In this chapter, we will combine multi-plot layouts (patchwork), collision-free labels (ggrepel) and rich text (ggtext) into three polished before/after case studies.
Individual plots answer single questions. Combining them into one composed figure with clean labels is what separates an exploratory chart from a published one.
Each extension adds load time and new syntax. Master core ggplot2 first; reach for these only for final figures.
Before: two related plots shown separately. After: one composed figure with a shared title.
p1 <- ggplot(mtcars) +
geom_point(aes(disp, mpg, color = factor(cyl))) +
labs(title = "Displacement vs mileage")
p2 <- ggplot(mtcars) +
geom_boxplot(aes(factor(cyl), mpg, fill = factor(cyl))) +
labs(title = "Mileage by cylinders")
p1 + p2 + plot_annotation(title = "Engine size explains fuel economy")
Stack vertically with / and collect legends with plot_layout(guides = "collect"):
p1 / p2 + plot_layout(guides = "collect")
Before: geom_text() labels pile onto each other. After: geom_text_repel() pushes them apart with thin leader lines.
cars <- mtcars
cars$model <- rownames(mtcars)
efficient <- cars[cars$mpg > 30, ]
ggplot(cars) +
geom_point(aes(disp, mpg)) +
ggrepel::geom_text_repel(data = efficient, aes(disp, mpg, label = model), size = 3)
Before: plain titles. After: element_markdown() renders color and emphasis inline.
ggplot(mtcars) +
geom_point(aes(disp, mpg, color = factor(cyl))) +
labs(title = "Heavier engines drink <b style='color:#d62728'>more fuel</b>") +
theme(plot.title = ggtext::element_markdown())