Data Visualization using GGPlot2

Using facet_grid

1. Facet with one discrete variable. Split by the levels of the group “supp”

# Split in vertical direction
p + facet_grid(rows = vars(supp))

# Split in horizontal direction
p + facet_grid(cols = vars(supp))

2. Facet with multiple variables. Split by the levels of two grouping variables: “dose” and “supp”

# Facet by two variables: dose and supp.
# Rows are dose and columns are supp
p + facet_grid(rows = vars(dose), cols = vars(supp))

Using facet_wrap

facet_wrap: Facets can be placed side by side using the function facet_wrap() as follow :

p + facet_wrap(vars(dose))

p + facet_wrap(vars(dose), ncol=2)

Facet scales

By default, all the panels have the same scales (scales="fixed"). They can be made independent, by setting scales to free, free_x, or free_y.

p + facet_grid(rows = vars(dose), cols = vars(supp), scales = "free")

Create some basic plots

# 0. Define custom color palette and prepare the data
my3cols <- c("#E7B800", "#2E9FDF", "#FC4E07")
ToothGrowth$dose <- as.factor(ToothGrowth$dose)

# 1. Create a box plot (bp)
p <- ggplot(ToothGrowth, aes(x = dose, y = len))
bxp <- p + geom_boxplot(aes(color = dose)) +
  scale_color_manual(values = my3cols)

# 2. Create a dot plot (dp)
dp <- p + geom_dotplot(aes(color = dose, fill = dose), 
                       binaxis='y', stackdir='center') +
  scale_color_manual(values = my3cols) + 
  scale_fill_manual(values = my3cols)

# 3. Create a line plot
lp <- ggplot(economics, aes(x = date, y = psavert)) + 
  geom_line(color = "#E46726") 

Combine the plots on one page

figure <- ggarrange(bxp, dp, lp,
                    labels = c("A", "B", "C"),
                    ncol = 2, nrow = 2)
figure

Change column and row span of a plot

We’ll use nested ggarrange() functions to change column/row span of plots. For example, using the R code below:

• the line plot (lp) will live in the first row and spans over two columns
• the box plot (bxp) and the dot plot (dp) will be first arranged and will live in the second row with two different columns

ggarrange(
  lp,                # First row with line plot
  # Second row with box and dot plots
  ggarrange(bxp, dp, ncol = 2, labels = c("B", "C")), 
  nrow = 2, 
  labels = "A"       # Label of the line plot
  ) 

Use shared legend for combined ggplots

To place a common unique legend in the margin of the arranged plots, the function ggarrange() [in ggpubr] can be used with the following arguments:

• common.legend = TRUE: place a common legend in a margin
• legend: specify the legend position. Allowed values include one of c(“top”, “bottom”, “left”, “right”)

ggarrange(
  bxp, dp, labels = c("A", "B"),
  common.legend = TRUE, legend = "bottom"
  )

Combine the plots over multiple pages

If you have a long list of ggplots, say n = 20 plots, you may want to arrange the plots and to place them on multiple pages. With 4 plots per page, you need 5 pages to hold the 20 plots.

The function ggarrange() [ggpubr] provides a convenient solution to arrange multiple ggplots over multiple pages. After specifying the arguments nrow and ncol,ggarrange()` computes automatically the number of pages required to hold the list of the plots. It returns a list of arranged ggplots.

For example the following R code,

multi.page <- ggarrange(bxp, dp, lp, bxp,
                        nrow = 1, ncol = 2)

returns a list of two pages with two plots per page. You can visualize each page as follow:

multi.page[[1]] # Visualize page 1
multi.page[[2]] # Visualize page 2

You can also export the arranged plots to a pdf file using the function ggexport() [ggpubr]:

ggexport(multi.page, filename = "multi.page.ggplot2.pdf")

See the PDF file: Multi.page.ggplot2

Export the arranged plots

R function: ggexport() [in ggpubr].

• Export the arranged figure to a pdf, eps or png file (one figure per page).

ggexport(figure, filename = "figure1.pdf")

• It’s also possible to arrange the plots (2 plot per page) when exporting them.

Export individual plots to a pdf file (one plot per page):

ggexport(bxp, dp, lp, bxp, filename = "test.pdf")

Arrange and export. Specify the nrow and ncol arguments to display multiple plots on the same page:

ggexport(bxp, dp, lp, bxp, filename = "test.pdf",
         nrow = 2, ncol = 1)