How to reduce the distance between text lines in ggplot axis? - r

For one of the presentations, I am trying to make a scatter plot. Here is a similar code I am trying to run for the visualization I would like to have
library(tidyverse)
library(showtext)
library(ggtext)
ggplot(mtcars, aes(x = mpg, y = disp)) +
geom_point(size = 1.5) +
labs(title = "<span style = 'color:#005A9C;'>A vs. B</span>",
x = "B<br>BBBBB<br>BBBBBBBBBB<br>BBBBBBBBBB",
y = "A<br>AAAAA<br>AAAAAAAAAA<br>AAAAAAAAAA",
caption = expression(paste(italic("Source:"), " JJJJJ"))) +
theme_minimal() +
theme(
plot.background = element_rect(fill = "white",colour = NA),
panel.background = element_rect(fill = 'white', colour = 'white'),
panel.border = element_blank(),
legend.position = "none",
plot.title = element_markdown(hjust = 0.5, family = "title", size = 45),
plot.subtitle = element_markdown(hjust = 0.5, family = "subtitle", size = 30), # note that to color numbers differently, I used element_markdown not element_text function
axis.title.x = element_markdown(hjust = 0.5, family = "subtitle", size = 33),
axis.text.x = element_markdown(hjust = 0.5, family = "subtitle", size = 20),
axis.title.y = element_markdown(hjust = 0.5, family = "subtitle", size = 33),
axis.text.y = element_markdown(hjust = 0.5, family = "subtitle", size = 20),
plot.caption = element_text(hjust = 0, size = 21, family = "caption"))
ggsave("plot.png", height = 6, width = 7)
And here is the result;
Now, my question is how to reduce the distance between text lines for the x and y axes?

Related

Editing legend in ggplot2 - R

I'm learning to use ggplot to make graphs for my research and I'm having some trouble setting legends for them.
Initially I thought about just using the aes() function inside geom_point and geom_line to get the aesthetics I'm looking for. However, I realized the legends weren't being generated by doing it this way. Code and exemple below.
#Stablish the variables as vectors
MexxJan_hydrogen <- c(0, 1.38, 3.19, 8.30)
MexyJan_hydrogen <- c(0, 1.25, 2.78, 6.23)
MexzJan_hydrogen <- c(0, 2.46, 5.68, 12.18)
MexwJan_hydrogen <- c(0, 7.56, 9.20, 10.19)
time_hydrogen <- c(0, 60, 120, 180)
#Create the data frame
hydrogen_data <- data.frame(time_hydrogen, MexxJan_hydrogen, MexyJan_hydrogen, MexzJan_hydrogen, MexwJan_hydrogen)
view(hydrogen_data)
#Code the plot
hydrogen_plot <- ggplot(data = hydrogen_data) +
geom_line(aes(x = time_hydrogen, y = MexxJan_hydrogen), color = "palegreen3", lwd = 1) +
geom_line(aes(x = time_hydrogen, y = MexyJan_hydrogen), color = "tan1", lwd = 1) +
geom_line(aes(x = time_hydrogen, y = MexzJan_hydrogen), color = "tomato2", lwd = 1) +
geom_line(aes(x = time_hydrogen, y = MexwJan_hydrogen), color = "cadetblue", lwd = 1) +
geom_point(aes(x = time_hydrogen, y = MexxJan_hydrogen), color = "palegreen3", shape = 15, size = 5) +
geom_point(aes(x = time_hydrogen, y = MexyJan_hydrogen), color = "tan1", shape = 16, size = 5) +
geom_point(aes(x = time_hydrogen, y = MexzJan_hydrogen), color = "tomato2", shape = 17, size = 5) +
geom_point(aes(x = time_hydrogen, y = MexwJan_hydrogen), color = "cadetblue", shape = 18, size = 5) +
theme_bw() +
theme(axis.text = element_text(family = "Arial", size = 15, color = "black"),
axis.title.x = element_text(family = "Arial", size = 16, margin = margin(t = 15)),
axis.title.y = element_text(family = "Arial", size = 16, margin = margin(r = 15)),axis.line = element_line(color = "black"),
plot.background = element_rect(fill = "transparent", color = NA),
panel.border = element_rect(color = "black"),
panel.background = element_rect(fill = "transparent"),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
axis.ticks.length = unit(0.20, units = "cm"),
legend.background = element_rect(fill = "transparent"),
legend.key = element_rect(fill = "transparent", colour = NA),
legend.position = "top",
legend.key.width = unit(0, unit = "cm"),
legend.key.height = unit(0, unit = "cm"),
legend.title = element_blank(),
legend.text = element_text(size = 13.5),
legend.spacing.x = unit(0.1, "cm"),
legend.text.align = unit(0.05, unit = "cm")) +
labs(x = "Time (min)", y = "Gas Evolution (µmol.g"^-1~")") +
coord_cartesian(ylim = c(0,15), xlim = c(0,180)) +
scale_y_continuous(expand = expansion(mult = c(0.02, 0.02)),
n.breaks = 5) +
scale_x_continuous(expand = expansion(mult = c(0.02, 0.02)),
breaks = c(0, 60, 120, 180))
I then found that I could use the function scale_colors_manual to get the desired colors and show the legend. Also, using scale_colors_manual I managed to change the legend text to a shorter option. Code and exemple below.
#Stablish the variables as vectors
MexxJan_hydrogen <- c(0, 1.38, 3.19, 8.30)
MexyJan_hydrogen <- c(0, 1.25, 2.78, 6.23)
MexzJan_hydrogen <- c(0, 2.46, 5.68, 12.18)
MexwJan_hydrogen <- c(0, 7.56, 9.20, 10.19)
time_hydrogen <- c(0, 60, 120, 180)
#Create the data frame
hydrogen_data <- data.frame(time_hydrogen, MexxJan_hydrogen, MexyJan_hydrogen, MexzJan_hydrogen, MexwJan_hydrogen)
view(hydrogen_data)
hydrogen_plot <- ggplot(data = hydrogen_data) +
geom_line(aes(x = time_hydrogen, y = MexxJan_hydrogen, color = "MexxJan_hydrogen"), lwd = 1) +
geom_line(aes(x = time_hydrogen, y = MexyJan_hydrogen, color = "MexyJan_hydrogen"), lwd = 1) +
geom_line(aes(x = time_hydrogen, y = MexzJan_hydrogen, color = "MexzJan_hydrogen"), lwd = 1) +
geom_line(aes(x = time_hydrogen, y = MexwJan_hydrogen, color = "MexwJan_hydrogen"), lwd = 1) +
geom_point(aes(x = time_hydrogen, y = MexxJan_hydrogen, color = "MexxJan_hydrogen"), shape = 15, size = 5) +
geom_point(aes(x = time_hydrogen, y = MexyJan_hydrogen, color = "MexyJan_hydrogen"), shape = 16, size = 5) +
geom_point(aes(x = time_hydrogen, y = MexzJan_hydrogen, color = "MexzJan_hydrogen"), shape = 17, size = 5) +
geom_point(aes(x = time_hydrogen, y = MexwJan_hydrogen, color = "MexwJan_hydrogen"), shape = 18, size = 5) +
theme_bw() +
theme(axis.text = element_text(family = "Arial", size = 15, color = "black"),
axis.title.x = element_text(family = "Arial", size = 16, margin = margin(t = 15)),
axis.title.y = element_text(family = "Arial", size = 16, margin = margin(r = 15)),axis.line = element_line(color = "black"),
plot.background = element_rect(fill = "transparent", color = NA),
panel.border = element_rect(color = "black"),
panel.background = element_rect(fill = "transparent"),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
axis.ticks.length = unit(0.20, units = "cm"),
legend.background = element_rect(fill = "transparent"),
legend.key = element_rect(fill = "transparent", colour = NA),
legend.position = "top",
legend.key.width = unit(0, unit = "cm"),
legend.key.height = unit(0, unit = "cm"),
legend.title = element_blank(),
legend.text = element_text(size = 13.5),
legend.spacing.x = unit(0.1, "cm"),
legend.text.align = unit(0.05, unit = "cm")) +
labs(x = "Time (min)", y = "Gas Evolution (µmol.g"^-1~")") +
coord_cartesian(ylim = c(0,15), xlim = c(0,180)) + #Limit the size of the plot
scale_y_continuous(expand = expansion(mult = c(0.02, 0.02)),
n.breaks = 5) +
scale_x_continuous(expand = expansion(mult = c(0.02, 0.02)),
breaks = c(0, 60, 120, 180)) +
scale_color_manual(labels = c("15Me-NT", "15Me-nNT", "15Me-NNT", "15Me-nnt"),
values = c("MexxJan_hydrogen" = "palegreen3", "MexyJan_hydrogen" = "tan1", "MexzJan_hydrogen" = "cadetblue", "MexwJan_hydrogen" = "tomato2"))
In this case, I got the colors and the legend. However, as you can see in the image, the legend keys look like a bunch of geometric forms stacked. I couldn't find a way to solve this. Tried using scale_shape_manual but I couldn't get the code right.
May you help me getting this plot some beautiful aesthetics? hehehe
Thank you. Stay safe.

To fix your issue you have to move shape inside aes similar to what you have done for color and afterwards set your shapes via scale_shape_manual. However, you could simplify your approach considerably by first reshaping your data to long or tidy data format. Doing so allows to add your lines and points which just one geom_point and geom_line:
library(tidyr)
library(ggplot2)
hydrogen_data_long <- hydrogen_data %>%
tidyr::pivot_longer(-time_hydrogen, names_to = "hydrogren")
ggplot(hydrogen_data_long, aes(x = time_hydrogen, y = value, color = hydrogren)) +
geom_line(lwd = 1) +
geom_point(aes(shape = hydrogren), size = 5) +
scale_shape_manual(
labels = c("15Me-NT", "15Me-nNT", "15Me-NNT", "15Me-nnt"),
values = c(
"MexxJan_hydrogen" = 15, "MexyJan_hydrogen" = 16,
"MexzJan_hydrogen" = 17, "MexwJan_hydrogen" = 18
)
) +
scale_color_manual(
labels = c("15Me-NT", "15Me-nNT", "15Me-NNT", "15Me-nnt"),
values = c(
"MexxJan_hydrogen" = "palegreen3", "MexyJan_hydrogen" = "tan1",
"MexzJan_hydrogen" = "cadetblue", "MexwJan_hydrogen" = "tomato2"
)
) +
theme_bw() +
theme(
axis.text = element_text(family = "Arial", size = 15, color = "black"),
axis.title.x = element_text(family = "Arial", size = 16, margin = margin(t = 15)),
axis.title.y = element_text(family = "Arial", size = 16, margin = margin(r = 15)),
axis.line = element_line(color = "black"),
plot.background = element_rect(fill = "transparent", color = NA),
panel.border = element_rect(color = "black"),
panel.background = element_rect(fill = "transparent"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.ticks.length = unit(0.20, units = "cm"),
legend.background = element_rect(fill = "transparent"),
legend.key = element_rect(fill = "transparent", colour = NA),
legend.position = "top",
legend.key.width = unit(0, unit = "cm"),
legend.key.height = unit(0, unit = "cm"),
legend.title = element_blank(),
legend.text = element_text(size = 13.5),
legend.spacing.x = unit(0.1, "cm"),
legend.text.align = unit(0.05, unit = "cm")
) +
labs(x = "Time (min)", y = "Gas Evolution (µmol.g"^-1 ~ ")") +
coord_cartesian(ylim = c(0, 15), xlim = c(0, 180)) + # Limit the size of the plot
scale_y_continuous(
expand = expansion(mult = c(0.02, 0.02)),
n.breaks = 5
) +
scale_x_continuous(
expand = expansion(mult = c(0.02, 0.02)),
breaks = c(0, 60, 120, 180)
)

You are making life harder for yourself by passing your data frame in the wrong format. If you pivot to long format, you only need a single geom_line and geom_point. It's also far easier to map your colors and shapes, which will automatically appear in the legend.
Also, try to choose a default theme that's closer to the look you want to achieve to cut down on the number of tweaks you have to make via theme. One of the key things you'll learn in R, as in other languages, is that cutting down code to a minimum makes it easier to change or debug your code later on.
library(tidyverse)
hydrogen_data %>%
pivot_longer(-time_hydrogen) %>%
ggplot(aes(time_hydrogen, value, color = name, shape = name)) +
geom_line(lwd = 1) +
geom_point(size = 5) +
scale_color_manual(values = c("tomato2", "palegreen", "tan1", "cadetblue"),
labels = paste0("15Me-", c("NT", "nNT", "NNT", "nnt"))) +
scale_shape_manual(values = c(18, 15, 16, 17),
labels = paste0("15Me-", c("NT", "nNT", "NNT", "nnt"))) +
scale_y_continuous(expression(Gas~Evolution~(µmol.g^-1)),
expand = expansion(mult = c(0.02, 0.02)), n.breaks = 5) +
scale_x_continuous("Time (min)", expand = expansion(mult = c(0.02, 0.02)),
breaks = c(0, 60, 120, 180)) +
theme_classic(base_size = 16) +
theme(axis.text = element_text(family = "Arial", size = 15, color = "black"),
plot.background = element_blank(),
panel.border = element_rect(color = "black", fill = NA),
panel.background = element_blank(),
axis.ticks.length = unit(0.20, units = "cm"),
legend.background = element_blank(),
legend.position = "top",
legend.title = element_blank()) +
coord_cartesian(ylim = c(0, 15), xlim = c(0, 180))

Facet_Wrap title overlapping with y-axis in ggplotly?

I am currently using a facet_wrap to knit data (html) to an Rmarkdown document. I am looking to use facet_wrap and ggplot to show this data.
This is how the data looks just in ggplot (not plotly):
However, when I use plotly the titles of each plot intersect with the y-axis making interpretability difficult
Here is the code to the first plot not using plotly
plot <- ggplot(dataframe, aes(x = week, y = measure))+
geom_line(size = 1.25, aes(color = "orange"))+
geom_point(size = 1.50)+
theme_economist()+
geom_smooth(method = 'auto', se = FALSE, size = .50)+
scale_x_continuous(breaks=seq(0,13,1))+
scale_y_continuous(labels = scales::dollar_format(scale = .0001, suffix = "K"))+
facet_wrap(vars(category), scales = "free", ncol = 3, nrow = 6)+
theme(legend.position = "none")+
ggtitle('Title')+
theme(
panel.grid.major = element_line(linetype = "dotted"),
axis.title.x = element_text( size = 10, margin=margin(30,0,0,0)),
axis.title.y = element_text( size = 10, margin=margin(0,30,0,0)),
axis.text = element_text( size = 10),
plot.title = element_text( size = 14, margin=margin(0,0,35,0), hjust = 0.5),
panel.background = element_rect(fill = NA),
strip.text = element_text(size=10)
)
Then here is what I do to conver it to plotly
ggplotly(plot)

Some random data:
require(stats)
r <- function(x) {abs(as.numeric(arima.sim(n=x, list(order=c(1,0,0),ar=0.95)))+10)}
dataframe = data.frame(week = rep(1:13,6), measure = r(13*6), category = rep(as.character(1:6),each=13))
Although I was not able to reproduce the overlapping y-axis labels, you can set the margins between the faceted plots by setting panel.margin.y and panel.margin.x inside the theme():
plot <- ggplot(dataframe, aes(x = week, y = measure))+
geom_line(size = 1.25, aes(color = "orange"))+
geom_point(size = 1.50)+
theme_economist() +
geom_smooth(method = 'auto', se = FALSE, size = .50)+
scale_x_continuous(breaks=seq(0,13,1))+
scale_y_continuous(labels = scales::dollar_format(scale = .0001, suffix = "K"))+
facet_wrap(vars(category), scales = "free", ncol = 3, nrow = 6)+
theme(legend.position = "none")+
ggtitle('Title')+
theme(
panel.grid.major = element_line(linetype = "dotted"),
axis.title.x = element_text( size = 10, margin=margin(30,0,0,0)),
axis.title.y = element_text( size = 10, margin=margin(0,30,0,0)),
axis.text = element_text( size = 10),
plot.title = element_text( size = 14, margin=margin(0,0,35,0), hjust = 0.5),
panel.background = element_rect(fill = NA),
strip.text = element_text(size=10), panel.margin.x = unit(1,"lines"), panel.margin.y = unit(0,"lines")
)
ggplotly(plot)
You can fine tune the margins to suit your plot.
Before:
> ggplotly(plot)
After:
> ggplotly(plot)

Pie chart and Bar chart aligned on same plot

After seeing this question on how to recreate this graph from the economist in ggplot2, I decided to attempt this myself from scratch (since no code or data was provided), as I found this quite interesting.
Here is what I have managed to do so far:
I was able to do this with relative ease. However, I am struggling with putting pie charts. Because ggplot uses cartesian coordinates to make pie charts, I can't have bars and pies on the same graph. So I discovered geom_arc_bar() from ggforce, which does allow pies on cartesian coordinate system. However, the issue is with coord_fixed(). I can get the pies to align but I cannot get the circular shape without coord_fixed(). However, with coord_fixed(), I can't get the graph to match the height of Economist graph. Without coord_fixed() I can, but the pies are ovals rather than circles. See below:
With coord_fixed():
Without coord_fixed():
The other option that I have tried is to make a series of pie charts separately and then combine the plots together. However, I struggled to get the plots aligned with gridExtra and other alternatives. I did combining with paint. Obviously this works, but is not programmatic. I need a solution that is 100% based in R.
My solution with pasting separate images from R in paint:
Anybody with a solution to this problem? I think it is an interesting question to answer and I have provided a starting point. I am open to any suggestions, also feel free to suggest an entirely different approach, as I acknowledge that mine is not the best. Thanks!
CODE:
# packages
library(data.table)
library(dplyr)
library(forcats)
library(ggplot2)
library(ggforce)
library(ggnewscale)
library(ggtext)
library(showtext)
library(stringr)
# data
global <- fread("Sector,ROE,Share,Status
Technology,14.2,10,Local
Technology,19,90,Multinational
Other consumer,16.5,77,Multinational
Other consumer,20.5,23,Local
Industrial,13,70,Multinational
Industrial,18,30,Local
Cyclical consumer,12,77,Multinational
Cyclical consumer,21,23,Local
Utilities,6,88,Local
Utilities,11,12,Multinational
All sectors,10,50,Local
All sectors,10.2,50,Multinational
Financial,6,27,Multinational
Financial,10.5,73,Local
Diversified,4.9,21,Local
Diversified,5,79,Multinational
Basic materials,4,82,Multinational
Basic materials,9,18,Local
Media & communications,3,76,Multinational
Media & communications,14,24,Local
Energy,-1,40,Local
Energy,1,60,Multinational
")
equity <- global %>%
group_by(Sector) %>%
mutate(xend = ifelse(min(ROE) > 0, 0, min(ROE)))
equity$Sector <- factor(equity$Sector, levels= rev(c("Technology", "Other consumer",
"Industrial", "Cyclical consumer",
"Utilities", "All sectors", "Financial",
"Diversified", "Basic materials",
"Media & communications", "Energy")))
equity$Status <- factor(equity$Status, levels = c("Multinational", "Local"))
# fonts
font_add_google("Montserrat", "Montserrat")
font_add_google("Roboto", "Roboto")
# scaling text for high res image
img_scale <- 5.5
# graph
showtext_auto() # for montserrat font to show
economist <- ggplot(equity)+
geom_vline(aes(xintercept = -2.5, color = "+-"), show.legend = FALSE)+
geom_vline(aes(xintercept = 2.5, color = "+-"), show.legend = FALSE)+
geom_segment(aes(x = ROE, xend = xend, y = Sector, yend = Sector, color = "line"),
show.legend = FALSE, size = 2)+
geom_tile(aes(x = ROE, y = Sector, width = 1, height = 0.5, fill = Status),
size = 0.5)+
geom_vline(aes(xintercept = 0, color = "x-axis"), show.legend = FALSE)+
scale_fill_manual("", values = c("Local" = "#ea5f47", "Multinational" = "#0a5268"))+
scale_color_manual(values = c("x-axis" = "red", "+-" = "#cddee6", "line" = "#a8adb3"))+
scale_x_continuous(position = "top", limits = c(-5, 25),
breaks = c(-5, -2.5, 0, 2.5, 5,10,15,20,25),
labels = c(5, "-", 0, "+", 5,10,15,20,25),
minor_breaks = c(-2.5, 2.5)
)+
scale_y_discrete(labels = function(x) str_replace_all(x, "& c" , "&\nc"))+
#width = 40))+
labs(x = "", y = "", caption = c("Sources: Bloomberg;",
"The Economist",
"<span style='font-size:80px;
color:#292929;'><sup>*</sup></span>Top 500 global companies"))+
ggtitle("The price of being global",
subtitle = "Return on equity<span style='font-size:80px;color:#292929;'>*</span>, latest 12 months, %")+
theme(legend.position = "top",
legend.direction = "vertical",
legend.justification = -1.25,
legend.key.size = unit(0.18, "cm"),
legend.key.height = unit(0.1, "cm"),
legend.background = element_rect("#cddee6"),
legend.text = element_text("Montserrat", size = 9 * img_scale),
plot.background = element_rect("#cddee6"),
plot.margin = margin(t = 10, r = 10, b = 20, l = 10),
panel.background = element_rect("#cddee6"),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.minor.x = element_blank(),
axis.ticks = element_blank(),
axis.text = element_text(family = "Montserrat", size = 9 * img_scale,
colour = "black"),
axis.text.y = element_text(hjust = 0, lineheight = 0.15,
face = c(rep("plain",5), "bold.italic", rep("plain",5))
),
#axis.text.x = element_text(family = "Montserrat", size = 9*img_scale,)
plot.title = element_text(family = "Montserrat", size = 12 * img_scale,
face = "bold",
hjust = -34.12),
text = element_text(family = "Montserrat"),
plot.subtitle = element_markdown(family = "Montserrat", size = 9 * img_scale,
hjust = 7.5),
plot.caption = element_markdown(size = 9*img_scale,
face = c("plain", "italic", "plain"),
hjust = c(-1.35, -1.85, -2.05),
vjust = c(0,0.75,0)))
# only way to get google fonts on plot (R device does not show them)
png("bar.png", height = 480*8, width = 250*8, res = 72*8) # increased resolution (dpi)
economist
dev.off()
# piechart
pies <- equity %>%
mutate(Sector = fct_rev(Sector)) %>%
ggplot(aes(x = "", y = Share, fill = Status, width = 0.15)) +
geom_bar(stat = "identity", position = position_fill(), show.legend = FALSE, size = 0.1) +
# geom_text(aes(label = Cnt), position = position_fill(vjust = 0.5)) +
coord_polar(theta = "y", direction = -1) +
facet_wrap(~ Sector, dir = "v", ncol = 1) +
scale_fill_manual("", values = c("Local" = "#93b7c7", "Multinational" = "#08526b"))+
#theme_void()+
theme(panel.spacing = unit(-0.35, "lines"),
plot.background = element_rect("#cddee6"),
panel.background = element_rect("transparent"),
strip.text = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
legend.position='none',
axis.ticks = element_blank(),
axis.text = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
# guides(fill=guide_legend(nrow=2, byrow=TRUE))
png("pie_chart.png", height = 350*8, width = 51*8, res = 72*8)
pies
dev.off()
# geom_bar_arc (ggforce) with coord_fixed - cannot match height but pies are circular
eco_circle_pies <- ggplot(equity)+
geom_vline(aes(xintercept = -2.5, color = "+-"), show.legend = FALSE)+
geom_vline(aes(xintercept = 2.5, color = "+-"), show.legend = FALSE)+
geom_segment(aes(x = ROE, xend = xend, y = Sector, yend = Sector, color = "line"),
show.legend = FALSE, size = 1)+
scale_fill_manual("", values = c("Local" = "#ea5f47", "Multinational" = "#0a5268"))+
geom_tile(aes(x = ROE, y = Sector, width = 1, height = 0.5, fill = Status),
size = 0.5, show.legend = TRUE)+
geom_vline(aes(xintercept = 0, color = "x-axis"), show.legend = FALSE)+
new_scale_fill()+
geom_arc_bar(aes(x0 = 27, y0 = as.numeric(equity$Sector), r0 = 0, r = 0.45,
amount = Share,
fill = Status),
stat = 'pie',
color = "transparent",
show.legend = FALSE)+
coord_fixed()+
scale_fill_manual("", values = c("Local" = "#93b7c7", "Multinational" = "#08526b"))+
scale_color_manual(values = c("x-axis" = "red", "+-" = "#cddee6", "line" = "#a8adb3"))+
scale_x_continuous(position = "top", limits = c(-5, 30),
breaks = c(-5, -2.5, 0, 2.5, 5,10,15,20,25),
labels = c(5, "-", 0, "+", 5,10,15,20,25),
minor_breaks = c(-2.5, 2.5)
)+
scale_y_discrete(labels = function(x) str_replace_all(x, "& c" , "&\nc"))+
# below is to get * superscript
labs(x = "", y = "", caption = c("Sources: Bloomberg;",
"<span style='font-style:italic;font-color:#292929'>The Economist</span>",
"<span style='font-size:80px;
color:#292929;'><sup>*</sup></span>Top 500 global companies"))+ # this is to get
ggtitle("The price of being global",
subtitle = "Return on equity<span style='font-size:80px;color:#292929;'>*</span>, latest 12 months, %")+
guides(color = FALSE)+
theme(legend.position = "top",
legend.direction = "vertical",
# legend.justification = -0.9,
legend.key.size = unit(0.18, "cm"),
legend.key.height = unit(0.1, "cm"),
legend.background = element_rect("#cddee6"),
legend.text = element_text("Montserrat", size = 9 * img_scale),
plot.background = element_rect("#cddee6"),
# plot.margin = margin(t = -80, r = 10, b = -20, l = 10),
panel.background = element_rect("#cddee6"),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.minor.x = element_blank(),
axis.ticks = element_blank(),
axis.text = element_text(family = "Montserrat", size = 9 * img_scale,
colour = "black"),
axis.text.y = element_text(hjust = 0, lineheight = 0.15),
#axis.text.x = element_text(family = "Montserrat", size = 9*img_scale,)
plot.title = element_text(family = "Montserrat", size = 12 * img_scale,
hjust = -2.12),
plot.subtitle = element_markdown(family = "Montserrat", size = 9 * img_scale,
hjust = -5.75),
plot.caption = element_markdown(size = 9*img_scale,
face = c("plain", "italic", "plain"),
#hjust = c(-.9, -1.22, -1.95),
#vjust = c(0,0.75,0)))
))
png("eco_circle_pies.png", height = 220*8, width = 420*8, res = 72*8)
eco_circle_pies
dev.off()
# geom_bar_arc (ggforce) without coord_fixed - matches height, but pies are oval
eco_oval_pie <- ggplot(equity)+
geom_vline(aes(xintercept = -2.5, color = "+-"), show.legend = FALSE)+
geom_vline(aes(xintercept = 2.5, color = "+-"), show.legend = FALSE)+
geom_segment(aes(x = ROE, xend = xend, y = Sector, yend = Sector, color = "line"),
show.legend = FALSE, size = 1)+
scale_fill_manual("", values = c("Local" = "#ea5f47", "Multinational" = "#0a5268"))+
geom_tile(aes(x = ROE, y = Sector, width = 1, height = 0.5, fill = Status),
size = 0.5, show.legend = TRUE)+
geom_vline(aes(xintercept = 0, color = "x-axis"), show.legend = FALSE)+
new_scale_fill()+
geom_arc_bar(aes(x0 = 27, y0 = as.numeric(equity$Sector), r0 = 0, r = 0.45,
amount = Share,
fill = Status),
stat = 'pie',
color = "transparent",
show.legend = FALSE)+
# coord_fixed()+
scale_fill_manual("", values = c("Local" = "#93b7c7", "Multinational" = "#08526b"))+
scale_color_manual(values = c("x-axis" = "red", "+-" = "#cddee6", "line" = "#a8adb3"))+
scale_x_continuous(position = "top", limits = c(-5, 30),
breaks = c(-5, -2.5, 0, 2.5, 5,10,15,20,25),
labels = c(5, "-", 0, "+", 5,10,15,20,25),
minor_breaks = c(-2.5, 2.5)
)+
scale_y_discrete(labels = function(x) str_replace_all(x, "& c" , "&\nc"))+
#width = 40))+
labs(x = "", y = "", caption = c("Sources: Bloomberg;",
"<span style='font-style:italic;font-color:#292929'>The Economist</span>",
"<span style='font-size:80px;
color:#292929;'><sup>*</sup></span>Top 500 global companies"))+
ggtitle("The price of being global",
subtitle = "Return on equity<span style='font-size:80px;color:#292929;'>*</span>, latest 12 months, %")+
guides(color = FALSE)+
theme(legend.position = "top",
legend.direction = "vertical",
legend.justification = -1.1,
legend.key.size = unit(0.18, "cm"),
legend.key.height = unit(0.1, "cm"),
legend.background = element_rect("#cddee6"),
legend.text = element_text("Montserrat", size = 9 * img_scale),
plot.background = element_rect("#cddee6"),
# plot.margin = margin(t = -80, r = 10, b = -20, l = 10),
panel.background = element_rect("#cddee6"),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.minor.x = element_blank(),
axis.ticks = element_blank(),
axis.text = element_text(family = "Montserrat", size = 9 * img_scale,
colour = "black"),
axis.text.y = element_text(hjust = 0, lineheight = 0.15),
text = element_text(family = "Montserrat"),
plot.title = element_text(family = "Montserrat", size = 12 * img_scale,
face = "bold",
hjust = -7.05),
plot.subtitle = element_markdown(family = "Montserrat", size = 9 * img_scale,
hjust = 53.75),
plot.caption = element_markdown(size = 9*img_scale,
face = c("plain", "italic", "plain"),
hjust = c(-1.15, -1.58, -1.95),
vjust = c(0.5,1.15,0.5)))
png("eco_oval_pies.png", height = 480*8, width = 250*8, res = 72*8)
eco_oval_pie
dev.off()

Indeed an interesting problem. In my opinion the easiest way to get your desired result is to create two separate plots and to glue them together using the wonderful patchwork package:
Note: To focus on the main issue and to make the code more minimal I dropped all or most of your theme adjustments, ggtext styling, custom fonts, ... . Instead I relied on ggthemes::theme_economist to get close to the economist look.
# packages
library(data.table)
library(dplyr)
library(stringr)
library(forcats)
library(ggplot2)
library(patchwork)
library(ggthemes)
bars <-ggplot(equity)+
geom_vline(aes(xintercept = -2.5, color = "+-"), show.legend = FALSE)+
geom_vline(aes(xintercept = 2.5, color = "+-"), show.legend = FALSE)+
geom_segment(aes(x = ROE, xend = xend, y = Sector, yend = Sector, color = "line"),
show.legend = FALSE, size = 2)+
geom_tile(aes(x = ROE, y = Sector, width = 1, height = 0.5, fill = Status),
size = 0.5)+
geom_vline(aes(xintercept = 0, color = "x-axis"), show.legend = FALSE)+
scale_fill_manual("", values = c("Local" = "#ea5f47", "Multinational" = "#0a5268"))+
scale_color_manual(values = c("x-axis" = "red", "+-" = "#cddee6", "line" = "#a8adb3"))+
scale_x_continuous(position = "top", limits = c(-5, 25),
breaks = c(-5, -2.5, 0, 2.5, 5,10,15,20,25),
labels = c(5, "-", 0, "+", 5,10,15,20,25),
minor_breaks = c(-2.5, 2.5)
)+
scale_y_discrete(labels = function(x) str_replace_all(x, "& c" , "&\nc"))+
labs(x = "", y = "") +
ggthemes::theme_economist() +
theme(legend.position = "top", legend.justification = "left")
pies <- equity %>%
mutate(Sector = fct_rev(Sector)) %>%
ggplot(aes(x = "", y = Share, fill = Status, width = 0.15)) +
geom_bar(stat = "identity", position = position_fill(), show.legend = FALSE, size = 0.1) +
coord_polar(theta = "y", direction = -1) +
facet_wrap(~ Sector, dir = "v", ncol = 1) +
scale_fill_manual("", values = c("Local" = "#93b7c7", "Multinational" = "#08526b")) +
labs(x = NULL, y = NULL) +
ggthemes::theme_economist() +
theme(strip.text = element_blank(), panel.spacing.y = unit(0, "pt"),
axis.text = element_blank(), , axis.ticks = element_blank(), axis.line = element_blank(),
panel.grid.major = element_blank())
bars + pies +
plot_layout(widths= c(5, 1)) +
plot_annotation(caption = c("Sources: Bloomberg;",
"The Economist", "Top 500 global companies"),
title = "The price of being global",
subtitle = "Return on equity, latest 12 months, %",
theme = theme_economist())

Here's a base figure
global <- read.csv(strip.white = TRUE, text = "Sector,ROE,Share,Status
Technology,14.2,10,Local
Technology,19,90,Multinational
Other consumer,16.5,77,Multinational
Other consumer,20.5,23,Local
Industrial,13,70,Multinational
Industrial,18,30,Local
Cyclical consumer,12,77,Multinational
Cyclical consumer,21,23,Local
Utilities,6,88,Local
Utilities,11,12,Multinational
All sectors,10,50,Local
All sectors,10.2,50,Multinational
Financial,6,27,Multinational
Financial,10.5,73,Local
Diversified,4.9,21,Local
Diversified,5,79,Multinational
Basic materials,4,82,Multinational
Basic materials,9,18,Local
Media & communications,3,76,Multinational
Media & communications,14,24,Local
Energy,-1,40,Local
Energy,1,60,Multinational")
global <- within(global, {
Sector <- factor(Sector, unique(Sector))
Status <- factor(Status, unique(Status))
})
global <- global[order(global$Sector, global$Status), ]
f <- function(x, y, z, col, lbl, xat) {
all <- grepl('All', lbl)
par(mar = c(0, 0, 0, 0))
pie(rev(z), labels = '', clockwise = TRUE, border = NA, col = rev(col))
par(mar = c(0, 10, 0, 0))
plot.new()
plot.window(range(xat), c(-1, 1))
abline(v = xat, col = 'white', lwd = 3)
abline(v = 0, col = 'tomato3', lwd = 3)
segments(min(c(x, 0)), 0, max(x), 0, ifelse(all, 'grey50', 'grey75'), lwd = 7, lend = 1)
text(grconvertX(0.05, 'ndc'), 0, paste(strwrap(lbl, 15), collapse = '\n'),
xpd = NA, adj = 0, cex = 2, font = 1 + all * 3)
for (ii in 1:2)
segments(x[ii], -y / 2, x[ii], y / 2, col = col[ii], lwd = 7, lend = 1)
}
pdf('~/desktop/fig.pdf', height = 10, width = 7)
layout(
matrix(rev(sequence(nlevels(global$Sector) * 2)), ncol = 2, byrow = TRUE),
widths = c(5, 1)
)
cols <- c(Local = '#ea5f47', Multinational = '#08526b')
op <- par(bg = '#cddee6', oma = c(5, 6, 15, 0))
sp <- rev(split(global, global$Sector))
for (x in sp)
f(x$ROE, 1, x$Share, cols, x$Sector[1], -1:5 * 5)
axis(3, lwd = 0, cex.axis = 2)
cols <- rev(cols)
legend(
grconvertX(0.05, 'ndc'), grconvertY(0.91, 'ndc'), paste(names(cols), 'firms'),
border = NA, fill = cols, bty = 'n', xpd = NA, cex = 2
)
text(
grconvertX(0.05, 'ndc'), grconvertY(c(0.96, 0.925), 'ndc'),
c('The price of being global', 'Return on equity*, latest 12 months, %'),
font = c(2, 1), adj = 0, cex = c(3, 2), xpd = NA
)
text(
grconvertX(0.05, 'ndc'), grconvertY(0.03, 'ndc'),
'Sources: Bloomberg;\nThe Economist', xpd = NA, adj = 0, cex = 1.5
)
text(
grconvertX(0.95, 'ndc'), grconvertY(0.03, 'ndc'),
'*Top 500 global companies', xpd = NA, adj = 1, cex = 1.5
)
box('outer')
par(op)
dev.off()

How to properly format percentage plot axis labels and bars in ggplot2

I've got a dataframe I imported from SPSS into R, and I'm having trouble properly formatting the y axis in a ggplot2 percentage bar chart.
I need to constrain the axis range to a smaller amount and also lengthen those bars. This is what I keep getting:
Here's the code for the above visualization:
#import packages
library(foreign)
library(ggthemes)
library(stringr)
library(ggplot2)
library(scales)
#read in data
WBGC <- read.spss("2019.07.14_Cleaned.Data.sav", use.value.label=TRUE, to.data.frame=TRUE)
#define member/non-member datasets
WBGC_members <- subset(WBGC, Freq.Of.Attendance == 'Once a month' | Freq.Of.Attendance == 'A few times a month' | Freq.Of.Attendance == 'Once or twice a week' | Freq.Of.Attendance == '3-5 days a week')
#visualization of race
student_race <- ggplot(data = WBGC_members, aes(x = Race, fill = Gender))
+ theme_hc()
+ geom_bar(colour = "black", stat = "count", aes(y = prop.table(stat(count))), position = position_dodge(), size = 0.5)
+ labs(title = "Student Race", y = "Frequency")
+ scale_y_continuous(labels = percent)
+ geom_label(data = WBGC_members, stat = 'count', aes(label = scales::percent(prop.table(stat(count))), vjust = -0.4, fontface = 'bold'), size = 6, position = position_dodge(0.9), alpha = 1.0, show.legend = FALSE)
+ theme(
plot.title = element_text(size = 16, face = 'bold', family = '', color = 'black', hjust = 0.5, lineheight = 1.2),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 12, angle = 45, vjust = 0.5),
axis.title.y = element_text(size = 14, margin = margin(t = 0, r = 8, b = 0, l = 0)),
axis.text.y = element_text(size = 12),
legend.title = element_text(size = 14, color = "black", face="bold", hjust = 1, lineheight = 4),
legend.text = element_text(size = 13),
legend.position = 'right',
legend.box.background = element_rect(colour = 'black')
)
student_race
Since it looks like the labels are doing OK, I added scales::percent to the aes y= argument in geom_bar and had to delete the scale_y_continuous function. I wound up with this:
Any help is much appreciated. Thanks!

Fixed by adding y = prop.table(stat(count)) to the geom_label function call.
Here's the result:
And final code for reference:
student_race <- ggplot(data = WBGC_members, aes(x = Race, fill = Gender)) +
theme_hc()+
geom_bar(colour = "black", stat = "count", aes(y = prop.table(stat(count))), position = position_dodge(), size = 0.5) +
geom_label(data = WBGC_members, stat = 'count', aes(label = scales::percent(prop.table(stat(count))), y = prop.table(stat(count)), vjust = -0.4, fontface = 'bold'), size = 6, position = position_dodge(0.9), alpha = 1.0, show.legend = FALSE) +
labs(title = "Student Race", y = "Frequency") +
scale_y_continuous(labels = scales::percent, limits = c(0,0.2)) +
theme(plot.title = element_text(size = 16, face = 'bold', family = '', color = 'black', hjust = 0.5, lineheight = 1.2),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 12, angle = 45, vjust = 0.5),
axis.title.y = element_text(size = 14, margin = margin(t = 0, r = 8, b = 0, l = 0)),
axis.text.y = element_text(size = 12),
legend.title = element_text(size = 14, color = "black", face="bold", hjust = 1, lineheight = 4),
legend.text = element_text(size = 13),
legend.position = 'right',
legend.box.background = element_rect(colour = 'black')
)
student_race

Adjusting space between legend text and boxes after coord_flip() in ggplot

I am trying to move the legend text and legend boxes further apart (horizontally) on a box and jitter plot. The complicating factor is the coord_flip I used to make the boxplot horizontal. In theme I tried using both legend.spacing.x and legend.spacing.y but neither had any effect on the distance between legend text and legend boxes.
Here is the graph with fake data. More complex than necessary I know but I need to be able to make it work with all the complications.
library(dplyr)
library(ggplot2)
set.seed(01234)
# make some data
totDays <- data.frame(id = 1:80,
group = rep(c("Placebo", "Drug"), each = 40),
total84 = c(pmin(abs(round(rnorm(40, 55, 30))),84), pmin(abs(round(rnorm(40, 38, 30))),84)))
# get some descriptives
(groupDF <- totDays %>% group_by(group) %>%
dplyr::summarise(m = mean(total84, na.rm = T),
sd = sd(total84, na.rm = T),
count = n()) %>%
mutate(se = sd/sqrt(count)))
# now for the box and scatter plot
(g <- ggplot(totDays, aes(group, total84, colour = group)) +
geom_jitter(size = 1, width = 0.1) + # so points aren't overlaid, width controls how much jitter
geom_point(stat = "summary", fun.y = "mean", shape = 3, size = 3, colour = "black") + # crosses for mean
geom_boxplot(alpha = 0, width = 0.5, lwd = 1, size = 0.5) +
scale_color_manual(values = c("#00AFBB", "#E7B800")) +
scale_y_continuous(breaks = seq(0,84,14), minor_breaks = seq(0, 84, 14)) + # changes minor break line
coord_flip() +
labs(y = "Score") +
geom_hline(yintercept = c(groupDF$m), linetype = "dotted") +
geom_segment(x = 2.38, xend = 2.38, y = groupDF$m[2] + .1, yend = groupDF$m[1] - .1, size = .7, arrow = arrow(end = "both", type = "open", length = unit(0.15, "cm")), colour = "#696969") +
annotate("text", x = 2.46, y = mean(groupDF$m), label = paste0("italic(p) == ", 0.02), parse = T) +
theme_bw() +
theme(axis.title.y = element_blank(),
axis.ticks.y = element_blank(),
axis.text.y = element_blank(),
axis.text.x = element_text(size = 13),
axis.title.x = element_text(size = 13, face = "bold", margin = margin(t = 0, r = 0, b = 10, l = 0), vjust = -2), # note the use of margin to move the title away from the axis text
legend.title = element_blank(),
legend.position = "top",
legend.spacing.y = unit(.1, "cm"),
legend.box.spacing = unit(.1, "cm"), # adjusts distance of box from x-axis
legend.key.size = unit(1, "cm"),
legend.text = element_text(size = 13, face = "bold"),
strip.text = element_text(size = 13, face = "bold"),
panel.grid.major.y = element_blank(),
panel.grid.major.x = element_line(size=.4, color="#F7F7F7")))

Use either stringr::str_pad() or theme(legend.spacing.x = ...) or both
g <- ggplot(totDays, aes(group, total84, colour = group)) +
geom_jitter(size = 1, width = 0.1) + # so points aren't overlaid, width controls how much jitter
geom_point(stat = "summary", fun.y = "mean", shape = 3, size = 3, colour = "black") + # crosses for mean
geom_boxplot(alpha = 0, width = 0.5, lwd = 1, size = 0.5) +
scale_color_manual(values = c("#00AFBB", "#E7B800"),
### added
labels = stringr::str_pad(c("Drug", "Placebo"), 10, "right")) +
scale_y_continuous(breaks = seq(0,84,14), minor_breaks = seq(0, 84, 14)) + # changes minor break line
coord_flip() +
labs(y = "Score") +
geom_hline(yintercept = c(groupDF$m), linetype = "dotted") +
geom_segment(x = 2.38, xend = 2.38, y = groupDF$m[2] + .1, yend = groupDF$m[1] - .1, size = .7,
arrow = arrow(end = "both", type = "open", length = unit(0.15, "cm")), colour = "#696969") +
annotate("text", x = 2.46, y = mean(groupDF$m), label = paste0("italic(p) == ", 0.02), parse = T) +
theme_bw() +
theme(axis.title.y = element_blank(),
axis.ticks.y = element_blank(),
axis.text.y = element_blank(),
axis.text.x = element_text(size = 13),
axis.title.x = element_text(size = 13, face = "bold",
margin = margin(t = 0, r = 0, b = 10, l = 0), vjust = -2),
legend.title = element_blank(),
legend.position = "top",
### added
legend.spacing.x = unit(0.25, 'cm'),
legend.spacing.y = unit(.1, "cm"),
legend.box.spacing = unit(.1, "cm"), # adjusts distance of box from x-axis
legend.key.size = unit(1, "cm"),
legend.text = element_text(size = 13, face = "bold"),
strip.text = element_text(size = 13, face = "bold"),
panel.grid.major.y = element_blank(),
panel.grid.major.x = element_line(size=.4, color="#F7F7F7"))
Created on 2019-03-11 by the reprex package (v0.2.1.9000)

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