![]() Scatterplot with ggplot2 How to Annotate a Specific Cluster or Group using geom_mark_ellipse ![]() # simple scatter plot colored by variable Let us get started by loading the package and data needed to make the plot.įirst, let make a scatterplot using ggplot2’s geom_point() after removing any missing data. To annotate specific cluster as circle, we can use geom_mark_circle() function from ggforce. In this example, we will use geom_mark_ellipse() function to highlight a cluster on scatterplot. We can use R package ggforce to annotate a select group as a circle or ellipse on a scatter plot. This can be useful to highlight overlap between groups.In this tutorial, we will learn how to annotate or highlight a specific cluster/group in R using ggplot2. We can change the transparency and fill values of the different polygons for all the methods. # plot with spline encirclement ggplot ( birdsAll, aes ( x = mass, y = length, color = age )) + geom_point () + geom_encircle ( expand = 0 ) + theme_bw () with smoothing spline using the areas or the amount of overlap for other subsequent tests). This method is nice for highlighting groups visually and indicate cohesion, and not necessarily for performing any further analyses on the polygons themselves (e.g. It has flexible options for color, fill, and the smoothness of the polygons that it draws. ![]() This geom uses polynomial splines to draw nice smoothed polygons around the groups of points. It uses geom_encircle, a new geometry provided in the ggalt package. This option is what I ended up using for my own figures. # plot with ellipse ggplot ( birdsAll, aes ( x = mass, y = length )) + geom_mark_ellipse ( expand = 0, aes ( fill = age )) + geom_point () + theme_bw () ellipse Encircle We can plot the ellpises with ggforce, although ggplot::stat_ellipse is also an option. # rounded and more concave hull ggplot ( birdsAll, aes ( x = mass, y = length )) + geom_mark_hull ( expand = 0.01, aes ( fill = age )) + geom_point () + theme_bw () hulls and fills for each group EllipsesĪnother common alternative is to group points using ellipses. Tweaking the parameters can give us a tighter hull with nice round corners. # calculating convex hulls #plot with hull ggplot ( birdsAll, aes ( x = mass, y = length )) + geom_mark_hull ( concavity = 5, expand = 0, radius = 0, aes ( fill = age )) + geom_point () + theme_bw () with convex hulls and fills for each groupĬonvex hulls often include large areas with no points in them. We can now calculate the convex hulls for many groups using ggforce. Convex hulls have a formal geometric definition, but basically they are like stretching a rubber band around the outermost points in the group. ) %>% mutate ( age = "da圓0" ) # bind and remove rows with missing data birdsAll % na.omit () # plot points only ggplot ( birdsAll, aes ( x = mass, y = length, color = age )) + geom_point () + theme_bw () just the points in 2d Convex hullsĬonvex hulls are one of the most common methods for grouping points. ) %>% mutate ( age = "day40" ) birds30 % select ( mass = Day.30.mass.g. # load packages (install first if needed) library ( dplyr ) library ( ggplot2 ) library ( ggalt ) library ( ggforce ) # load data downloaded from repository (from your own working directory) birdData % select ( mass = Day.40.mass.g. After loading (or installing if necessary) the required packages and downloading the data from Dryad, we can wrangle the data so we can plot length and mass data from several individual birds at 30 vs 40 days of age. ![]() I wanted to use real data, so the following examples use data from this paper on the physiology of the Japanese quail. These methods are for ggplot, but I assume there are ways to do the same things using base or other plotting engines. Here are some alternatives for drawing polygons around groups of points, with code and examples. This includes Principal Component Analyses, bioclimatic profiles, or any other combination of values on two axes. Updated on February 2020 to include geoms provided by ggforce.Įsta publicación está disponible en español aquiįor various kinds of analyses, we often end up plotting point data in two dimensions for two or groups. Drawing polygons around groups of points in ggplot
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