ggplot2 align fun.data in stat_summary - r

Let
df <- data.frame("Method" = rep(c("Method1", "Method2", "Method3", "Method4", "Method5"), each = 3, times = 1),
"Type" = rep(c("A", "B", "C"), 5),
"Value" = c(runif(5, 0, 1), runif(5, 0.2, 1.2), runif(5, 0.4, 1.4)))
I created a boxplot
get_box_stats <- function(y, upper_limit = max(df$Value) * 1.42) {
return(data.frame(
y = upper_limit,
label = paste(
length(y), "\n",
round(quantile(y, 0.25), 2), "\n",
round(median(y), 2), "\n",
round(quantile(y, 0.75), 2), "\n"
)
))
}
ggplot(df, aes(factor(Type), Value)) +
labs(fill = "Method") +
stat_summary(size = 4.6, fun.data = get_box_stats, geom = "text", position = position_dodge(.9),
hjust = 0.5, vjust = 1, aes(group = factor(Type)))+
geom_boxplot(coef = 0, aes(fill = factor(Type))) + theme_classic()+
theme(legend.position = "top", axis.text.x = element_text(size = 15),
axis.text.y = element_text(size = 15),
axis.title.x = element_text(size = 15),
axis.title.y = element_text(size = 15),
legend.title=element_text(size = 15),
legend.text=element_text(size = 15)) +
geom_dotplot(aes(fill = factor(Type)), dotsize = 0.8, binaxis = 'y', stackdir = 'center',
position = position_dodge(0.75))+
xlab("Method")
This results in a boxplot
QUESTION: As you can see, for stats are not perfectly centered, i.e for Method B -- values 1 and 5. Is there a way to fix this?


The problem lies in your use of paste in your summary function. By default, paste adds a space character between each element you want to paste together. Your summary string therefore has a space before and after every line break, but not before the first line. Since a space takes up some room, the aligment is off. Instead of adding in all those newline characters, specify that you want to use just a newline character as a separator using the sep argument:
get_box_stats <- function(y, upper_limit = max(df$Value) * 1.42) {
return(data.frame(
y = upper_limit,
label = paste(
length(y),
round(quantile(y, 0.25), 2),
round(median(y), 2),
round(quantile(y, 0.75), 2), sep = "\n"
)
))
}
ggplot(df, aes(factor(Type), Value)) +
labs(fill = "Method") +
stat_summary(size = 4.6, fun.data = get_box_stats, geom = "text",
hjust = 0.5, vjust = 1, aes(group = factor(Type)))+
geom_boxplot(coef = 0, aes(fill = factor(Type))) + theme_classic()+
theme(legend.position = "top", axis.text.x = element_text(size = 15),
axis.text.y = element_text(size = 15),
axis.title.x = element_text(size = 15),
axis.title.y = element_text(size = 15),
legend.title=element_text(size = 15),
legend.text=element_text(size = 15)) +
geom_dotplot(aes(fill = factor(Type)), dotsize = 0.8, binaxis = 'y',
stackdir = 'center',
position = position_dodge(0.75))+
xlab("Method")

Related

ggplot2 - geom_line generating line equal to a ladder

I verified that when using geom_line the resulting graph is not formed by solid lines, the lines look like a ladder.
Would anyone know how to get solid lines?
Here is the code used.
data base
0;0
0.000700;1.050
0.001750;1.100
0.003800;1.150
0.029110;1.200
0.130900;1.240
0.341428;1.303
`library(tidyverse)
library(reprex)
SAT <- read.delim("Curva_Tipica.txt", header = FALSE, encoding = "UTF-8")
SAT <- str_split(SAT[[1]],";")
length_SAT <- length(SAT) + 1
curva_VxI <- tibble(
.rows = length_SAT,
I = 0,
V = 0,
)
for (linha in 2:length_SAT) {
curva_VxI$I[linha] <- as.double(SAT[[linha-1]][1])
curva_VxI$V[linha] <- as.double(SAT[[linha-1]][2])
}
Xac <- (curva_VxI$V[length_SAT] - curva_VxI$V[length_SAT-1])/(curva_VxI$I[length_SAT] - curva_VxI$I[length_SAT-1])
Vj <- curva_VxI$V[length_SAT] - Xac*curva_VxI$I[length_SAT]
Xac_grafico <- tibble(
x = c(0, 1),
y = c(0, Xac)
)
Vj_grafico <- tibble(
x = c(0),
y = c(Vj)
)
theme_set(theme_bw())
ggplot() +
geom_point(
data = curva_VxI,
aes(x = I, y = V),
color = "orange",
size = 2
) +
geom_line(
data = curva_VxI,
aes(x = I, y = V),
color = "orange",
linewidth = 1
) +
geom_point(
data = Xac_grafico,
aes(x = x, y = y),
color = "blue",
) +
geom_line(
data = Xac_grafico,
aes(x = x, y = y),
color = "blue",
linewidth = 1,
linetype = "solid",
) +
labs(
y = "V (pu)",
x = "I (pu)"
) +
coord_cartesian(
xlim = c(0, 1),
ylim = c(0, 1.5),
expand = FALSE,
clip = "off"
) +
scale_y_continuous(sec.axis = sec_axis(~.*1, "Xac (pu)")) +
theme(
axis.title.x = element_text(margin = margin(t = 10), size = 12, face = "bold"),
axis.title.y = element_text(margin = margin(r = 10), size = 12, face = "bold"),
axis.text.x = element_text(size = 10),
axis.text.y = element_text(size = 10),
legend.position = "top",
# plot.background = element_rect(fill = "gray60"),
plot.margin = margin(t = 1, r = 1, b = 0.5, l = 0.5, unit = "cm"),
)`
code output
expected result
result obtained

Add id labels to points above the limit line in ggplot

I have a dataframe like this
id <- c(5738180,51845,167774,517814,1344920)
amount <- c(3.76765976,0.85195407,1.96821355,0.01464609,0.57378284)
outlier <- c("TRUE","FALSE","FALSE","FALSE","FALSE")
df.sample <- data.frame(id,amount,outlier)
I am trying to plot the points and add an id label to any point that is above the limit. In this case (id=5738180)
I am plotting like this
library(tidyverse)
library(ggplot2)
library(ggrepel) # help avoid overlapping text labels
library(gridExtra) # adds custom table inside ggplot
library(scales) # breaks and labels for axes and legends
library(ggthemes) # Adding desired ggplot themes
df.sample %>%
ggplot(aes(x = as.numeric(row.names(df.sample)),
y = amount, label = as.character(id))) +
geom_point(alpha = 0.6, position = position_jitter(w = 0.05, h = 0.0),
aes(colour = (amount < 3)), size = 2) +
geom_hline(aes(yintercept = 3, linetype = "Limit"),
color = 'black', size = 1) +
geom_text(aes(y = 3,x = amount[4],
label = paste("Limit = ", round(3, 3)),
hjust = 0, vjust = 1.5)) +
geom_text_repel(data = subset(df.sample, outlier == 'TRUE'),
nudge_y = 0.75,
size = 4,
box.padding = 1.5,
point.padding = 0.5,
force = 100,
segment.size = 0.2,
segment.color = "grey50",
direction = "x") +
geom_label_repel(data = subset(df.sample, outlier == 'TRUE'),
nudge_y = 0.75,
size = 4,
box.padding = 0.5,
point.padding = 0.5,
force = 100,
segment.size = 0.2,
segment.color = "grey50",
direction = "x")
labs(title = "Outlier Detection",
y = "amount",
x = "") +
theme_few() +
theme(legend.position = "none",
axis.text = element_text(size = 10, face = "bold"),
axis.title = element_text(size = 10, face = "bold"),
plot.title = element_text(colour = "blue", hjust = 0.5,
size = 15, face = "bold"),
strip.text = element_text(size = 10, face = "bold")) +
scale_colour_manual(values = c("TRUE" = "green","FALSE" = "red"))
I am running into an error "Error: Aesthetics must be either length 1 or the same as the data (1): x"
Can someone point me in the right direction?

The issue is with geom_text_repel() and geom_label_repel(). You subset the data, which now only includes 1 row, but the aes() are inheriting from the original data which have 5 rows, hence the error. To fix this, subset the data outside of the ggplot() call, and change the aesthetics for it. You are also missing a + after geom_label_repel() and the result below modifies the nudge_y to nudge_x and removes the geom_text_repel().
outliers <- subset(df.sample, outlier == TRUE)
ggplot(data = df.sample,
aes(x = as.numeric(row.names(df.sample)),
y = amount,
label = as.character(id))) +
geom_point(alpha = 0.6,
position = position_jitter(w = 0.05, h = 0.0),
aes(colour = (amount < 3)),
size = 2) +
geom_hline(aes(yintercept = 3,
linetype = "Limit"),
color = 'black',
size = 1) +
geom_text(aes(y = 3,x = amount[4],
label = paste("Limit = ",
round(3, 3)),
hjust = 0,
vjust = 1.5)) +
geom_label_repel(data = outliers,
aes(x = as.numeric(rownames(outliers)),
y = amount,
label = amount),
nudge_x = 0.75,
size = 4,
box.padding = 0.5,
point.padding = 0.5,
force = 100,
segment.size = 0.2,
segment.color = "grey50",
direction = "x",
inherit.aes = F) +
labs(title = "Outlier Detection",
y = "amount",
x = "") +
theme_few() +
theme(legend.position = "none",
axis.text = element_text(size = 10, face = "bold"),
axis.title = element_text(size = 10, face = "bold"),
plot.title = element_text(colour = "blue", hjust = 0.5,
size = 15, face = "bold"),
strip.text = element_text(size = 10, face = "bold")) +
scale_colour_manual(values = c("TRUE" = "green","FALSE" = "red"))

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()

Adding variable name outside of panel/plot

Sample-data:
df <- data.frame("SL" = runif(50, 2.2, 5.8), "LMX" = runif(50, 1.8, 5.5))
I have many different variables for each of which I want to make a box plot with the code below. So that all panels will have the same size, I determined the plot margin so that it is not influenced by the length of the name of the variable. Therefore, now I want to add the variable name outside of the panel to the left.
However, this turns out to be more difficult than expected. I know that this issue has been raised before, but none of the solutions works with me (rnorm or geom_text).
Any help is much appreciated, thank you :)
df %>%
select("Servant Leadership" = SL) %>%
gather(key = "variable", value = "value") -> n
n$variable <- factor(n$variable, levels = c("Servant Leadership"))
ggplot(data = n, aes(y = value, x = as.numeric(variable))) +
stat_summary(fun.data = min.mean.sd.max, geom = "boxplot", col = "#323232", fill = "#EFC76C") +
scale_fill_identity() +
scale_x_continuous(breaks = as.numeric(unique(n$variable)), minor_breaks = NULL,
labels = "", expand = c(0.12, 0.12)) +
scale_y_continuous(breaks = c(1, 2, 3, 4, 5, 6, 7)) +
expand_limits(y = c(1, 7)) + coord_flip() + labs(x = "", y = "") +
theme(text = element_text(size = 15), panel.background = element_rect(fill = "#EAEDED"),
panel.border = element_rect(fill=NA, color = "grey", size = 0.5, linetype = "solid")) +
theme(plot.margin=unit(c(0.2, 0.2, 0, 4),"cm"))
I forgot this code which I ran before:
min.mean.sd.max <- function(x) {
r <- c(min(x), mean(x) - sd(x), mean(x), mean(x) + sd(x), max(x))
names(r) <- c("ymin", "lower", "middle", "upper", "ymax")
r
}
And this are the packages which I use (maybe not all in this code however):
library(reshape)
library(scales)
library(ggplot2)
library(dplyr)
library(tidyr)

Based on the answer by Tung I amended the code for the box plot in the following way:
ggplot(data = n, aes(y = value, x = as.numeric(variable))) +
stat_summary(fun.data = min.mean.sd.max, geom = "boxplot", col = "#323232", fill = "#EFC76C") +
scale_fill_identity() +
scale_x_continuous(breaks = as.numeric(unique(n$variable)), minor_breaks = NULL,
labels = "", expand = c(0.12, 0.12)) +
scale_y_continuous(breaks = c(1, 2, 3, 4, 5, 6, 7)) +
expand_limits(y = c(1, 7)) + coord_flip(clip = "off") + labs(x = "", y = "") +
theme(text = element_text(size = 18), panel.background = element_rect(fill = "#EAEDED"),
panel.border = element_rect(fill=NA, color = "grey", size = 0.5, linetype = "solid")) +
geom_text(x = 1, y = 0.5, inherit.aes = FALSE, label = "Servant Leadership", check_overlap = TRUE, hjust = 1,
fontface = 'plain', size = 6, color = "#4E4E4E") +
theme(plot.margin=unit(c(0.05, 4.5, 0, 9.5),"cm"))

How to add annotation on each facet

I want to give each facet an alpha code, from A to H since there are eight facets, and draw each code on the top-left of each facet:
ggthemr('dust', layout = 'scientific',
spacing = 1, type = 'inner', line_weight = 0.6,
)
ptitles <- c('A' = "Total mass (g)", 'B' = "Root mass (g)", 'C' = "Stem mass (g)",
'D' = "Leaf mass (g)", 'E' = "Number of nodes",
'F' = "Number of leaves", 'G' = "Total stem length (cm)", 'H' = "RDI")
ggplot(gtr, aes(sediment, value)) +
geom_boxplot(aes(fill = nitrogen)) +
geom_text(aes(label = trait, group = trait)) +
facet_wrap(~trait, scales = "free_y", ncol = 2,
labeller = as_labeller(ptitles),
strip.position = "left"
) +
theme(legend.position = "bottom",
legend.title = element_text(size = 12),
legend.key.size = unit(2, "lines"),
legend.text = element_text(size = 12),
strip.text.x = element_text(size = 12, margin = margin(0, 0, 0, 10)),
strip.text.y = element_text(size = 14),
strip.placement = "outside",
axis.title.y = element_text(size = 14),
axis.title.x = element_text(size = 14),
axis.text.x = element_text(size = 14),
panel.spacing.x = unit(0.5, "lines"),
panel.spacing.y = unit(0.3, "lines"),
aspect.ratio = 2 / 3
) +
xlab("Effects of sediment type and nitrogen deposition") +
ylab(NULL)
I tried to use geom_text():
geom_text(aes(label = trait, group = trait))
(Here the variable trait stores factors from A to H to distinguish each facet)
But it did not work like what I expected:
Is there a simple way to such a thing?
UPDATE:
According to baptiste's answer, I changed my geom_text() code above to below:
geom_text(aes(x = -Inf, y = Inf, label = trait, group = trait),
size = 5,
hjust = -0.5,
vjust = 1.4,
inherit.aes = FALSE)
inherit.aes = FALSE here seems to do nothing, how does this parameter work?.
Now my plot looks good:

library(ggplot2)
d <- data.frame(x=rep(1:3, 4), f=rep(letters[1:4], each=3))
labels <- data.frame(f=letters[1:4], label=LETTERS[1:4])
ggplot(d, aes(x,x)) +
facet_wrap(~f) +
geom_point() +
geom_label(data = labels, aes(label=label),
x = Inf, y = -Inf, hjust=1, vjust=0,
inherit.aes = FALSE)

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