Prerequisites

if(!require(devtools)) install.packages("devtools")
devtools::install_github("kassambara/ggpubr")

install.packages("ggpubr")

library(ggpubr)

# ToothGrowth
data("ToothGrowth")
head(ToothGrowth)
   len supp dose
1  4.2   VC  0.5
2 11.5   VC  0.5
3  7.3   VC  0.5
4  5.8   VC  0.5
5  6.4   VC  0.5
6 10.0   VC  0.5
# mtcars 
data("mtcars")
mtcars$name <- rownames(mtcars)
mtcars$cyl <- as.factor(mtcars$cyl)
head(mtcars[, c("name", "wt", "mpg", "cyl")])
                               name    wt  mpg cyl
Mazda RX4                 Mazda RX4 2.620 21.0   6
Mazda RX4 Wag         Mazda RX4 Wag 2.875 21.0   6
Datsun 710               Datsun 710 2.320 22.8   4
Hornet 4 Drive       Hornet 4 Drive 3.215 21.4   6
Hornet Sportabout Hornet Sportabout 3.440 18.7   8
Valiant                     Valiant 3.460 18.1   6

Create some plots

Here, we’ll use ggplot2-based plotting functions available in ggpubr. You can use any ggplot2 functions to create the plots that you want for arranging them later.

We’ll start by creating 4 different plots:

• Box plots and dot plots using the ToothGrowth data set
• Bar plots and scatter plots using the mtcars data set

You’ll learn how to combine these plots in the next sections using specific functions.

• Create a box plot and a dot plot:

# Box plot (bp)
bxp <- ggboxplot(ToothGrowth, x = "dose", y = "len",
                 color = "dose", palette = "jco")
bxp
# Dot plot (dp)
dp <- ggdotplot(ToothGrowth, x = "dose", y = "len",
                 color = "dose", palette = "jco", binwidth = 1)
dp

Arrange multiple ggplots on the same page

• Create an ordered bar plot and a scatter plot:

Create ordered bar plots. Change the fill color by the grouping variable “cyl”. Sorting will be done globally, but not by groups.

# Bar plot (bp)
bp <- ggbarplot(mtcars, x = "name", y = "mpg",
          fill = "cyl",               # change fill color by cyl
          color = "white",            # Set bar border colors to white
          palette = "jco",            # jco journal color palett. see ?ggpar
          sort.val = "asc",           # Sort the value in ascending order
          sort.by.groups = TRUE,      # Sort inside each group
          x.text.angle = 90           # Rotate vertically x axis texts
          )
bp + font("x.text", size = 8)
# Scatter plots (sp)
sp <- ggscatter(mtcars, x = "wt", y = "mpg",
                add = "reg.line",               # Add regression line
                conf.int = TRUE,                # Add confidence interval
                color = "cyl", palette = "jco", # Color by groups "cyl"
                shape = "cyl"                   # Change point shape by groups "cyl"
                )+
  stat_cor(aes(color = cyl), label.x = 3)       # Add correlation coefficient
sp

Arrange multiple ggplots on the same page

Arrange on one page

To arrange multiple ggplots on one single page, we’ll use the function ggarrange()[in ggpubr], which is a wrapper around the function plot_grid() [in cowplot package]. Compared to the standard function plot_grid(), ggarange() can arrange multiple ggplots over multiple pages.

ggarrange(bxp, dp, bp + rremove("x.text"), 
          labels = c("A", "B", "C"),
          ncol = 2, nrow = 2)

Arrange multiple ggplots on the same page

Alternatively, you can also use the function plot_grid() [in cowplot]:

library("cowplot")
plot_grid(bxp, dp, bp + rremove("x.text"), 
          labels = c("A", "B", "C"),
          ncol = 2, nrow = 2)

or, the function grid.arrange() [in gridExtra]:

library("gridExtra")
grid.arrange(bxp, dp, bp + rremove("x.text"), 
             ncol = 2, nrow = 2)

Annotate the arranged figure

R function: annotate_figure() [in ggpubr].

figure <- ggarrange(sp, bp + font("x.text", size = 10),
                    ncol = 1, nrow = 2)
annotate_figure(figure,
                top = text_grob("Visualizing mpg", color = "red", face = "bold", size = 14),
                bottom = text_grob("Data source: \n mtcars data set", color = "blue",
                                   hjust = 1, x = 1, face = "italic", size = 10),
                left = text_grob("Figure arranged using ggpubr", color = "green", rot = 90),
                right = "I'm done, thanks :-)!",
                fig.lab = "Figure 1", fig.lab.face = "bold"
                )

Arrange multiple ggplots on the same page

Align plot panels

A real use case is, for example, when plotting survival curves with the risk table placed under the main plot.

To illustrate this case, we’ll use the survminer package. First, install it using install.packages(“survminer”), then type this:

# Fit survival curves
library(survival)
fit <- survfit( Surv(time, status) ~ adhere, data = colon )
# Plot survival curves
library(survminer)
ggsurv <- ggsurvplot(fit, data = colon, 
                     palette = "jco",                              # jco palette
                     pval = TRUE, pval.coord = c(500, 0.4),        # Add p-value
                     risk.table = TRUE                            # Add risk table
                     )
names(ggsurv)
[1] "plot"           "table"          "data.survplot"  "data.survtable"

ggsurv is a list including the components:

• plot: survival curves
• table: the risk table plot

You can arrange the survival plot and the risk table as follow:

ggarrange(ggsurv$plot, ggsurv$table, heights = c(2, 0.7),
          ncol = 1, nrow = 2)

Arrange multiple ggplots on the same page

ggarrange(ggsurv$plot, ggsurv$table, heights = c(2, 0.7),
          ncol = 1, nrow = 2, align = "v")

Arrange multiple ggplots on the same page

Change column/row span of a plot

Use ggpubr R package

We’ll use nested ggarrange() functions to change column/row span of plots.

For example, using the R code below:

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

Arrange multiple ggplots on the same page

Use cowplot R package

The combination of the functions ggdraw() + draw_plot() + draw_plot_label() [in cowplot] can be used to place graphs at particular locations with a particular size.

ggdraw(). Initialize an empty drawing canvas:

ggdraw()

Note that, by default, coordinates run from 0 to 1, and the point (0, 0) is in the lower left corner of the canvas (see the figure below).

draw_plot(). Places a plot somewhere onto the drawing canvas:

draw_plot(plot, x = 0, y = 0, width = 1, height = 1)

• plot: the plot to place (ggplot2 or a gtable)
• x, y: The x/y location of the lower left corner of the plot.
• width, height: the width and the height of the plot

draw_plot_label(). Adds a plot label to the upper left corner of a graph. It can handle vectors of labels with associated coordinates.

draw_plot_label(label, x = 0, y = 1, size = 16, ...)

• label: a vector of labels to be drawn
• x, y: Vector containing the x and y position of the labels, respectively.
• size: Font size of the label to be drawn

For example, you can combine multiple plots, with particular locations and different sizes, as follow:

library("cowplot")
ggdraw() +
  draw_plot(bxp, x = 0, y = .5, width = .5, height = .5) +
  draw_plot(dp, x = .5, y = .5, width = .5, height = .5) +
  draw_plot(bp, x = 0, y = 0, width = 1, height = 0.5) +
  draw_plot_label(label = c("A", "B", "C"), size = 15,
                  x = c(0, 0.5, 0), y = c(1, 1, 0.5))

Arrange multiple ggplots on the same page

Use gridExtra R package

The function arrangeGrop() [in gridExtra] helps to change the row/column span of a plot.

For example, using the R code below:

• the scatter plot (sp) will live in the first row and spans over two columns
• the box plot (bxp) and the dot plot (dp) will live in the second row with two plots in two different columns

library("gridExtra")
grid.arrange(sp,                             # First row with one plot spaning over 2 columns
             arrangeGrob(bxp, dp, ncol = 2), # Second row with 2 plots in 2 different columns
             nrow = 2)                       # Number of rows

Arrange multiple ggplots on the same page

It’s also possible to use the argument layout_matrix in the grid.arrange() function, to create a complex layout.

In the R code below layout_matrix is a 2x2 matrix (2 columns and 2 rows). The first row is all 1s, that’s where the first plot lives, spanning the two columns; the second row contains plots 2 and 3 each occupying one column.

grid.arrange(bp,                                    # bar plot spaning two columns
             bxp, sp,                               # box plot and scatter plot
             ncol = 2, nrow = 2, 
             layout_matrix = rbind(c(1,1), c(2,3)))

Arrange multiple ggplots on the same page

Note that, it’s also possible to annotate the output of the grid.arrange() function using the helper function draw_plot_label() [in cowplot].

To easily annotate the grid.arrange() / arrangeGrob() output (a gtable), you should first transform it to a ggplot using the function as_ggplot() [in ggpubr ]. Next you can annotate it using the function draw_plot_label() [in cowplot].

library("gridExtra")
library("cowplot")
# Arrange plots using arrangeGrob
# returns a gtable (gt)
gt <- arrangeGrob(bp,                               # bar plot spaning two columns
             bxp, sp,                               # box plot and scatter plot
             ncol = 2, nrow = 2, 
             layout_matrix = rbind(c(1,1), c(2,3)))
# Add labels to the arranged plots
p <- as_ggplot(gt) +                                # transform to a ggplot
  draw_plot_label(label = c("A", "B", "C"), size = 15,
                  x = c(0, 0, 0.5), y = c(1, 0.5, 0.5)) # Add labels
p

Arrange multiple ggplots on the same page

In the above R code, we used arrangeGrob() instead of grid.arrange().

Note that, the main difference between these two functions is that, grid.arrange() draw automatically the output of the arranged plots.

As we want to annotate the arranged plots before drawing it, the function arrangeGrob() is preferred in this case.

Use grid R package

The grid R package can be used to create a complex layout with the help of the function grid.layout(). It provides also the helper function viewport() to define a region or a viewport on the layout. The function print() is used to place plots in a specified region.

The different steps can be summarized as follow :

1. Create plots : p1, p2, p3, ….
2. Move to a new page on a grid device using the function grid.newpage()
3. Create a layout 2X2 - number of columns = 2; number of rows = 2
4. Define a grid viewport : a rectangular region on a graphics device
5. Print a plot into the viewport

library(grid)
# Move to a new page
grid.newpage()
# Create layout : nrow = 3, ncol = 2
pushViewport(viewport(layout = grid.layout(nrow = 3, ncol = 2)))
# A helper function to define a region on the layout
define_region <- function(row, col){
  viewport(layout.pos.row = row, layout.pos.col = col)
} 
# Arrange the plots
print(sp, vp = define_region(row = 1, col = 1:2))   # Span over two columns
print(bxp, vp = define_region(row = 2, col = 1))
print(dp, vp = define_region(row = 2, col = 2))
print(bp + rremove("x.text"), vp = define_region(row = 3, col = 1:2))

Arrange multiple ggplots on the same page

Use common 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")

Arrange multiple ggplots on the same page

Scatter plot with marginal density plots

# Scatter plot colored by groups ("Species")
sp <- ggscatter(iris, x = "Sepal.Length", y = "Sepal.Width",
                color = "Species", palette = "jco",
                size = 3, alpha = 0.6)+
  border()                                         
# Marginal density plot of x (top panel) and y (right panel)
xplot <- ggdensity(iris, "Sepal.Length", fill = "Species",
                   palette = "jco")
yplot <- ggdensity(iris, "Sepal.Width", fill = "Species", 
                   palette = "jco")+
  rotate()
# Cleaning the plots
yplot <- yplot + clean_theme() 
xplot <- xplot + clean_theme()
# Arranging the plot
ggarrange(xplot, NULL, sp, yplot, 
          ncol = 2, nrow = 2,  align = "hv", 
          widths = c(2, 1), heights = c(1, 2),
          common.legend = TRUE)

Arrange multiple ggplots on the same page

Mix table, text and ggplot2 graphs

In this section, we’ll show how to plot a table and text alongside a chart. The iris data set will be used.

We start by creating the following plots:

1. a density plot of the variable “Sepal.Length”. R function: ggdensity() [in ggpubr]
2. a plot of the summary table containing the descriptive statistics (mean, sd, … ) of Sepal.Length.
   • R function for computing descriptive statistics: desc_statby() [in ggpubr].
   • R function to draw a textual table: ggtexttable() [in ggpubr].
3. a plot of a text paragraph. R function: ggparagraph() [in ggpubr].

We finish by arranging/combining the three plots using the function ggarrange() [in ggpubr]

# Density plot of "Sepal.Length"
#::::::::::::::::::::::::::::::::::::::
density.p <- ggdensity(iris, x = "Sepal.Length", 
                       fill = "Species", palette = "jco")
# Draw the summary table of Sepal.Length
#::::::::::::::::::::::::::::::::::::::
# Compute descriptive statistics by groups
stable <- desc_statby(iris, measure.var = "Sepal.Length",
                      grps = "Species")
stable <- stable[, c("Species", "length", "mean", "sd")]
# Summary table plot, medium orange theme
stable.p <- ggtexttable(stable, rows = NULL, 
                        theme = ttheme("mOrange"))
# Draw text
#::::::::::::::::::::::::::::::::::::::
text <- paste("iris data set gives the measurements in cm",
              "of the variables sepal length and width",
              "and petal length and width, respectively,",
              "for 50 flowers from each of 3 species of iris.",
             "The species are Iris setosa, versicolor, and virginica.", sep = " ")
text.p <- ggparagraph(text = text, face = "italic", size = 11, color = "black")
# Arrange the plots on the same page
ggarrange(density.p, stable.p, text.p, 
          ncol = 1, nrow = 3,
          heights = c(1, 0.5, 0.3))

Arrange multiple ggplots on the same page

Insert a graphical element inside a ggplot

The function annotation_custom() [in ggplot2] can be used for adding tables, plots or other grid-based elements within the plotting area of a ggplot. The simplified format is :

annotation_custom(grob, xmin, xmax, ymin, ymax)

Place a table within a ggplot

We’ll use the plots - density.p and stable.p - created in the previous section (@ref(mix-table-text-and-ggplot)).

density.p + annotation_custom(ggplotGrob(stable.p),
                              xmin = 5.5, ymin = 0.7,
                              xmax = 8)

Arrange multiple ggplots on the same page

Place a box plot within a ggplot

1. Create a scatter plot of y = “Sepal.Width” by x = “Sepal.Length” using the iris data set. R function ggscatter() [ggpubr]
2. Create separately the box plot of x and y variables with transparent background. R function: ggboxplot() [ggpubr].
3. Transform the box plots into graphical objects called a “grop” in Grid terminology. R function ggplotGrob() [ggplot2].
4. Place the box plot grobs inside the scatter plot. R function: annotation_custom() [ggplot2].

As the inset box plot overlaps with some points, a transparent background is used for the box plots.

# Scatter plot colored by groups ("Species")
#::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
sp <- ggscatter(iris, x = "Sepal.Length", y = "Sepal.Width",
                color = "Species", palette = "jco",
                size = 3, alpha = 0.6)
# Create box plots of x/y variables
#::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
# Box plot of the x variable
xbp <- ggboxplot(iris$Sepal.Length, width = 0.3, fill = "lightgray") +
  rotate() +
  theme_transparent()
# Box plot of the y variable
ybp <- ggboxplot(iris$Sepal.Width, width = 0.3, fill = "lightgray") +
  theme_transparent()
# Create the external graphical objects
# called a "grop" in Grid terminology
xbp_grob <- ggplotGrob(xbp)
ybp_grob <- ggplotGrob(ybp)
# Place box plots inside the scatter plot
#::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
xmin <- min(iris$Sepal.Length); xmax <- max(iris$Sepal.Length)
ymin <- min(iris$Sepal.Width); ymax <- max(iris$Sepal.Width)
yoffset <- (1/15)*ymax; xoffset <- (1/15)*xmax
# Insert xbp_grob inside the scatter plot
sp + annotation_custom(grob = xbp_grob, xmin = xmin, xmax = xmax, 
                       ymin = ymin-yoffset, ymax = ymin+yoffset) +
  # Insert ybp_grob inside the scatter plot
  annotation_custom(grob = ybp_grob,
                       xmin = xmin-xoffset, xmax = xmin+xoffset, 
                       ymin = ymin, ymax = ymax)

Arrange multiple ggplots on the same page

Add background image to ggplot2 graphs

Import the background image. Use either the function readJPEG() [in jpeg package] or the function readPNG() [in png package] depending on the format of the background image.

To test the example below, make sure that the png package is installed. You can install it using install.packages(“png”) R command.

# Import the image
img.file <- system.file(file.path("images", "background-image.png"),
                        package = "ggpubr")
img <- png::readPNG(img.file)

Combine a ggplot with the background image. R function: background_image() [in ggpubr].

library(ggplot2)
library(ggpubr)
ggplot(iris, aes(Species, Sepal.Length))+
  background_image(img)+
  geom_boxplot(aes(fill = Species), color = "white")+
  fill_palette("jco")

Arrange multiple ggplots on the same page

Change box plot fill color transparency by specifying the argument alpha. Value should be in [0, 1], where 0 is full transparency and 1 is no transparency.

library(ggplot2)
library(ggpubr)
ggplot(iris, aes(Species, Sepal.Length))+
  background_image(img)+
  geom_boxplot(aes(fill = Species), color = "white", alpha = 0.5)+
  fill_palette("jco")

Arrange multiple ggplots on the same page

Another example, overlaying the France map and a ggplot2:

mypngfile <- download.file("https://upload.wikimedia.org/wikipedia/commons/thumb/e/e4/France_Flag_Map.svg/612px-France_Flag_Map.svg.png", 
                           destfile = "france.png", mode = 'wb') 
img <- png::readPNG('france.png') 
ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width)) +
  background_image(img)+
  geom_point(aes(color = Species), alpha = 0.6, size = 5)+
  color_palette("jco")+
  theme(legend.position = "top")

Arrange multiple ggplots on the same page

Arrange 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() [in ggpubr] provides a convenient solution to arrange multiple ggplots over multiple pages. After specifying the arguments nrow and ncol, the function 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, bp, sp,
                        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() [in ggpubr]:

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

PDF file: Multi.page.ggplot2

library(gridExtra)
res <- marrangeGrob(list(bxp, dp, bp, sp), nrow = 1, ncol = 2)
# Export to a pdf file
ggexport(res, filename = "multi.page.ggplot2.pdf")
# Visualize interactively
res

Nested layout with ggarrange()

We’ll arrange the plot created in section (@ref(mix-table-text-and-ggplot)) and (@ref(create-some-plots)).

p1 <- ggarrange(sp, bp + font("x.text", size = 9),
                ncol = 1, nrow = 2)
p2 <- ggarrange(density.p, stable.p, text.p, 
                ncol = 1, nrow = 3,
                heights = c(1, 0.5, 0.3))
ggarrange(p1, p2, ncol = 2, nrow = 1)

Arrange multiple ggplots on the same page

Export plots

R function: ggexport() [in ggpubr].

First, create a list of 4 ggplots corresponding to the variables Sepal.Length, Sepal.Width, Petal.Length and Petal.Width in the iris data set.

plots <- ggboxplot(iris, x = "Species",
                   y = c("Sepal.Length", "Sepal.Width", "Petal.Length", "Petal.Width"),
                   color = "Species", palette = "jco"
                   )
plots[[1]]  # Print the first plot
plots[[2]]  # Print the second plots and so on...

Next, you can export individual plots to a file (pdf, eps or png) (one plot per page). 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(plotlist = plots, filename = "test.pdf")

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

ggexport(plotlist = plots, filename = "test.pdf",
         nrow = 2, ncol = 1)

Acknoweledgment

We sincerely thank all developers for their efforts behind the packages that ggpubr depends on, namely:

• Baptiste Auguie (2016). gridExtra: Miscellaneous Functions for “Grid” Graphics. R package version 2.2.1. https://CRAN.R-project.org/package=gridExtra
• Claus O. Wilke (2016). cowplot: Streamlined Plot Theme and Plot Annotations for ‘ggplot2’. R package version 0.7.0. https://CRAN.R-project.org/package=cowplot
• H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2009.

Infos

This analysis has been performed using R software (ver. 3.3.2) and ggpubr (ver. 0.1.4.999).