I'm using this tutorial to create a circular barplot: https://www.r-graph-gallery.com/295-basic-circular-barplot.html
I want to create a legend in the middle of the barplot, where the white area is. However, so far i have only been able to add text in the middle. If i want to draw a small cube with the colour, it wraps itself around and i don't know how it uses the coordinates (i tried x = 0, y = 0 which gives the result below, they are always curved).
These are the two lines that i added:
geom_tile(aes(x = 1, y = 0, colour = "#EB5500"), width = 100, height = 100, inherit.aes = F) +
geom_text(x = 0, aes(y = -100, label = "test"), size = 4)
So that the full code now looks like this:
# Clear workspace
rm(list = ls())
# Libraries
library(tidyverse)
# Create dataset
data <- data.frame(
id=seq(1,60),
individual=paste( "Mister ", seq(1,60), sep=""),
value=sample( seq(10,100), 60, replace=T)
)
# Make the plot
p <- ggplot(data, aes(x=as.factor(id), y=value)) + # Note that id is a factor. If x is numeric, there is some space between the first bar
# This add the bars with a blue color
geom_bar(stat="identity", fill=alpha("blue", 0.3)) +
# Limits of the plot = very important. The negative value controls the size of the inner circle, the positive one is useful to add size over each bar
ylim(-100,120) +
# Custom the theme: no axis title and no cartesian grid
theme_minimal() +
theme(
axis.text = element_blank(),
axis.title = element_blank(),
panel.grid = element_blank(),
plot.margin = unit(rep(-2,4), "cm") # This remove unnecessary margin around plot
) +
# This makes the coordinate polar instead of cartesian.
coord_polar(start = 0) +
geom_tile(aes(x = 1, y = 0, colour = "#EB5500"), width = 100, height = 100, inherit.aes = F) +
geom_text(x = 0, aes(y = -100, label = "test"), size = 4)
p
But this gives me an image that looks like this:
It seems that ggplot automatically adds a legend based on the grid that I added. That legend needs to be in the center, and it should be a legend for the blue bar chart instead of the grid. Is there a way to do this?
What I don't really get about your question is what is supposed to be in the legend. The idea of legends is that they explain a mapping (something inside aes()) so you usually want to have that in your data already:
library(tidyverse)
data <- data.frame(
id=seq(1,60),
individual=paste( "Mister ", seq(1,60), sep=""),
value=sample( seq(10,100), 60, replace=T),
colour = "test1" # added to have something to map to
)
Now you can map the fill aesthetic to the new column. To move the legend to the center you have to add legend.position = c(0.5, 0.5) to your theme.
p <- ggplot(data, aes(x=as.factor(id), y=value, fill = colour)) + # Note that id is a factor. If x is numeric, there is some space between the first bar
geom_bar(stat="identity") +
ylim(-100,120) +
theme_minimal() +
theme(
axis.text = element_blank(),
axis.title = element_blank(),
panel.grid = element_blank(),
legend.position = c(0.5, 0.5), # move legend to the center
plot.margin = unit(rep(-2,4), "cm") # This remove unnecessary margin around plot
) +
coord_polar(start = 0)
p
I chose test1 to show that anything can go into the data. To change the colour you have to define a manual (or other) scale:
p +
scale_fill_manual(values = alpha("blue", 0.3))
theme(legend.position = c(.5, .5)) center the legend to the plot.
Related
I want to write the y-axis title horizontally on top of the y-axis line while keeping settings defined for the y-axis in the theme() function. The objective is to avoid wasting space while keeping a nice looking design (e.g. with the title left-aligned with y-axis-ticks-labels).
I know it is possible to use other "hacks" (see this using subtitle), but here I look for a solution using the grid approach. I am also aware that it is possible to move around the title by setting margins but it requires to uptade it all the time and I was not able to get a satisfying result with it.
Then, using grid functions as demonstrated in this SO post seems the way to go.
Here is what I would like to get:
It is possible to start with theme(axis.title.y = element_text(angle = 0, vjust = 1)) but the y-axis title is not on top of the line.
This code removes the y-axis title while keeping the theme() parameters defined for the grob:
library(ggplot2)
library(grid)
p <- ggplot(data = iris, aes(x = Sepal.Length, y = Petal.Length)) +
theme(axis.title.y = element_text(angle = 0, vjust = 1),
axis.title.x = element_blank())
# convert from ggplot to grob object
gp <- ggplotGrob(p)
# locate the grob that corresponds to y-axis title and save its parameters
y.label.grob <- gp$grobs[[which(gp$layout$name == "ylab-l")]]$children
# remove y-axis labels from the plot, & shrink the space occupied by them
gp$grobs[[which(gp$layout$name == "ylab-l")]] <- zeroGrob()
gp$widths[gp$layout$l[which(gp$layout$name == "ylab-l")]] <- unit(0, "cm")
But now I am stuck as I do not know how to use functions from the grid package to move the title where I would like to (i.e. on the top left corner).
You can exceed vjust beyond 1 and adapt the margins a bit. It's hard to get the alignment perfectly though.
library(ggplot2)
library(grid)
ggplot(data = iris, aes(x = Sepal.Length, y = Petal.Length)) +
theme(
plot.margin = margin(t = 30),
axis.title.y = element_text(
angle = 0, vjust = 1.1,
margin = margin(r = -50, t = 5.5, b = 5.5, l = 5.5)),
axis.title.x = element_blank()
)
If you know the title in advance you can use it's string width.
ggplot(data = iris, aes(x = Sepal.Length, y = Petal.Length)) +
theme(
plot.margin = margin(t = 30),
axis.title.y = element_text(
angle = 0, vjust = 1.07,
margin = unit.c(
unit(c(2.75), "pt"),
unit(-1, "strwidth", data = "Petal.Length"),
unit(c(2.75, 2.75), "pt")
)
),
axis.title.x = element_blank()
)
Created on 2021-09-09 by the reprex package (v2.0.1)
You could use cowplot as another approach:
library(ggplot2)
library(cowplot)
title <- ggdraw() +
draw_label(
"Petal.Length",
#fontface = 'bold',
x = 0,
hjust = 0
) +
theme(
# add margin on the left of the drawing canvas,
# so title is aligned with left edge of first plot
plot.margin = margin(0, 0, 0, 7)
)
p <- ggplot(data = iris, aes(x = Sepal.Length, y = Petal.Length)) +
labs(y = "")
plot_row <- plot_grid(p)
plot_grid(
title, plot_row,
ncol = 1,
rel_heights = c(0.1, 1)
)
I have decided to rephrase this question. (Editing would have taken more time and in my opinion would also not have helped the OP.)
How can one left-adjust (hjust = 0, i.e., in text direction) over facets, when scale = 'free_x'?
I don't really think that left-adjustment of x-labels is a very necessary thing to do (long labels generally being difficult to read, and right-adjusting probably the better choice) - but I find the problem interesting enough.
I tried with empty padding to the maximum character length, but this doesn't result in the same length for all strings. Also, setting axis.text.x = element.text(margin = margin()) doesn't help. Needless to say, hjust = 0 does not help, because it is adjusting within each facet.
library(ggplot2)
diamonds$cut_label <- paste("Super Dee-Duper", as.character(diamonds$cut))
ggplot(data = diamonds, aes(cut_label, carat)) +
facet_grid(~ cut, scales = "free_x") +
theme(axis.text.x = element_text(angle = 90))
The red arrows and dashed line indicate how the labels should adjust. hjust = 0 or margins or empty padding do not result in adjustment of those labels over all facets.
Data modification from this famous question
I tried with empty padding to the maximum character length, but this
doesn't result in the same length for all strings.
This caught my attention. Actually, it would result in the same length for all strings if you padded the labels with spaces, made them all the same length, and ensured the font family was non-proportionally spaced.
First, pad the labels with spaces such that all labels have the same length. I'm going to ustilise the str_pad function from the stringr package.
library(ggplot2)
data("diamonds")
diamonds$cut_label <- paste("Super Dee-Duper", as.character(diamonds$cut))
library(stringr)
diamonds$cut_label <- str_pad(diamonds$cut_label, side="right",
width=max(nchar(diamonds$cut_label)), pad=" ")
Then, you may need to load a non-proportionally-spaced font using the extrafont package.
library(extrafont)
font_import(pattern='consola') # Or any other of your choice.
Then, run the ggplot command and specify a proportionally spaced font using the family argument.
ggplot(data = diamonds, aes(cut_label, carat)) +
facet_grid(~cut, scales = "free_x") +
theme(axis.text.x = element_text(angle = 90, family="Consolas"))
One way, and possibly the most straight forward hack, would be to annotate outside the coordinates.
Disadvantage is that the parameters would need manual adjustments (y coordinate, and plot margin), and I don't see how to automate this.
library(ggplot2)
diamonds$cut_label <- paste("Super Dee-Duper", as.character(diamonds$cut))
ann_x <- data.frame(x = unique(diamonds$cut_label), y = -16, cut = unique(diamonds$cut))
ggplot(data = diamonds, aes(cut_label, carat)) +
facet_grid(~cut, scales = "free_x") +
geom_text(data = ann_x, aes(x, y, label = x), angle = 90, hjust = 0) +
theme(
axis.text.x = element_blank(),
plot.margin = margin(t = 0.1, r = 0.1, b = 2.2, l = 0.1, unit = "in")
) +
coord_cartesian(ylim = c(0, 14), clip = "off")
Created on 2020-03-14 by the reprex package (v0.3.0)
I'd approach this by making 2 plots, one of the plot area and one of the axis labels, then stick them together with a package like cowplot. You can use some theme settings to disguise the fact that the axis labels are actually made by a geom_text.
The first plot is fairly straightforward. For the second which becomes the axis labels, use dummy data with the same variables and adjust spacing how you want via text size and scale expansion. You'll probably also want to mess with the rel_heights argument in plot_grid to change the ratio of the two charts' heights.
library(ggplot2)
library(cowplot)
p1 <- ggplot(diamonds, aes(x = cut_label, y = carat)) +
facet_grid(cols = vars(cut), scales = "free_x") +
theme(axis.text.x = element_blank()) +
labs(x = NULL)
axis <- ggplot(dplyr::distinct(diamonds, cut_label, cut), aes(x = cut_label, y = 1)) +
geom_text(aes(label = cut_label), angle = 90, hjust = 0, size = 3.5) +
facet_grid(cols = vars(cut), scales = "free_x") +
scale_x_discrete(breaks = NULL) +
scale_y_continuous(expand = expansion(add = c(0.1, 1)), breaks = NULL) +
labs(y = NULL) +
theme(strip.text = element_blank(),
axis.text.x = element_blank(),
axis.ticks = element_blank(),
panel.background = element_blank())
plot_grid(p1, axis, ncol = 1, axis = "lr", align = "v")
We can edit the text grobs after generating the plot, using library(grid).
g <- ggplot(data = diamonds, aes(cut_label, carat)) +
facet_grid(~cut, scales = "free_x") +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5))
gt <- cowplot::as_gtable(g)
axis_grobs <- which(grepl("axis-b", gt$layout$name))
labs <- levels(factor(diamonds$cut_label))[order(levels(diamonds$cut))]
for (i in seq_along(axis_grobs)) {
gt$grobs[axis_grobs[i]][[1]] <-
textGrob(labs[i], y = unit(0, "npc"), just = "left", rot = 90, gp = gpar(fontsize = 9))
}
grid.draw(gt)
I want to use geom_segment to replace error bars with arrows when the error exceeds a certain limit. I found a previous post that addresses this question: R - ggplot2 - Add arrow if geom_errorbar outside limits
The code works well, except that my x-axis is a factor variable instead of a numeric variable. Using position_dodge within the geom_segment statement makes the arrows start in the correct location, but it doesn't change the terminal point (xend) and all arrows point towards one central point on the x-axis instead of going straight up from the origins.
Instead of recoding the x-axis to be numeric (I will use this code to create many plots that have a range of x-axis values, with the last numeric value always ending in "+"), is there a way to correct this within geom_segment?
Code used:
data$OR.95U_u = ifelse(data$OR.95U > 10, 10 , NA)
ggplot(data, aes(x = numAlleles, y = OR, fill = Outcome)) +
geom_bar(position = position_dodge(.5), stat = "identity", width = .4, color = "black") + geom_hline(yintercept = 1, linetype = "dashed", color = "black") +
ylim(0,10) + geom_errorbar(aes(ymin=OR.95L, ymax=OR.95U), width=.2,position=position_dodge(.5)) +
theme(legend.key = element_blank(), text = element_text(size = 11.5), legend.title = element_blank()) +
labs(x = "Number of rare alleles") +
scale_fill_manual(values=c("chocolate1","coral1", "red2", "darkred")) +
geom_segment(aes(x = numAlleles, xend = numAlleles, y = OR, yend = OR.95U_u), position = position_dodge(.5), arrow = arrow(length = unit(0.3, "cm")))
Resulting figure
Ok, after investigating a bit, I didn't find a clean way of doing this, at it seems that position_dodge only change the x aes, and not the xend aes. position_nudge also don't work here, as it moves all the arrows at the same time.
So I came with a dirty way of doing this. All we need is create a new variable with the desired xend position for the geom_segment. I try and came with a semi-automtized way of doing it, for any number of levels of the coloring variable, and also created a reproducible dataset to work with, as I'm sure this could be improved a lot by people with more knowledge than me.
The code has inline comments expalining the steps:
library(tidyverse)
# dummy data (tried to replicate your plot data more or less accurately)
df <- tibble(
numAlleles = rep(c("1", "2+"), each = 4),
Outcome = rep(LETTERS[1:4], 2),
OR = c(1.4, 1.5, 1.45, 2.3, 3.8, 4.2, 4.0, 1.55),
OR.95U = c(1.9,2.1,1.9,3.8,12,12,12,12),
OR.95L = c(0.9, 0.9, 0.9, 0.8, NA, NA,NA,NA)
) %>%
mutate(
OR.95U_u = if_else(OR.95U > 10, 10, NA_real_)
)
# as it seems that position_dodge in a geom_segment only "dodge" the x aes and
# not the xend aes, we need to supply a custom xend. Also, we need to try
# to automatize the position, for more classes or different dodge widths.
# To do that, lets start with some parameters:
# position_dodge width
position_dodge_width <- 0.5
# number of bars per x axis class
bars_per_class <- length(unique(df$Outcome))
# total space available per class. In discrete vars, this is 1 au (arbitrary unit)
# for each class, but position_dodge only use the fraction of that unit
# indicated in the width parameter, so we need to calculate the real
# space available:
total_space_available <- 1 * position_dodge_width
# now we calculate the real bar width used by ggplot in these au, dividing the
# space available by the number of bars to plot for each class
bar_width_real <- (total_space_available / bars_per_class)
# position_dodge with discrete variables place bars to the left and to the right of the
# class au value, so we need to know when to place the xend to the left or
# to the right. Also, the number of bars has to be taken in to account, as
# in odd number of bars, one is located on the exact au value
if (bars_per_class%%2 == 0) {
# we need an offset, as bars are wider than arrows, and we want them in the
# middle of the bar
offset_segment <- bar_width_real / 2
# offset modifier to know when to substract or add the modifier
offset_modifier <- c(rep(-1, bars_per_class%/%2), rep(1, bars_per_class%/%2))
# we also need to know how meny bars to the left and how many to the right,
# but, the first bar of each side is already taken in account with the offset,
# so the bar modifier has to have one bar less for each side
bar_width_modifier <- c(seq((bars_per_class%/%2-1), 0), seq(0, (bars_per_class%/%2-1)))
} else {
# when odd number of columns, the offset is the same as the bar width
offset_segment <- bar_width_real
# and the modifiers have to have a middle zero value for the middle bar
offset_modifier <- c(rep(-1, bars_per_class%/%2), 0, rep(1, bars_per_class%/%2))
bar_width_modifier <- c(seq((bars_per_class%/%2-1), 0), 0, seq(0, (bars_per_class%/%2-1)))
}
# finally we create the vector of xend values needed:
df %>%
mutate(
numAlleles_u = as.numeric(as.factor(numAlleles)) + offset_modifier*(offset_segment + (bar_width_modifier*bar_width_real))
)
ggplot(df, aes(x = numAlleles, y = OR, fill = Outcome)) +
geom_bar(
position = position_dodge(position_dodge_width), stat = "identity",
width = 0.4, color = "black"
) +
geom_hline(yintercept = 1, linetype = "dashed", color = "black") +
ylim(0,10) +
geom_errorbar(
aes(ymin=OR.95L, ymax=OR.95U), width=.2,position=position_dodge(position_dodge_width)
) +
theme(
legend.key = element_blank(), text = element_text(size = 11.5),
legend.title = element_blank()
) +
labs(x = "Number of rare alleles") +
scale_fill_manual(values=c("chocolate1","coral1", "red2", "darkred")) +
geom_segment(
aes(x = numAlleles, xend = numAlleles_u, y = OR, yend = OR.95U_u),
position = position_dodge(position_dodge_width), arrow = arrow(length = unit(0.3, "cm"))
)
And the plot:
We can check that for three levels discrete variables also works:
df_three_bars <- df %>% filter(Outcome != 'D')
bars_per_class <- length(unique(df_three_bars$Outcome))
total_space_available <- 1 * position_dodge_width
bar_width_real <- (total_space_available / bars_per_class)
if (bars_per_class%%2 == 0) {
offset_segment <- bar_width_real / 2
offset_modifier <- c(rep(-1, bars_per_class%/%2), rep(1, bars_per_class%/%2))
bar_width_modifier <- c(seq((bars_per_class%/%2-1), 0), seq(0, (bars_per_class%/%2-1)))
} else {
offset_segment <- bar_width_real
offset_modifier <- c(rep(-1, bars_per_class%/%2), 0, rep(1, bars_per_class%/%2))
bar_width_modifier <- c(seq((bars_per_class%/%2-1), 0), 0, seq(0, (bars_per_class%/%2-1)))
}
df_three_bars <- df_three_bars %>%
mutate(
numAlleles_u = as.numeric(as.factor(numAlleles)) + offset_modifier*(offset_segment + (bar_width_modifier*bar_width_real))
)
ggplot(df_three_bars, aes(x = numAlleles, y = OR, fill = Outcome)) +
geom_bar(
position = position_dodge(position_dodge_width), stat = "identity",
width = 0.4, color = "black"
) +
geom_hline(yintercept = 1, linetype = "dashed", color = "black") +
ylim(0,10) +
geom_errorbar(
aes(ymin=OR.95L, ymax=OR.95U), width=.2,position=position_dodge(position_dodge_width)
) +
theme(
legend.key = element_blank(), text = element_text(size = 11.5),
legend.title = element_blank()
) +
labs(x = "Number of rare alleles") +
scale_fill_manual(values=c("chocolate1","coral1", "red2", "darkred")) +
geom_segment(
aes(x = numAlleles, xend = numAlleles_u, y = OR, yend = OR.95U_u),
position = position_dodge(position_dodge_width), arrow = arrow(length = unit(0.3, "cm"))
)
My data :
dat <- data.frame(x = c(1,2,3,4,5,6), y = c(2,3,4,6,2,3))
Breaks and labels of my plot :
breaks <- c(3,5)
labels <- c(paste(3,"(0.3)"), paste(5,"(0.5)"))
And my plot :
library(ggplot2)
ggplot() +
geom_point(data = dat, aes(x = x, y = y)) +
scale_y_continuous(breaks = breaks, labels = labels)
I wish to colour the same labels differently. For instance, I wish to colour the "3" with a different colour than the one of "(0.3)".
Here's a way to stick 2 plots together with patchwork, which is a package similar to cowplot but with a little more flexibility. I split the labels into 2 vectors, one with the integers and one with the decimals in parentheses. Then make 2 plots, one for the outer labels with no other markings, and one for the main plot.
After doing one round of trying to build this, I started adjusting the margins in each theme, realizing I needed to set the top and bottom margins the same, but making no margin on the right side of the left plot and the left side of the right plot, so there's very little space between them. There's definitely still ways to tweak this, but I'd start with some of the spacing.
library(tidyverse)
library(patchwork)
lbl_int <- str_extract(labels, "^\\d+")
lbl_frac <- str_extract(labels, "\\(.+\\)")
The main plot is fairly straightforward, just removing elements from the left side in the theme.
(main_plot <- ggplot(dat, aes(x = x, y = y)) +
geom_point() +
scale_y_continuous(breaks = breaks, labels = lbl_frac) +
theme(axis.text.y.left = element_text(color = "gray"),
axis.title.y.left = element_blank(),
plot.margin = margin(1, 1, 1, 0, "mm")))
The plot for the outer labels has most theme elements removed, but has the y-axis title and labels.
(int_plot <- ggplot(dat, aes(x = 0, y = y)) +
scale_y_continuous(breaks = breaks, labels = lbl_int) +
theme(axis.text.y.left = element_text(color = "black"),
axis.title.y.left = element_text(color = "black"),
axis.title.x = element_blank(),
panel.grid = element_blank(),
axis.ticks = element_blank(),
axis.text.x = element_blank(),
panel.background = element_blank(),
plot.margin = margin(1, 0, 1, 1, "mm")))
Then patchwork makes it easy to just add plots together—literally with +—and then set the widths. Again, here's something you can adjust as you need, but I made the left plot very very skinny compared to the right one.
int_plot + main_plot +
plot_layout(ncol = 2, widths = c(1e-3, 1))
Created on 2018-12-21 by the reprex package (v0.2.1)
This is something to get you going (credit to this answer which I adapted).
We use annotate to plot your labels, on two different x-axis coords, this will function as our labels (so we need to shut off the actual labelling in the theme).
First we create two vectors of the exact labels that we want in different colors.
dat <- data.frame(x = c(1,2,3,4,5,6), y = c(2,3,4,6,2,3))
breaks <- c(3,5)
labels_new1 <- c(NA, NA, 3, NA, 5, NA) # NA in order to skip that annotation
labels_new2 <- c(NA, NA, "(0.3)", NA, "(0.5)", NA)
Important parts:
coord_cartesian(xlim = c(0, 6), expand = FALSE) + # this will cut our plot properly
plot.margin = unit(c(1, 1, 1, 5), "lines") # this will give us some space on the left
Note that in coord_cartesian defined like that we are actually cutting off the two annotations (notice that the two x values you see in the next part (-1, -0.5) are outside the xlim range).
Plot object:
g1 <- ggplot() +
geom_point(data = dat, aes(x = x, y = y)) +
annotate(geom = "text", y = seq_len(nrow(dat)), x = -1, label = labels_new1, size = 4) +
#first the number add color = "blue" for example
annotate(geom = "text", y = seq_len(nrow(dat)), x = -0.5, label = labels_new2, size = 4, color = "red") +
#second the parenthesis (colored in red)
coord_cartesian(xlim = c(0, 6), expand = FALSE) +
scale_y_continuous(breaks = breaks) +
#now lets shut off the labels and give us some left space in the plot
theme(plot.margin = unit(c(1, 1, 1, 5), "lines"),
axis.title.y = element_blank(),
axis.text.y = element_blank())
Finally:
g2 <- ggplot_gtable(ggplot_build(g1)) # convert to grob
g2$layout$clip[g2$layout$name == "panel"] <- "off" # clipping of the axes
# this will show the two annotations that we left off before
grid::grid.draw(g2)
Remarks:
You can play around with x=-1 and x=-0.5 to move the two annotations, and with the last value in c(1, 1, 1, 5) to give you more space on the left side.
labels_new1 and labels_new2 are very important, they are doing all the heavy work of what and where you want to show something.
I'm looking to set up a mirrored bar chart with one set of axis labels in the middle. This image shows what I have so far (code to reproduce at the end):
I'd like the names to be centred between the charts. Methods tried:
using axis labels (best attempt shown here)
using annotation_custom (I found placing the labels to be very difficult and disliked the combination of ggplot references and base plot references)
creating a separate "chart object" to put into the grid.arrange panel (difficult to get the correct vertical spacing between labels without there being any bars)
I'd welcome any suggestions around the easiest way to achieve this layout. The base has to be ggplot, but happy to use other packages to arrange charts.
require("ggplot2")
require("gridExtra")
dataToPlot <- data.frame(
"Person" = c("Alice", "Bob", "Carlton"),
"Age" = c(14, 63, 24),
"Score" = c(73, 62.1, 21.5))
plot1 <- ggplot(dataToPlot) +
geom_bar(data = dataToPlot, aes(x = Person, y = Score), stat = "identity",
fill = "blue", width = 0.8) +
scale_y_continuous(trans = "reverse", expand = c(0, 0)) +
scale_x_discrete(position = "top") +
theme(
axis.text.y = element_blank()
) +
labs(x = NULL) +
coord_flip()
plot2 <- ggplot(dataToPlot) +
geom_bar(data = dataToPlot, aes(x = Person, y = Age), stat = "identity",
fill = "red", width = 0.8) +
scale_y_continuous(expand = c(0, 0)) +
theme(
axis.text.y = element_text(size = 20, hjust = 0.5)
) +
labs(x = "") +
coord_flip()
gridExtra::grid.arrange(plot1, plot2, ncol = 2, widths = c(1, 1.2))
There are two ways (perhaps in combination)...
Add a margin to the right of the axis labels in the right-hand chart...
element_text(size = 20, hjust = 0.5, margin=margin(r=30))
...or move the two charts closer together
grid.arrange(plot1, plot2, ncol = 2, widths = c(1, 1.2),padding=0)