Data Visualization

Using ggplot2

POLISHING PLOTS

Visual Appearance

Built-In Themes

Other Themes: ggthemes a ggplot2 extension

Setting Themes

You can globally set a theme with the theme_set() function:

theme_set(theme_bw()) #<<
ggplot(mtcars, aes(x = wt, y = mpg, colour = gear)) + 
  geom_point()

Elements in a theme

The function theme() is used to control non-data parts of the graph including:

  • Line elements: axis lines, minor and major grid lines, plot panel border, axis ticks background color, etc.
  • Text elements: plot title, axis titles, legend title and text, axis tick mark labels, etc.
  • Rectangle elements: plot background, panel background, legend background, etc.

There is a specific function to modify each of these three elements :

  • element_line() to modify the line elements of the theme
  • element_text() to modify the text elements
  • element_rect() to change the appearance of the rectangle elements
  • element_blank() to draw nothing and assign no space

Note: rel() is used to specify sizes relative to the parent, margins() is used to specify the margins of elements.

Modifying a plot

p1 <- ggplot(mpg) + 
  geom_bar(aes(x = class, colour = manufacturer, fill = manufacturer) ) 

p2 <- p1 + #<<
  theme_classic() + 
  ## modify plot background
  theme(plot.background = element_rect(fill = "lightskyblue1",colour = "pink",size = 0.5, linetype = "longdash")) #<<

Plot Legends

p3 <- p2 + 
  theme(
  ### move and modify legend 
  legend.title = element_blank(), #<<
  legend.position = "top", #<<
  legend.key = element_rect(fill = "lightskyblue1", color = "lightskyblue1"), #<<
  legend.background = element_rect( fill = "lightskyblue1",color = "pink", size = 0.5,linetype = "longdash") #<<
  )

Modifying Axes

p4 <- p3 + theme(
  ### remove axis ticks
  axis.ticks=element_blank(), #<<
  ### modify axis lines
  axis.line.y = element_line(colour = "pink", size = 1, linetype = "dashed"),#<<
  axis.line.x = element_line(colour = "pink", size = 1.2, linetype = "dashed") #<<
  )

Plot Labels

Can be modified in several ways: - labs(), xlab(), ylab(), ggtitle() - You can also set axis and legend labels in the individual scales (using the first argument, the name) e.g. scale_x_continuous() .

p5 <- p4 + 
  labs(x = "Class of car", #<<
       y = "", #<<
       title = "Cars by class and manufacturer", #<<
       subtitle = "With a custom theme!!") #<<

Zooming

p <- ggplot(mtcars, aes(x = wt, y = mpg, colour = gear)) + 
  geom_point() 

p_zoom_in <- p + 
  xlim(2, 4) + #<<
  ylim(10, 25) #<<

p_zoom_out <- p + 
  scale_x_continuous(limits = c(0,7)) + #<<
  scale_y_continuous(limits = c(0, 45)) #<<

Interactive graphics

Plotly

p <- ggplot(mtcars, aes(x = wt, y = mpg, colour = gear)) + 
  geom_point() +
  scale_color_locuszoom()

library(plotly) #<<
ggplotly(p) #<<

Saving graphics

Saving your Work

We can save the results of a plot to a file (as an image) using the ggsave() function:

p1 <- ggplot(mtcars, aes(x = wt, y = mpg, colour = gear)) + 
  geom_point()

ggsave("mpg_by_wt.pdf", plot = p1) #<<

Your Turn

  1. Create a scatterplot of bill length versus bill width from the penguins and color by species.
  2. Use the black and white theme
  3. Clean up axis labels and include an informative title.
  4. Capitalize legend title and change the color palette from default.
  5. Move the legend to the bottom and set aspect ratio to 1.
  6. Save your plot to a pdf file and open it in a pdf viewer.
  7. Save a png of the same scatterplot.
  8. Embed the png into MS word or another editor.
install.packages("palmerpenguins")
data(penguins, package = "palmerpenguins")
head(penguins)

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