Format ggplot2 diagrams

Install required packages

ggplot2, colorspace

wants <- c("ggplot2", "colorspace")
has   <- wants %in% rownames(installed.packages())
if(any(!has)) install.packages(wants[!has])

Simulate data

Data needs to be in long format.

Njk    <- 50
P      <- 3
Q      <- 2
IQ     <- rnorm(P*Q*Njk, mean=100, sd=15)
height <- rnorm(P*Q*Njk, mean=175, sd=7)
rating <- factor(sample(LETTERS[1:3], Njk*P*Q, replace=TRUE))
sex    <- factor(rep(c("f", "m"), times=P*Njk))
group  <- factor(rep(c("control", "placebo", "treatment"), each=Q*Njk))
sgComb <- interaction(sex, group)
mood   <- round(rnorm(P*Q*Njk, mean=c(85, 80, 110, 90, 130, 100)[sgComb], sd=25))
myDf   <- data.frame(sex, group, sgComb, IQ, height, rating, mood)

Control element position

Side-by-side = “dodge”

library(ggplot2)
ggplot(myDf, aes(x=mood, fill=sex)) +
    geom_histogram(aes(y=..density..), position=position_dodge())

Random jitter - useful for overlapping points, e.g., when variables are integer.

ggplot(myDf, aes(x=group, y=mood)) +
    geom_point()

ggplot(myDf, aes(x=group, y=mood)) +
    geom_point(position=position_jitter(width=0.2))

ggplot(myDf, aes(x=rating, group=sex, fill=sex)) +
    geom_bar(stat="count",
             aes(y=(..count..) / sum(..count..)),
             position=position_fill())

Format axes

Change order of categories by changing order of factor levels.

levels(myDf$rating)

[1] "A" "B" "C"

levels(myDf$rating) <- rev(levels(myDf$rating))
ggplot(myDf, aes(x=rating, group=sex, fill=sex)) +
    geom_bar(stat="count",
             aes(y=(..count..) / sum(..count..)),
             position=position_fill()) +
    labs(x="Rating category", y="Cumulative relative frequency")

Rotate x-axis labels and fine tune x-axis limits / breaks.

ggplot(myDf, aes(x=height, y=mood, colour=sex, shape=group)) +
    geom_point(size=3) +
    scale_x_continuous(limits=c(150, 200),
                       expand=c(0, 0),
                       breaks=seq(150, 200, by=5)) +
    scale_y_continuous(n.breaks=8) +
    guides(x=guide_axis(angle=90))

Flip x- and y-axis

ggplot(myDf, aes(x=sex, y=height, fill=sex)) +
    geom_boxplot() +
    coord_flip(ylim=c(140, 200))

Format legend

ggplot(myDf, aes(x=height, y=mood, colour=sex:group, shape=sex)) +
    geom_hline(aes(yintercept=100), linetype=2) +
    geom_vline(aes(xintercept=180), linetype=2) +
    geom_point(size=3) +
    geom_smooth(method=lm, se=TRUE, size=1.2, fullrange=TRUE) +
    facet_grid(sex ~ group) +
    labs(title="mood ~ height stratified by sex + group") +
    geom_text(aes(x=190, y=70, label=sgComb),
              size=7, hjust="right", show.legend=FALSE) +
    annotate("text", x=165, y=35, size=7, label="Annotation") +
    guides(shape="none") +
    theme(legend.position="bottom")

Format color, shape and line type

library(colorspace)
(groupM <- aggregate(mood ~ sex + group, data=myDf, FUN=mean))

  sex     group   mood
1   f   control  84.28
2   m   control  84.04
3   f   placebo 117.22
4   m   placebo  87.06
5   f treatment 130.40
6   m treatment 103.38

ggplot(groupM, aes(x=group, y=mood, color=sex, shape=sex, group=sex)) +
    geom_point(size=8, stroke=2) +
    geom_line(size=2, linetype="dashed") +
    scale_shape_discrete(solid=FALSE)

ggplot(myDf, aes(x=mood, fill=group)) +
    geom_histogram(aes(y=..density..), alpha=0.5) +
    geom_density(alpha=0.7) +
    scale_fill_discrete_qualitative()

Use themes for a collection of pre-set formatting choices.

ggplot(myDf, aes(x=mood, fill=group)) +
    geom_histogram(aes(y=..density..), alpha=0.5) +
    geom_density(alpha=0.7) +
    scale_fill_discrete_qualitative() +
    theme_bw()

ggplot(myDf, aes(x=sex, y=height, fill=sex)) +
    geom_boxplot() +
    coord_flip(ylim=c(140, 200)) +
    theme_minimal()

Further resources

See Cookbook for R: ggplot2 diagrams for many detailed examples of ggplot2 diagrams.

Detach (automatically) loaded packages (if possible)

try(detach(package:ggplot2))
try(detach(package:colorspace))

Get the article source from GitHub

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