R Graphics · Dot Plot

Comparing Values Clearly with Dot Plots in R

Use categorical dots, Cleveland plots, grouped dots, distributions, confidence intervals, and ggplot2.

6 examplesReproducible R code

Before you begin

Choose the variation that serves the analysis

Dot plots replace bars with position along a common scale. They are compact, precise, and particularly effective for rankings and comparisons across many categories.

Examples: 06
Levels: Beginner + Intermediate

Example 01Base RBeginner

Create a Basic Dot Plot

A dot plot displays labeled values along one quantitative axis.

Run the code, inspect how the visual encoding changes, and adapt the labels, scales, and styling to the analytical question rather than treating the defaults as fixed.

RRun this code

values<-c(A=18,B=27,C=22,D=35,E=29)
dotchart(values,pch=19,col="#2563eb",xlab="Value")

Example 02Base RBeginner

Order Categories by Value

Ordering dots reveals rank and magnitude more clearly than alphabetical order.

Run the code, inspect how the visual encoding changes, and adapt the labels, scales, and styling to the analytical question rather than treating the defaults as fixed.

RRun this code

values<-sort(c(A=18,B=27,C=22,D=35,E=29))
dotchart(values,pch=19,col="#2563eb",xlab="Value")

Example 03Base RBeginner

Compare Grouped Dots

Grouped dots place related estimates on the same scale for direct comparison.

Run the code, inspect how the visual encoding changes, and adapt the labels, scales, and styling to the analytical question rather than treating the defaults as fixed.

RRun this code

m<-cbind(First=c(20,28,24,31),Second=c(24,25,29,35));rownames(m)<-LETTERS[1:4]
dotchart(m,pch=c(19,17),color=c("#2563eb","#f59e0b"),xlab="Score")

Example 04Base RIntermediate

Show a One-Dimensional Distribution

Stacked dots reveal repeated or closely spaced observations without binning into bars.

Run the code, inspect how the visual encoding changes, and adapt the labels, scales, and styling to the analytical question rather than treating the defaults as fixed.

RRun this code

x<-round(rnorm(80,10,2),1)
stripchart(x,method="stack",pch=19,col="#2563eb",xlab="Value")

Example 05Base RIntermediate

Add Confidence Intervals

Dots with horizontal intervals display estimates and their uncertainty together.

Run the code, inspect how the visual encoding changes, and adapt the labels, scales, and styling to the analytical question rather than treating the defaults as fixed.

RRun this code

est<-c(1.2,.7,1.8,1.1);se<-c(.2,.15,.3,.18);y<-1:4
plot(est,y,pch=19,col="#2563eb",yaxt="n",xlab="Estimate",ylab="")
axis(2,y,LETTERS[1:4],las=1);segments(est-1.96*se,y,est+1.96*se,y,lwd=2,col="#172554")

Example 06ggplot2Intermediate

Create a Dot Plot with ggplot2

ggplot2 supports categorical dot charts with flexible ordering and themes.

Run the code, inspect how the visual encoding changes, and adapt the labels, scales, and styling to the analytical question rather than treating the defaults as fixed.

RRun this code

library(ggplot2)
data<-data.frame(group=LETTERS[1:5],value=c(18,27,22,35,29))
ggplot(data,aes(value,reorder(group,value)))+geom_point(size=3,color="#2563eb")+labs(y=NULL)+theme_minimal()