Branches of mechanical engineering: Ggplot2 – Slow Trend To Mix Multiple Graphs On The Same Page

(This article was outset published on Easy Guides, in addition to kindly contributed to R-bloggers)

To arrange multiple ggplot2 graphs on the same page, the touchstone R functions – par() and layout() – cannot hold out used.
The basic solution is to occupation the gridExtra R package, which comes with the next functions:

grid.arrange() and arrangeGrob() to suit multiple ggplots on 1 page
marrangeGrob() for arranging multiple ggplots over multiple pages.

However, these functions makes no endeavor at aligning the plot panels; instead, the plots are precisely placed into the grid equally they are, in addition to thence the axes are non aligned.
If axis alignment is required, yous tin switch to the cowplot package, which include the function plot_grid() with the argument align. However, the cowplot bundle doesn’t incorporate whatsoever solution for multi-pages layout. Therefore, nosotros furnish the function ggarrange() [in ggpubr], a wrapper around the plot_grid() function, to suit multiple ggplots over multiple pages. It tin also create a mutual unique legend for multiple plots.

This article volition exhibit you, stair yesteryear step, how to combine multiple ggplots on the same page, equally good as, over multiple pages, using helper functions available inwards the next R package: ggpubr R package, cowplot and gridExtra. We’ll also force how to export the arranged plots to a file.

Contents:

Prerequisites

Required R package

You require to install the R package ggpubr (version >= 0.1.3), to easily create ggplot2-based publication prepare plots.
We recommend to install the latest developmental version from GitHub as follow:

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

If installation from Github failed, in addition to thence attempt to install from CRAN as follow:

install.packages("ggpubr")

Note that, the installation of ggpubr will install the gridExtra and the cowplotpackage; thence yous don’t require to re-install them.

Load ggpubr:

library(ggpubr)

Demo information sets

Data: ToothGrowth and mtcars data sets.

# 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 four  5.8   VC  0.5 v  6.4   VC  0.5 half dozen 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")])

                               cite    wt  mpg cyl Mazda RX4                 Mazda RX4 2.620 21.0   half dozen Mazda RX4 Wag         Mazda RX4 Wag 2.875 21.0   half dozen Datsun 710               Datsun 710 2.320 22.8   four Hornet four Drive       Hornet four Drive 3.215 21.4   half dozen Hornet Sportabout Hornet Sportabout 3.440 18.7   8 Valiant                     Valiant 3.460 18.1   6

Create some plots

Here, we’ll occupation ggplot2-based plotting functions available in ggpubr. You tin occupation whatsoever ggplot2 functions to create the plots that yous desire for arranging them later.
We’ll start yesteryear creating four dissimilar plots:

Box plots in addition to dot plots using the ToothGrowth data set
Bar plots in addition to scatter plots using the mtcars data set

You’ll larn how to combine these plots inwards the adjacent sections using specific functions.

Create a box plot in addition to 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 in addition to a scatter plot:

Create ordered bar plots. Change the fill upwards color yesteryear the grouping variable “cyl”. Sorting volition hold out done globally, but non yesteryear groups.

# Bar plot (bp) bp <- ggbarplot(mtcars, x = "name", y = "mpg",           fill upwards = "cyl",               # alter fill upwards color yesteryear cyl           color = "white",            # Set bar edge colors to white           palette = "jco",            # jco mag color palett. run across ?ggpar           sort.val = "asc",           # Sort the value inwards ascending club           sort.by.groups = TRUE,      # Sort within each grouping           x.text.angle = ninety           # Rotate vertically x axis texts           ) bp + font("x.text", size = 8) # Scatter plots (sp) sp <- ggscatter(mtcars, x = "wt", y = "mpg",                 add together = "reg.line",               # Add regression line of piece of work                 conf.int = TRUE,                # Add confidence interval                 color = "cyl", palette = "jco", # Color yesteryear groups "cyl"                 shape = "cyl"                   # Change indicate shape yesteryear groups "cyl"                 )+   stat_cor(aes(color = cyl), label.x = 3)       # Add correlation coefficient sp

Arrange multiple ggplots on the same page

Arrange on 1 page

To suit multiple ggplots on 1 unmarried page, we’ll occupation the function ggarrange()[in ggpubr], which is a wrapper around the function plot_grid() [in cowplot package]. Compared to the touchstone function plot_grid(), ggarange() tin suit 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, yous tin also occupation 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,                 hand = text_grob("Visualizing mpg", color = "red", seem upwards = "bold", size = 14),                 bottom = text_grob("Data source: \n mtcars information set", color = "blue",                                    hjust = 1, x = 1, seem upwards = "italic", size = 10),                 left = text_grob("Figure arranged using ggpubr", color = "green", rot = 90),                 correct = "I'm done, thank yous :-)!",                 fig.lab = "Figure 1", fig.lab.face = "bold"                 )

Arrange multiple ggplots on the same page

Note that, the role annotate_figure() supports whatsoever ggplots.

Align plot panels

Influenza A virus subtype H5N1 existent occupation instance is, for example, when plotting survival curves with the gamble tabular array placed nether the primary plot.
To illustrate this case, we’ll occupation the survminer package. First, install it using install.packages(“survminer”), in addition to thence type this:

# Fit survival curves library(survival) jibe <- survfit( Surv(time, status)   adhere, information = colon ) # Plot survival curves library(survminer) ggsurv <- ggsurvplot(fit, information = colon,                       palette = "jco",                              # jco palette                      pval = TRUE, pval.coord = c(500, 0.4),        # Add p-value                      risk.table = TRUE                            # Add gamble tabular array                      ) names(ggsurv)

[1] "plot"           "table"          "data.survplot"  "data.survtable"

ggsurv is a listing including the components:

plot: survival curves
table: the gamble tabular array plot

You tin suit the survival plot in addition to the gamble tabular array equally follow:

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

Arrange multiple ggplots on the same page

It tin hold out seen that the axes of the survival plot in addition to the gamble tabular array are non aligned vertically. To align them, specify the argument align as follow.

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 bridge of a plot

Use ggpubr R package

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

the scatter plot (sp) volition alive inwards the outset row in addition to spans over 2 columns
the box plot (bxp) in addition to the dot plot (dp) volition hold out outset arranged in addition to volition alive inwards the minute row with 2 dissimilar columns

ggarrange(sp,                                                 # First row with scatter plot           ggarrange(bxp, dp, ncol = 2, labels = c("B", "C")), # Second row with box in addition to 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] tin hold out used to house graphs at item locations with a item size.
ggdraw(). Initialize an empty drawing canvas:

ggdraw()

Note that, yesteryear default, coordinates run from 0 to 1, in addition to the indicate (0, 0) is inwards the lower left corner of the canvass (see the figure below).

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

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

plot: the plot to house (ggplot2 or a gtable)
x, y: The x/y location of the lower left corner of the plot.
width, height: the width in addition to the summit of the plot

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

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

label: a vector of labels to hold out drawn
x, y: Vector containing the x in addition to y seat of the labels, respectively.
size: Font size of the label to hold out drawn

For example, yous tin combine multiple plots, with item locations in addition to dissimilar sizes, equally follow:

library("cowplot") ggdraw() +   draw_plot(bxp, x = 0, y = .5, width = .5, summit = .5) +   draw_plot(dp, x = .5, y = .5, width = .5, summit = .5) +   draw_plot(bp, x = 0, y = 0, width = 1, summit = 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 alter the row/column bridge of a plot.
For example, using the R code below:

the scatter plot (sp) volition alive inwards the outset row in addition to spans over 2 columns
the box plot (bxp) in addition to the dot plot (dp) volition alive inwards the minute row with 2 plots inwards 2 dissimilar columns

library("gridExtra") grid.arrange(sp,                             # First row with 1 plot spaning over 2 columns              arrangeGrob(bxp, dp, ncol = 2), # Second row with 2 plots inwards 2 dissimilar columns              nrow = 2)                       # Number of rows

Arrange multiple ggplots on the same page

It’s also possible to occupation 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 in addition to 2 rows). The outset row is all 1s, that’s where the outset plot lives, spanning the 2 columns; the minute row contains plots 2 in addition to 3 each occupying 1 column.

grid.arrange(bp,                                    # bar plot spaning 2 columns              bxp, sp,                               # box plot in addition to 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() role using the helper function draw_plot_label() [in cowplot].

To easily annotate the grid.arrange() / arrangeGrob() output (a gtable), yous should outset transform it to a ggplot using the function as_ggplot() [in ggpubr ]. Next yous tin 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 2 columns              bxp, sp,                               # box plot in addition to 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 higher upwards R code, nosotros used arrangeGrob() instead of grid.arrange().
Note that, the primary divergence betwixt these 2 functions is that, grid.arrange() force automatically the output of the arranged plots.
As nosotros desire to annotate the arranged plots earlier drawing it, the function arrangeGrob() is preferred inwards this case.

Use grid R package

The grid R bundle tin hold out used to create a complex layout with the assistance of the function grid.layout(). It provides also the helper function viewport() to define a part or a viewport on the layout. The function print() is used to house plots inwards a specified region.
The dissimilar steps tin hold out summarized equally follow :

Create plots : p1, p2, p3, ….
Move to a novel page on a grid device using the function grid.newpage()
Create a layout 2X2 - issue of columns = 2; issue of rows = 2
Define a grid viewport : a rectangular part on a graphics device
Print a plot into the viewport

library(grid) # Move to a novel page grid.newpage() # Create layout : nrow = 3, ncol = 2 pushViewport(viewport(layout = grid.layout(nrow = 3, ncol = 2))) # Influenza A virus subtype H5N1 helper role to define a part 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 2 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 mutual legend for combined ggplots

To house a mutual unique legend inwards the margin of the arranged plots, the function ggarrange() [in ggpubr] tin hold out used with the next arguments:

common.legend = TRUE: house a mutual legend inwards a margin
legend: specify the legend position. Allowed values include 1 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 yesteryear 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) in addition to y (right panel) xplot <- ggdensity(iris, "Sepal.Length", fill upwards = "Species",                    palette = "jco") yplot <- ggdensity(iris, "Sepal.Width", fill upwards = "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 in addition to ggplot2 graphs

In this section, we’ll exhibit how to plot a tabular array in addition to text amongst a chart. The iris information laid volition hold out used.
We start yesteryear creating the next plots:

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

We complete yesteryear arranging/combining the 3 plots using the function ggarrange() [in ggpubr]

# Density plot of "Sepal.Length" #:::::::::::::::::::::::::::::::::::::: density.p <- ggdensity(iris, x = "Sepal.Length",                         fill upwards = "Species", palette = "jco") # Draw the summary tabular array of Sepal.Length #:::::::::::::::::::::::::::::::::::::: # Compute descriptive statistics yesteryear groups stable <- desc_statby(iris, measure.var = "Sepal.Length",                       grps = "Species") stable <- stable[, c("Species", "length", "mean", "sd")] # Summary tabular array plot, medium orangish subject stable.p <- ggtexttable(stable, rows = NULL,                          subject = ttheme("mOrange")) # Draw text #:::::::::::::::::::::::::::::::::::::: text <- paste("iris information laid gives the measurements inwards cm",               "of the variables sepal length in addition to width",               "and petal length in addition to width, respectively,",               "for l flowers from each of 3 species of iris.",              "The species are Iris setosa, versicolor, in addition to virginica.", sep = " ") text.p <- ggparagraph(text = text, seem upwards = "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 chemical element within a ggplot

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

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

grob: the external graphical chemical element to display
xmin, xmax : x location inwards information coordinates (horizontal location)
ymin, ymax : y location inwards information coordinates (vertical location)

Place a tabular array within a ggplot

We’ll occupation the plots - density.p in addition to stable.p - created inwards the previous department (@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

Create a scatter plot of y = “Sepal.Width” yesteryear x = “Sepal.Length” using the iris information set. R function ggscatter() [ggpubr]
Create separately the box plot of x in addition to y variables with transparent background. R function: ggboxplot() [ggpubr].
Transform the box plots into graphical objects called a “grop” inwards Grid terminology. R function ggplotGrob() [ggplot2].
Place the box plot grobs within 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 yesteryear 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$Sepal.Length, width = 0.3, fill upwards = "lightgray") +   rotate() +   theme_transparent() # Box plot of the y variable ybp <- ggboxplot(iris$Sepal.Width, width = 0.3, fill upwards = "lightgray") +   theme_transparent() # Create the external graphical objects # called a "grop" inwards Grid terminology xbp_grob <- ggplotGrob(xbp) ybp_grob <- ggplotGrob(ybp) # Place box plots within 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 within the scatter plot sp + annotation_custom(grob = xbp_grob, xmin = xmin, xmax = xmax,                         ymin = ymin-yoffset, ymax = ymin+yoffset) +   # Insert ybp_grob within 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 icon to ggplot2 graphs

Import the background image. Use either the function readJPEG() [in jpegpackage] or the function readPNG() [in png package] depending on the format of the background image.
To attempt the representative below, brand certain that the png package is installed. You tin install it using install.packages(“png”) R command.

# Import the icon img.file <- system.file(file.path("images", "background-image.png"),                         bundle = "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 upwards color transparency yesteryear specifying the declaration alpha. Value should hold out inwards [0, 1], where 0 is total transparency in addition to 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 French Republic map in addition to 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", means = '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 yous convey a long listing of ggplots, say n = xx plots, yous may desire to suit the plots in addition to to house them on multiple pages. With four plots per page, yous require v pages to concur the xx plots.
The function ggarrange() [in ggpubr] provides a convenient solution to suit multiple ggplots over multiple pages. After specifying the arguments nrow and ncol, the function ggarrange() computes automatically the issue of pages required to concur the listing of the plots. It returns a listing of arranged ggplots.
For representative the next R code,

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

returns a listing of 2 pages with 2 plots per page. You tin visualize each page equally follow:

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

You tin 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

Source: https://www.r-bloggers.com/ggplot2-easy-way-to-mix-multiple-graphs-on-the-same-page/

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