How do I create a dumbbell chart in R with ggplot2?

Use geom_segment() + geom_point() from the ggplot2 package. Variables needed: 1 categorical + 2 numerical.

What data types work with a dumbbell chart?

A dumbbell chart works best with categorical, numerical data. It requires 1 categorical + 2 numerical.

Comparison CategoricalNumerical

Dumbbell Chart

ggplot2: geom_segment() + geom_point() · Package: ggplot2 · Variables: 1 categorical + 2 numerical

WHAT IS A DUMBBELL CHART?

A dumbbell chart (also called a connected dot plot or gap chart) shows two values per category connected by a line segment, highlighting the gap or change between them. It is ideal for before/after comparisons, year-over-year changes, or showing the difference between two conditions (e.g., male vs female, plan vs actual). The visual emphasis is on the magnitude of the gap, not the absolute values. Dumbbell charts are more compact and elegant than grouped bar charts for pairwise comparisons. In ggplot2, combine geom_segment() for the connecting line with two geom_point() layers for the endpoints.

BEST FOR

· Before/after comparisons
· Gap analysis between two values
· Period-over-period change

AVOID WHEN

· More than 2 comparison points
· Very few categories
· When absolute values matter more than gap

R + GGPLOT2 CODE EXAMPLE

ggplot2

df <- data.frame(car = rownames(mtcars)[1:8],
  before = mtcars$mpg[1:8], after = mtcars$mpg[1:8] + sample(-3:5, 8, TRUE))
ggplot(df, aes(y = reorder(car, before))) +
  geom_segment(aes(x = before, xend = after, yend = car), color = "grey60") +
  geom_point(aes(x = before), color = "tomato", size = 3) +
  geom_point(aes(x = after), color = "#ff6a00", size = 3) +
  labs(title = "Before vs After MPG", x = "MPG", y = NULL)