Since I have updated to ggplot2 2.0.0, I cannot arrange charts propperly using gridExtra. The issue is that the faceted charts will get compressed while other will expand. The widths are basically messed up. I want to arrange them similar to the way these single facet plots are: left align two graph edges (ggplot)
I put a reproducible code
library(grid) # for unit.pmax()
library(gridExtra)
plot.iris <- ggplot(iris, aes(Sepal.Length, Sepal.Width)) +
geom_point() +
facet_grid(. ~ Species) +
stat_smooth(method = "lm")
plot.mpg <- ggplot(mpg, aes(x = cty, y = hwy, colour = factor(cyl))) +
geom_point(size=2.5)
g.iris <- ggplotGrob(plot.iris) # convert to gtable
g.mpg <- ggplotGrob(plot.mpg) # convert to gtable
iris.widths <- g.iris$widths # extract the first three widths,
mpg.widths <- g.mpg$widths # same for mpg plot
max.widths <- unit.pmax(iris.widths, mpg.widths)
g.iris$widths <- max.widths # assign max. widths to iris gtable
g.mpg$widths <- max.widths # assign max widths to mpg gtable
grid.arrange(g.iris,g.mpg,ncol=1)
As you will see, the top chart, the first facet is expanded while the other 2 get compressed at the right. Bottom chart does not cover all width.
Could it be that the new ggplot2 version is messing with the gtable widths?
Anyone know a workaround?
Thank you very much
EDIT: Added picture of chart
I'm looking for something like:
one option is to massage each plot into a 3x3 gtable, where the central cell wraps all the plot panels.
Using the example from #SandyMuspratt
# devtools::install_github("baptiste/egg")
grid.draw(egg::ggarrange(plots=plots, ncol=1))
the advantage being that once in this standardised format, plots may be combined in various layouts much more easily, regardless of number of panels, legends, axes, strips, etc.
grid.newpage()
grid.draw(ggarrange(plots=list(p1, p4, p2, p3), widths = c(2,1), debug=TRUE))
I'm not sure if you're still looking for a solution, but this is fairly general. I'm using ggplot 2.1.0 (now on CRAN). It's based on this solution. I break the problem into two parts. First, I deal with the left side of the plots, making sure the widths for the axis material are the same. This has already been done by others, and there are solutions on SO. But I don't think the result looks good. I would prefer the panels to align on the right side as well. So second, the procedure makes sure the widths of the columns to the right of the panels are the same. It does this by adding a column of appropriate width to the right of each of the plots. (There's possibly neater ways to do it. There is - see #baptiste solution.)
library(grid) # for pmax
library(gridExtra) # to arrange the plots
library(ggplot2) # to construct the plots
library(gtable) # to add columns to gtables of plots without legends
mpg$g = "Strip text"
# Four fairly irregular plots: legends, faceting, strips
p1 <- ggplot(mpg, aes(displ, 1000*cty)) +
geom_point() +
facet_grid(. ~ drv) +
stat_smooth(method = "lm")
p2 <- ggplot(mpg, aes(x = hwy, y = cyl, colour = factor(cyl))) +
geom_point() +
theme(legend.position=c(.8,.6),
legend.key.size = unit(.3, "cm"))
p3 <- ggplot(mpg, aes(displ, cty, colour = factor(drv))) +
geom_point() +
facet_grid(. ~ drv)
p4 <- ggplot(mpg, aes(displ, cty, colour = factor(drv))) +
geom_point() +
facet_grid(g ~ .)
# Sometimes easier to work with lists, and it generalises nicely
plots = list(p1, p2, p3, p4)
# Convert to gtables
g = lapply(plots, ggplotGrob)
# Apply the un-exported unit.list function for grid package to each plot
g.widths = lapply(g, function(x) grid:::unit.list(x$widths))
## Part 1: Make sure the widths of left axis materials are the same across the plots
# Get first three widths from each plot
g3.widths <- lapply(g.widths, function(x) x[1:3])
# Get maximum widths for first three widths across the plots
g3max.widths <- do.call(unit.pmax, g3.widths)
# Apply the maximum widths to each plot
for(i in 1:length(plots)) g[[i]]$widths[1:3] = g3max.widths
# Draw it
do.call(grid.arrange, c(g, ncol = 1))
## Part 2: Get the right side of the panels aligned
# Locate the panels
panels <- lapply(g, function(x) x$layout[grepl("panel", x$layout$name), ])
# Get the position of right most panel
r.panel = lapply(panels, function(x) max(x$r)) # position of right most panel
# Get the number of columns to the right of the panels
n.cols = lapply(g.widths, function(x) length(x)) # right most column
# Get the widths of these columns to the right of the panels
r.widths <- mapply(function(x,y,z) x[(y+1):z], g.widths, r.panel, n.cols)
# Get the sum of these widths
sum.r.widths <- lapply(r.widths, sum)
# Get the maximum of these widths
r.width = do.call(unit.pmax, sum.r.widths)
# Add a column to the right of each gtable of width
# equal to the difference between the maximum
# and the width of each gtable's columns to the right of the panel.
for(i in 1:length(plots)) g[[i]] = gtable_add_cols(g[[i]], r.width - sum.r.widths[[i]], -1)
# Draw it
do.call(grid.arrange, c(g, ncol = 1))
Taking off these two lines and keeping the rest, it worked just fine.
g.iris$widths <- max.widths # assign max. widths to iris gtable
g.mpg$widths <- max.widths # assign max widths to mpg gtable
Probably it was limiting the width of them.
This is ugly but if you're under a time pressure this hack will work (not generalizable and dependent upon plot window size). Basically make the top plot 2 columns with a blank plot on the right and guess at the widths.
grid.arrange(
grid.arrange(plot.iris, ggplot() + theme_minimal(),ncol=2, widths = c(.9, .1)),
plot.mpg,
ncol=1
)
Related
I made two heatmaps with the code:
I create the first heatmap
heatmap1<-ggplot(mod_mat_constraint, aes(x=Categorie, y=label)) +
geom_tile(aes(fill=Value)) + scale_fill_manual(values = c("#86d65e","#404040","#86d65e","#40c5e8","#e84a4a","#86d65e","#404040","#e2e2e2"), breaks=label_text)
I create the second heatmap
heatmap2<-ggplot(mod_mat_gen_env, aes(x=Categorie, y=label)) +
geom_tile(aes(fill=Value)) + scale_fill_manual(values = c("#86d65e","#404040","#86d65e","#40c5e8","#e84a4a","#86d65e","#404040","#e2e2e2"), breaks=label_text)
and I add them with a tree with:
heatmap2 %>% insert_left(tree) %>% insert_right(heatmap1, width=.5)
which gives me:
and I wondered if there were a way with ggplot2 to add an additional df box at the right corner such as:
from a dataframe called DF1
COL1 COL2 COL3
0.1 Peter USA
Hard to help precisely without a dataset, but to get a table overlaid on your plot, probably the best way would be to use annotation_custom() with a tableGrob() from the gridExtra package.
Here's an example heatmap pulled right from the R Graph Gallery which I used to add in your table as a grob.
# Library
library(ggplot2)
library(gridExtra)
# Dummy data
x <- LETTERS[1:20]
y <- paste0("var", seq(1,20))
data <- expand.grid(X=x, Y=y)
data$Z <- runif(400, 0, 5)
# Heatmap
p <- ggplot(data, aes(X, Y, fill= Z)) +
geom_tile()
df <- data.frame(COL1=0.1,COL2='Peter',COL3='USA')
# adding the table
p + coord_cartesian(clip='off') +
theme(plot.margin = margin(r=140)) +
annotation_custom(
grob=tableGrob(df, theme=ttheme_default(base_size = 7)),
xmin=20, xmax=27, ymin=1, ymax=5
)
You can probably use a similar approach in your case. Note the few things that I had to do here to get this to work:
add the grob as annotation_custom(). You will need to play around with the positioning... really just play with those numbers. Also note you may want to play with the base size to ensure the table is the right aspect ratio compared to your plot.
Extend the plot margin so that you have the real estate on that side to include the table.
Turn clipping off so that you can see things outside the plot area properly.
I have got four plots with all the same x axis (Time) but different y axis. So I used
library(ggplot2)
Gio.m <- melt(Gio, id="AGE")
ggplot(Gio.m[!is.na(Gio.m$value),], aes(x=AGE, y=value, group=1))+
geom_line(aes(color=variable)) +
facet_grid(variable ~ ., scales="free_y") +
theme(legend.position="none")
to make a grid with four scatterplots.
The result looks like this:
The first question would be how to avoid that the output shows all the y-values.
The second question is, if there is a possibility of turning the axis of only one plot within the grid (which should afterwards have a reversed y-axis).
Thanks a lot for your help, and if I should provide more infos on the data pls let me know.
For your first question, as already mentioned by #Roman, you most probably have categorical data in the column value after you melt Gio table. To fix that, transform it back to numeric:
if value is character, then run Gio.m$value <- as.numeric(Gio.m$value)
if value is factor, then run Gio.m$value <- as.numeric(levels(Gio.m$value))[Gio.m$value] as pointed out here
For the second question - not sure if I understand correctly, but one solution could be this:
1) Generate a plot example and its version with reversed OY axis:
library(ggplot2)
library(grid)
# Plot 1
p1 <- ggplot(mpg, aes(cty, displ)) + geom_point() + facet_grid(drv ~ cyl)
# Plot 2 = plot 1 with OY reversed
p2 <- p1 + scale_y_reverse()
2) Get the grid layout and identify grobs:
# Generate the ggplot2 plot grob for each case
g1 <- ggplotGrob(p1)
g2 <- ggplotGrob(p2)
# Draw a diagram of a Grid layout; Is helpful to identifies grobs
grid.show.layout(gtable:::gtable_layout(g1))
# or reduce the font if more practical
grid.show.layout(gtable:::gtable_layout(g1), vp = viewport(gp = gpar(cex=0.7)))
# Check also the layout
g1$layout
Checking and visualizing the layout structure as above can help with identifying the wanted grobs. Here, I want to identify the names of the top panel grobs, so that I replace them with the ones from the graph with reversed OY.
3) Replace the grobs. Will replace the top 3 panels of plot 1 (p1) with the ones from p2 having the OY reversed. Also need to replace the axis.
# Replace the panels from g1 with the ones from g2
panels <- c('panel-1-1', 'panel-4-1', 'panel-3-2', 'panel-2-3')
for (p in panels){
g1$grobs[grep(p, g1$layout$name)] <- g2$grobs[grep(p, g2$layout$name)]
}
# Also replace the axis corresponding to those panels
g1$grobs[grep('axis-l-1', g1$layout$name)] <- g2$grobs[grep('axis-l-1', g2$layout$name)]
Check the results
p1 # the original plot
grid.newpage(); grid.draw(g1) # the edited plot with top panels having OY reversed
Just realized that you do not facet by two variables, but only by one, in this case, is a bit less complex:
p1 <- ggplot(mpg, aes(cty, displ)) + geom_point() + facet_grid(cyl ~ ., scales="free_y")
p2 <- p1 + scale_y_reverse()
g1 <- ggplotGrob(p1)
g2 <- ggplotGrob(p2)
g1$grobs[grep("panel-1-1", g1$layout$name)] <- g2$grobs[grep("panel-1-1", g2$layout$name)]
g1$grobs[grep('axis-l-1', g1$layout$name)] <- g2$grobs[grep('axis-l-1', g2$layout$name)]
I am trying to align multiple plots with facets. My problem is somewhat minor but irratating: I can make a plot so that the plot areas are aligned and the facets themselves are aligned, but the facet strips are not all the same width. If the labels of the facets are different lengths, then the facet strips are sized so that the text can fit within the facets. I am unable so far to find a way to make all facet strips the same width when aligning multiple plots.
Here is an example of the type of plots I want to align and my efforts to align them:
library(data.table)
library(ggplot2)
library(foreach)
library(stringr)
library(cowplot)
# example data to show how aligning faceted plots is not quite right
plotvars = c(paste0("plot1_var", 1:7), paste0("plot2_var",1:5), paste0("plot3_var",1:10))
data =
foreach(p=plotvars,.combine = "rbind") %do% {
d = data.table(plot = rep(str_extract(p,pattern = "plot[[:digit:]]"),2),
plot_variables = rep(p,2),
fill_categories = c("fill1","fill2"),
number = sample(1:1000, size = 2))
d[, facet_variables := ifelse(plot=="plot1",
rep(sample(paste0("facet",1:3),size=1),2),
ifelse(plot=="plot2",
rep(sample(paste0("facet_title",1:3),size=1),2),
ifelse(plot=="plot3",
rep(sample(paste0("facet_title_longer",1:3),size=1),2),
NA)))]
d
}
# function to make stacked barplots with facets + coord_flip
make_plot = function(data, plot_var) {
ggplot(data[plot==plot_var],
aes(x=plot_variables,
y=number,
fill=fill_categories))+
geom_bar(stat="identity")+
coord_flip()+
facet_grid(facet_variables ~ .,
space="free",
scales="free")+
theme(strip.text.y = element_text(angle=0),
legend.position = "none")
}
p1 = make_plot(data=data,plot_var="plot1")
p1
p2 = make_plot(data=data,plot_var="plot2")
p2
p3 = make_plot(data=data,plot_var = "plot3")
p3
# using 'cowplot::plot_grid' gives strange re-sizing of individual bars
cowplot::plot_grid(p1,p2,p3, ncol=1,nrow=3,align = "hv")
# try gtable_rbind version
g1=ggplotGrob(p1)
g2=ggplotGrob(p2)
g3=ggplotGrob(p3)
# this plot keeps the bar widths the correct size, but the facets are still incorrectly different widths.
ggdraw(gridExtra::gtable_rbind(g1,g2,g3))
How can I make the facet strips the same width across plots?
You can achieve something like this with a labeller function that inserts a second row of blank spaces of whatever length you want. Using mtcars...
#define a function to add a second line of spaces after a given label
#and a blank line before to maintain the centre vertical alignment
#you might need to play with the appropriate value to get the width right
widen <- function(x) paste(" \n", x, "\n", paste0(rep(" ", 20), collapse=""))
mtcars %>% ggplot(aes(x = mpg)) +
geom_histogram() +
facet_grid(cyl ~ ., labeller = labeller(cyl = widen)) +
coord_flip() +
theme(strip.text.y = element_text(angle = 0))
The facet strips are wrapped inside another table, and you need to adjust the widths there. The following seems to work.
g1 <- ggplotGrob(p1)
g2 <- ggplotGrob(p2)
g3 <- ggplotGrob(p3)
# g3 has the widest strips, so get the width from there and copy over
# to the other plots
stripwidth <- g3$grobs[[13]]$widths
g1$grobs[[13]]$widths <- stripwidth
g1$grobs[[14]]$widths <- stripwidth
g1$grobs[[15]]$widths <- stripwidth
g2$grobs[[13]]$widths <- stripwidth
g2$grobs[[14]]$widths <- stripwidth
g2$grobs[[15]]$widths <- stripwidth
ggdraw(gridExtra::gtable_rbind(g1,g2,g3))
Change this part
facet_grid(facet_variables ~ .,
space="free",
scales="free")+
to
facet_grid(facet_variables ~ .,
space="fixed", # This is the difference
scales="free")+
To display multiple plots I use multiplot (http://www.cookbook-r.com/Graphs/Multiple_graphs_on_one_page_(ggplot2)/), now I have two plots who share the same x-axis range and are plotted above each other:
multiplot(plot1, plot2)
I removed the x-axis labels and title using:
xlab(NULL) + theme(axis.text.x=element_blank(),axis.ticks.x=element_blank())
But there is still a white margin between the two plots. How can I make this margin smaller or remove it?
To reduce space between the plots, remove the bottom margin of the top plot and remove the top margin of the bottom plot. The code below sets these margins to 0, which still results in a tiny bit of white space between the plots. You can make these margins slightly negative (maybe -0.1 or so) to completely remove the white space. Rather than the multiplot function, we use grid.arrange from the gridExtra package to lay out the plots. :
library(grid)
library(gridExtra)
## Create two sample plots with the same x axis using built-in mtcars data frame
# Top plot: Remove bottom margin, x-labels, and x title
p1 = ggplot(mtcars, aes(wt, mpg)) + geom_point() +
xlab(NULL) +
theme(axis.text.x=element_blank(),axis.ticks.x=element_blank(),
plot.margin=unit(c(1,1,0,1), "lines"))
# Bottom plot: Remove top margin
p2 = ggplot(mtcars, aes(wt, carb)) + geom_point() +
theme(plot.margin=unit(c(0,1,1,1), "lines"))
# Lay out plots in one column
grid.arrange(p1, p2, ncol=1)
Two problems with the above layout: (1) the y axes are not justified properly, and (2) the height of the lower plot's plot area is less than that of upper plot's plot area. The code below addresses these issues:
# Left justify plots
# Source: http://stackoverflow.com/a/13295880/496488
gA <- ggplotGrob(p1)
gB <- ggplotGrob(p2)
maxWidth = grid::unit.pmax(gA$widths[2:5], gB$widths[2:5])
gA$widths[2:5] <- as.list(maxWidth)
gB$widths[2:5] <- as.list(maxWidth)
# Lay out justified plots. Use heights argument to equalize heights of each plot area
grid.arrange(gA, gB, heights=c(0.47,0.53), ncol=1)
You can exactly equalize the heights of each plot area using the same trick as we used to left-justify the plots (rather than doing it by eye using the heights argument to grid.arrange), but then the plot margins get added back. I'm not sure of how to deal with that, but here's the code for reference:
maxHeight = grid::unit.pmax(gA$heights[2:5], gB$heights[2:5])
gA$heights[2:5] <- as.list(maxHeight)
gB$heights[2:5] <- as.list(maxHeight)
The last update of ggplot2 gives much more control over the plot. See for example:
ggplot(mtcars, aes(disp, mpg)) +
geom_point() +
facet_wrap(~vs)
You can further adjust the labels, number of rows, and how scales will be displayed, for instance: nrow = 2; scales = "free".
It is easier than you might think to re-arrange the data so that you can take advantage of the nice alignment features that already exist in ggplot2. See below for an example replicating eipi10's answer, but without having to use ggplotGrob.
What you have to do is just select the columns you want to plot, along with the ID columns (in this case, the car model and the x-axis value column). Then melt, and it's ready to plot using the standard facet procedure.
Note that the "switch" option in the facet_grid call is a new feature that you can access by updating to the most recent CRAN version. I used that to replace the regular y-axis title, which was omitted using theme.
The nice part about this approach is that the plots will always be perfectly aligned.
library("ggplot2")
library("dplyr")
library("reshape2")
df <- mtcars %>%
add_rownames(var = "Model") %>%
select(Model, wt, mpg, carb) %>%
melt(id.vars = c("Model","wt"))
ggplot(df)+
aes(x=wt, y=value)+
geom_point()+
theme(strip.background=element_blank())+
facet_grid(variable ~ ., scales="free_y", switch="y")
I'm trying to arrange plots for publication with the use of cowplot package.
I just want the panels to be equally sized and labelled.
Reproducible example
library(ggplot2)
library(cowplot)
gg1 <- ggplot(mtcars)+
geom_point(aes(x=mpg,y=hp))+
theme_bw()+
theme(aspect.ratio=1)
gg2 <- ggplot(mtcars)+
geom_point(aes(x=mpg,y=hp,fill=cyl))+
facet_wrap(~cyl,ncol=2)+
theme_bw()+
theme(aspect.ratio=1,
legend.position='none')
output <- plot_grid(gg1,gg2, labels = c('A','B'),label_size = 20)
print(output)
The code produces this plot.
As you may see, neither the horizontal axises match nor do the upper edges of the panels.
The argument align from cowplot does not work with faceted plots.
Any ideas?
Since this is one of the highest voted question regarding cowplot and complex alignments, I wanted to point out that cowplot now does have some functionality for aligning faceted plots. (I'm the package author.) However, they don't work in this particular case!
For example, this works (using the axis option in plot_grid()):
gg1 <- ggplot(mtcars) +
geom_point(aes(x=mpg, y=hp)) +
theme_bw()
gg2 <- ggplot(mtcars)+
geom_point(aes(x=mpg, y=hp, fill=cyl)) +
facet_wrap(~cyl, ncol=2) +
theme_bw() +
theme(legend.position='none')
plot_grid(gg1, gg2, labels = c('A','B'), label_size = 20,
align = 'h', axis = 'tb')
We can also do this the following, to get a different type of alignment (depending on whether you want the facet strip to be counted as part of the plot or not):
plot_grid(gg1, gg2, labels = c('A', 'B'), label_size = 20,
align = 'h', axis = 'b')
Now why did I say it doesn't work for this case? Because, if you look at the original code in the question, you'll see that there was a theme(aspect.ratio=1) setting that I removed. cowplot can align plots as long as you don't force a specific aspect ratio, because the method it uses to align plots typically modifies the aspect ratio of the individual plots.
Here's a hack until someone comes up with a more elegant answer: You can use grid.arrange from the gridExtra package to change the relative sizes of the two plots so that the axes line up. The w parameter in the code below is what controls that by giving the left-hand plot a bit more of the horizontal width, thereby making it relatively larger, when compared with the right-hand plot.
library(gridExtra)
w = 0.512
grid.arrange(gg1, gg2, widths=c(w,1-w), ncol=2)
You can also use arrangeGrob and textGrob to add the "A" and "B" titles to each plot.
w = 0.512
grid.arrange(arrangeGrob(textGrob("A", x=0.13, gp=gpar(fontface="bold", cex=1.4)),
gg1, heights=c(0.03,0.97)),
arrangeGrob(textGrob("B", x=0.13, gp=gpar(fontface="bold", cex=1.4)),
gg2, heights=c(0.03,0.97)),
widths=c(w,1-w), ncol=2)
In either case, you need to adjust w by hand to get the plots to line up (which is what makes this method, shall we say, sub-optimal). The appropriate value for w will change depending on the physical size of the plot. w=0.512 seemed to work well when I saved the plot below as a png of 1000 x 500 pixels.
A better answer will probably involve something analogous to this SO answer, but adapted for lining up facetted and non-facetted plots (or, more generally, plots that don't have a one-to-one correspondence between their constituent grobs).
here's a solution based on this idea
library(ggplot2)
library(grid)
library(gridExtra)
library(gtable)
gtable_frame <- function(g, width=unit(1,"null"), height=unit(1,"null")){
panels <- g[["layout"]][grepl("panel", g[["layout"]][["name"]]), ]
ll <- unique(panels$l)
tt <- unique(panels$t)
fixed_ar <- g$respect
if(fixed_ar) { # there lies madness, want to align despite aspect ratio constraints
ar <- as.numeric(g$heights[tt[1]]) / as.numeric(g$widths[ll[1]])
height <- width * ar
g$respect <- FALSE
}
core <- g[seq(min(tt), max(tt)), seq(min(ll), max(ll))]
top <- g[seq(1, min(tt)-1), ]
bottom <- g[seq(max(tt)+1, nrow(g)), ]
left <- g[, seq(1, min(ll)-1)]
right <- g[, seq(max(ll)+1, ncol(g))]
fg <- nullGrob()
lg <- if(length(left)) g[seq(min(tt), max(tt)), seq(1, min(ll)-1)] else fg
rg <- if(length(right)) g[seq(min(tt), max(tt)), seq(max(ll)+1,ncol(g))] else fg
grobs = list(fg, g[seq(1, min(tt)-1), seq(min(ll), max(ll))], fg,
lg, g[seq(min(tt), max(tt)), seq(min(ll), max(ll))], rg,
fg, g[seq(max(tt)+1, nrow(g)), seq(min(ll), max(ll))], fg)
widths <- unit.c(sum(left$widths), width, sum(right$widths))
heights <- unit.c(sum(top$heights), height, sum(bottom$heights))
all <- gtable_matrix("all", grobs = matrix(grobs, ncol=3, nrow=3, byrow = TRUE),
widths = widths, heights = heights)
all[["layout"]][5,"name"] <- "panel" # make sure knows where the panel is for nested calls
if(fixed_ar) all$respect <- TRUE
all
}
p1 <- ggplot(mtcars)+
geom_point(aes(x=mpg,y=hp))+
theme_bw()+
theme(aspect.ratio=1)
p2 <- ggplot(mtcars)+
geom_point(aes(x=mpg,y=hp,fill=cyl))+
facet_wrap(~cyl,ncol=2)+
theme_bw()+
theme(aspect.ratio=1,
legend.position='none')
g1 <- ggplotGrob(p1)
g2 <- ggplotGrob(p2)
fg1 <- gtable_frame(g1)
fg2 <- gtable_frame(g2)
grid.newpage()
grid.draw(cbind(fg1, fg2))
Note that the gtable_frame function wraps plots based on their panels, but excluding the panel strips by design (I find it more pleasant).
Update: egg package is on CRAN now
https://cran.r-project.org/web/packages/egg/index.html
I just want to add that #baptiste has created a great experimental package egg, which accomplishes what he wrote in his answer:
Install it from github (https://github.com/baptiste/egg)
library("devtools")
install_github("baptiste/egg")
Then simply do
library("egg")
ggarrange(gg1, gg2, ncol=2)
You can add labels manually:
ap <- ggarrange(gg1,gg2, ncol=2)
ggdraw(ap) + draw_plot_label(label=c("a","b"), x=c(0,0.5), y=c(1,1))
(When I tried to first add the labels to the individual plots, the plots didn't get arranged properly.)
I have a simpler solution sticking with plot_grid and the original example. However some may feel it is a bit of a cheat.
One can fine-tune aligning plots with cowplot:plot_grid by adding nested NULL plots and adjusting their height/width ratios. This is applied below:
gg3<-plot_grid(NULL,gg2, NULL, align = 'h', nrow = 3, rel_heights = c(0.06,1,0.06))
plot_grid(gg1,gg3, labels = c('A','B'),label_size = 20)