris, aes(x=Species, y=Sepal.Length)) + geom_boxplot() + geom_signif(comparisons = list(c("versicolor", "virginica")), map_signif_level=TRUE)

In this article, we’ll describe how to easily i) compare means of two or multiple groups; ii) and to automatically add p-values and significance levels to a ggplot (such as box plots, dot plots, bar plots and line plots …).

Significance bars help convey the statistical significance of differences between groups. They are often accompanied by asterisks that indicate the level of significance. Adding these elements to boxplots allows for a clearer understanding of how groups compare, especially in research and data analysis contexts.