Two main points:

1. Tweaking the look of the above plots
2. Plot Resolution and Font Sizes

ggplot2 uses themes to control the overall appearance

ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_bw()

My default is theme_bw()

• Removes the background grey, prints labels in black etc.

ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_classic()

ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_void()

library(ggthemes)

ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_economist()

ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_excel()

The theme() function is where you set:

• axis.text, legend attributes etc.
• Often uses elements to set an attribute

?theme

Changing text within themes uses element_text()

?element_text

ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_bw() +
  theme(axis.text = element_text(family = "Courier", 
                                 size = 15, angle = 30))

Changing backgrounds and outlines uses element_rect()

ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_bw() +
  theme(legend.background = element_rect(fill = "yellow", 
                                         colour = "black"))

To remove all attributes use element_blank() in place of element_rect(), element_text() or element_line()

ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_bw() +
  theme(panel.grid = element_blank())

We can move the legend to multiple places:

ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_bw() +
  theme(legend.position = "bottom")

Or we can use co-ordinates to place it inside the plotting region

ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_bw() +
  theme(legend.position = c(0.8, 0.1))

We can also edit axes, fills, outlines etc. using scale_...() layers

ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_bw() +
  scale_y_log10(limits = c(100, 200),
                breaks = c(100, 125, 150, 175)) 

We can turn off or modify plot expansion

ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_bw() +
  scale_y_continuous(expand=c(0, 0)) 

ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_bw() +
  scale_fill_manual(values = c("green", "blue"))

Colours can also be specified using hexadecimal codes

rgb(1, 0, 0)

[1] "#FF0000"

The main image formats are jpeg, png and tiff

• R can also export svg and pdf
• ggplot2 has the function ggsave()

?ggsave

The Plots Tab is the default graphics device

ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_bw() +
  scale_fill_manual(values = c("green", "blue"))

ggsave("HeightByGender.png")

• ggsave defaults to 300dpi
• Defaults to the size of the Plots Tab

• Change the size manually by setting the width and height attributes

ggsave("HeightByGender.png", width = 18, height = 18, units = "cm")

• Getting the font size right can take ages
• Need to set correctly when we make the plot

• We initiate another graphics device using png(), jpeg(), pdf() etc.
• Turn the device off after creating the image using dev.off()
• Nothing will appear in the Plots tab

png("HeightByGender.png", width = 18, height = 18, units = "cm", 
    res = 300)
ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_bw() +
  theme(text = element_text(size = 16)) +
  scale_fill_manual(values = c("green", "blue"))
dev.off()

Try to decide how big the plot will be in your final document

• Export using that size

To make multiple plots/subplots, use the package grid

1. Save each plot as an R object
2. Create viewports which we can "push" the plot to
3. Use the print() function, specifying the viewport

plotHeight <- ggplot(data, aes(x = gender, y = height, fill = gender)) +
  geom_boxplot() +
  theme_bw() +
  guides(fill = FALSE)
plotWeight <- ggplot(data, aes(x = gender, y = weight, fill = gender)) +
  geom_boxplot() +
  theme_bw() 

Create the viewports and print

• The device has width = 1 and height = 1

library(grid)
vp1 <- viewport(x = 0, y = 0, width = 0.4, just = c("left", "bottom"))
vp2 <- viewport(x = 0.4, y = 0, width = 0.6, just = c("left", "bottom"))
grid.newpage()
print(plotHeight, vp = vp1)
print(plotWeight, vp = vp2)
grid.text("A", 0.05, 0.95)
grid.text("B", 0.45, 0.95)