Margins between panels in ggplot - r

Hi this is the code I have pls:
library(ggplot2)
ggplot(mpg, aes(cty, hwy))+
geom_point()+
facet_grid( ~ drv) +
theme(panel.margin = unit(.05, "lines"),
panel.border = element_rect(color = "black", fill = NA, size = 1),
strip.background = element_rect(color = "black", size = 1))
I would like to draw a margin between the 3 panels (dotted lines ) and also how can I please remove the 'cty' legend which is appearing on x-axis? Many thanks

Perhaps you are looking for something like this?
library(ggplot2)
ggplot(mpg, aes(cty, hwy)) +
geom_point() +
facet_grid( ~ drv) +
theme(panel.spacing = unit(0, "lines"),
strip.background = element_rect(color = "black"),
axis.title.x = element_blank(),
axis.line = element_line()) +
annotation_custom(grid::linesGrob(gp = grid::gpar(lty = 2)),
xmin = 7.7, xmax = 7.7)

Related

How to plot counts stackbar in ggplot2 R?

Dataset contains "two friends" and coded "interaction" (all factors). I want to plot the frequency of type of interactions between two friends using a stacked bar. I tried the following code.
Friend1 <- c("A","A","A","A","A","A","A","A","B","B","B","B","B","B","B","B")
Friend2 <- c("1","1","2","2","1","1","2","2","1","1","2","2","1","1","2","2")
Interaction <- c("O","X","D","D","D","X","X","D/R","O","X","D","D","D","X","X","D/R")
df <- data.frame(Friend1, Friend2, Interaction)
df$Friend1 <- as.factor(as.character(df$Friend1))
df$Friend2 <- as.factor(as.character(df$Friend2))
df$Interaction <- as.factor(as.character(df$Interaction))
ggplot(df, aes(fill=Interaction, y=count(Interaction), x=Friend2)) +
geom_bar(position="fill", stat="identity", color = "white") + theme_classic() + theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(colour = "black", size=1)) + theme(strip.background = element_blank()) + facet_grid(.~Friend1)
Erorr: Error in UseMethod("count") :
no applicable method for 'count' applied to an object of class "character"
How do I "count" these factors to visualize frequency of interactions?
The issue is that dplyr::count expects a dataframe as its first argument and returns a dataframe. However, there is no reason to compute the counts as geom_bar will do that by default, i.e. get rid of y=... and stat="identity":
library(ggplot2)
ggplot(df, aes(fill = Interaction, x = Friend2)) +
geom_bar(position = "fill", color = "white") +
theme_classic() +
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(colour = "black", size = 1)
) +
theme(strip.background = element_blank()) +
facet_grid(. ~ Friend1)
An alternative visualization using facets per "friends" column may make your counts clearer than a standard stacked bar:
ggplot(df, aes(x = 1, fill = Interaction)) +
geom_bar(width = 1, color = "white", size = 1, alpha = 0.8) +
geom_text(stat = "count", aes(label = after_stat(count)), size = 7,
position = position_stack(vjust = 0.5), color = "white",
fontface = 2) +
facet_grid(Friend1 ~ Friend2, switch = "both") +
scale_fill_brewer(palette = "Set1") +
coord_polar(theta = "y") +
labs(x = "Friend1", y = "Friend2") +
theme_bw(base_size = 20) +
theme(panel.grid = element_blank(),
strip.background = element_blank(),
strip.placement = "outside",
axis.text.x = element_blank(),
panel.border = element_rect(color = "gray90", fill = NA),
panel.spacing = unit(0, "mm"),
axis.text = element_blank(),
axis.ticks = element_blank())

Barplot - stacked ggplot percentage barplot starting value NOT 0%

I have a plot like this:
library(ggplot2)
library(reshape2)
library(ggh4x)
data <- data.frame(col1=c("Sample1","Sample2","Sample3","Sample4","Sample5","Sample6"),
col2=c(0.5,0.1,0.4,0.05,0.05,0.9),
col3=c(0.6,0.1,0.3,0.1,0.1,0.8),
col4=c(0.5,0.3,0.2,0.05,0.15,0.8),
col5=c("a","a","a","b","b","b"),
col6=c("c","c","c","c","c","c"))
data2 <- melt(data)
ggplot(data=data2, aes(x = variable, y = value, fill=col1))+
geom_bar(position="stack", stat="identity")+
scale_fill_manual(values=c("#e6194B","#ffe119","#f58231","#911eb4","#42d4f4","#bfef45")) +
scale_y_continuous(expand = c(0, 0),labels = scales::percent) +
facet_nested(~col6 + ~col5, scales = "free_x",space = "free_x",switch = "x") +
ggtitle("Title") +
theme_classic() +
theme(strip.text.y = element_text(angle=0),legend.position = "right",
legend.key.size = unit(0.4, 'cm'),
axis.line = element_line(colour = "black"),
axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1),
strip.placement = "outside",
strip.background = element_rect(color = "white", fill = "white"),
axis.title = element_blank()) +
guides(fill=guide_legend(title=NULL, ncol = 1)) +
xlab("X axis") +
ylab("Y axis")
Which creates a barplot like this:
Please take a look
My question is simple, how can I set y-axis starting value to 10% instead of 0% (without changing the code too much). All answers are greatly appreciated! (Similar questions are checked, without success...)
While in general not recommended for bar charts one option to "set" the starting point would be to set the limits via coord_cartesian:
library(ggplot2)
library(ggh4x)
ggplot(data = data2, aes(x = variable, y = value, fill = col1)) +
geom_bar(position = "stack", stat = "identity") +
scale_fill_manual(values = c("#e6194B", "#ffe119", "#f58231", "#911eb4", "#42d4f4", "#bfef45")) +
scale_y_continuous(expand = c(0, 0), labels = scales::percent) +
facet_nested(~ col6 + ~col5, scales = "free_x", space = "free_x", switch = "x") +
ggtitle("Title") +
theme_classic() +
theme(
strip.text.y = element_text(angle = 0), legend.position = "right",
legend.key.size = unit(0.4, "cm"),
axis.line = element_line(colour = "black"),
axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1),
strip.placement = "outside",
strip.background = element_rect(color = "white", fill = "white"),
axis.title = element_blank()
) +
guides(fill = guide_legend(title = NULL, ncol = 1)) +
xlab("X axis") +
ylab("Y axis") +
coord_cartesian(ylim = c(.1, NA))

Increase distance between axis line and plot lines on ggplot

How do I increase the distance between the axis.line.y below and the blue geom_hline below? I want a gap between the two, I don't want them kissing as shown on the plot.
library(tidyverse)
ggplot(mpg, aes(cty, hwy)) +
geom_point() +
geom_hline(yintercept = 25, color = "blue") +
theme_minimal() +
theme(axis.line.y = element_line(color = "black"),
axis.ticks.y.left = element_line(color = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())
I'm not sure if this is exactly what you want but try it.
library(tidyverse)
ggplot(mpg, aes(cty, hwy)) +
geom_point() +
geom_segment(aes(x = min(cty), y = 25,
xend = max(cty), yend = 25),
data = mpg) +
theme_minimal() +
theme(axis.line.y = element_line(color = "black"),
axis.ticks.y.left = element_line(color = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank())

Specific Barplot in R ggplot

Hello I will try for a last time,
I am doing my best to draw a barplot like the following Figure:
However it seems impossible with R.
Any idea?
Thanks in advance,
Peter
Attached the code I used.
groupe2<-rep(c(rep("P",4),rep("I",4)),2)
groupe<-rep(c("PPP","PPI","PIP","PII","IPP","IPI","IIP","III"),2)
OR_A<-c(1.00,0.86,0.88,0.90,0.77,0.68,0.77,0.70)
ICinf_A<-c(NA,0.70,0.72,0.76,0.60,0.50,0.61,0.61)
ICsup_A<-c(NA,1.06,1.07,1.06,1.00,0.92,0.96,0.81)
OR_B<-c(1.00,0.97,1.01,0.81,0.73,0.69,0.61,0.58)
ICinf_B<-c(NA,0.78,0.77,0.62,0.61,0.57,0.50,0.52)
ICsup_B<-c(NA,1.20,1.28,1.05,0.81,0.82,0.71,0.65)
OR_C<-c(1.00,1.03,0.86,0.65,0.68,0.58,0.47,0.37)
ICinf_C<-c(NA,0.84,0.67,0.50,0.59,0.49,0.40,0.33)
ICsup_C<-c(NA,1.27,1.10,0.86,0.78,0.69,0.56,0.41)
Cohort<-c(rep(" PC",8), rep("RIC",8))#, rep("RIC",8))
OR<-c(OR_A,OR_B)#,OR_C)
ICinf<-c(ICinf_A,ICinf_B)#,ICinf_C)
ICsup<-c(ICsup_A,ICsup_B)#,ICsup_C)
rm(dataOR)
dataOR<-data.frame(OR,groupe,Cohort,groupe2,ICinf,ICsup)
names(dataOR)
dataOR[, "groupe"] <- factor(dataOR[, "groupe"] ,
levels = c("PPP","PPI","PIP","PII","IPP","IPI","IIP","III"))
##########
library(ggdag)
ggplot(dataOR, aes(fill=outcome, y=OR, x=groupe)) +
geom_bar(position="dodge", stat="identity", color = "gray95", size = 0.25) +
# scale_fill_brewer(palette="Blues")+
scale_fill_manual(values = RColorBrewer::brewer.pal(5, "Blues")[3:5]) +
geom_errorbar(aes(ymin=ICinf, ymax=ICsup), width=.4, position=position_dodge(.9))+
geom_hline(yintercept=1) +
geom_point(position = position_dodge(0.9), size = 0.5, show.legend = F) +
scale_y_continuous(expand = expand_scale(mult = c(0, 0.05))) +
facet_wrap(~groupe, nrow = 1, scales = "free_x") +
labs(fill = NULL) +
theme(legend.position = "top",
legend.key.height = unit(0.2, "cm"),
legend.background = element_rect(color = "black", size = 0.4),
axis.line = element_line(color = "black"),
axis.text.x = element_blank(),
axis.ticks = element_blank(),
panel.grid.major.x = element_blank(),
axis.title = element_text(face = "bold"))

Make the faceted x-axis text be the grouping factor in R using ggplot2 when plotting boxplots

I am creating faceted box plots that are grouped by a variable. Instead of having the x-axis text be the factors for the x-axis variable I'd like the x-axis text to be the grouping variable.
However, I don't just want to use the grouping variable as my x-axis variable because I'd like the boxplots to cluster. Its hard to explain well. But I think its clear from the code and comments below.
Let me know if you have any suggestions or can help and thanks in advance!
library(ggplot2)
library(scales)
ln_clr <- "black"
bk_clr <- "white"
set.seed(1)
# Creates variables for a dataset
donor = rep(paste0("Donor",1:3), each=40)
machine = sample(rep(rep(paste0("Machine",1:4), each=1),30))
gene = rep(paste0("Gene",LETTERS[1:5]), each=24)
value = rnorm(24*5, mean=rep(c(0.5,10,1000,25000,8000), each=24),
sd=rep(c(0.5,8,900,9000,3000), each=24))
# Makes all values positive
for(m in 1:length(value)){
if(value[m]<0){
value[m] <- sqrt(value[m]*value[m])
}
}
# Creates a data frame from variables
df = data.frame(donor, machine, gene, value)
# Adds a clone variable
clns <- LETTERS[1:4]
k=1
for(i in 1:nrow(df)/4){
for(j in 1:length(clns)){
df$clone[k] <- paste(df$donor[k],clns[j],sep="")
k = k+1
}
}
df$clone <- as.factor(df$clone)
#*************************************************************************************************************************************
# Creates the facet of the machine but what I want on the x-axis is clone, not donor.
# However, if I set x to clone it doesn't group the boxplots and its harder to read
# the graph.
bp1 <- ggplot(df, aes(x=donor, y=value, group=clone)) +
stat_boxplot(geom ='errorbar', position = position_dodge(width = .83),
width = 0.25, size = 0.7, coef = 1) +
geom_boxplot(coef=1, outlier.shape = NA, position = position_dodge(width = .83),
lwd = 0.3, alpha = 1, colour = ln_clr) +
geom_point(position = position_dodge(width = 0.83), size = 1.8, alpha = 0.9,
mapping=aes(group=clone)) +
facet_wrap(~ machine, ncol=2, scales="free_x")
bp1 + scale_y_log10(expand = c(0, 0)) +
theme(axis.text.x= element_text(size=rel(1), colour = "black", angle=45, hjust=1),
strip.background = element_rect(colour = ln_clr, fill = bk_clr, size = 1))
# Creates the facet of the Donor and clusters the clones but doesn't facet the
# machine. This could be okay if I could put spaces in between the different
# machine values but not the donors and could remove the donor facet labels, and
# only have the machine values show up once.
bp2 <- ggplot(df, aes(x=clone, y=value)) +
stat_boxplot(geom ='errorbar', position = position_dodge(width = .83),
width = 0.25, size = 0.7, coef = 1) +
geom_boxplot(coef=1, outlier.shape = NA, position = position_dodge(width = .83),
lwd = 0.3, alpha = 1, colour = ln_clr) +
geom_point(position = position_dodge(width = 0.83), size = 1.8, alpha = 0.9) +
facet_wrap(machine ~ donor, scales="free_x", ncol=6)
bp2 + scale_y_log10(expand = c(0, 0)) +
theme(axis.text.x= element_text(size=rel(1), colour = "black", angle=45, hjust=1),
strip.background = element_rect(colour = ln_clr, fill = bk_clr, size = 1),
panel.spacing = unit(0, "lines"))
Below is an example comparing what I'd like in an ideal world (Top two facets) as compared to what I'm getting (bottom two facets).
I'm not sure I understand exactly what you're trying to do, so let me know if this is on the right track:
library(dplyr)
pd = position_dodge(width=0.83)
ggplot(df %>% mutate(clone=gsub("Donor[1-3]","",clone),
donor=gsub("Donor", "", donor)),
aes(x=clone, y=value, color=donor, group=interaction(clone,donor))) +
geom_boxplot(coef=1, outlier.shape=NA, position=pd, lwd=0.3) +
geom_point(position=pd, size=1.8, alpha=0.9) +
facet_wrap(~ machine, ncol=2, scales="free_x") +
scale_y_log10(expand = c(0.02, 0)) +
theme(strip.background=element_rect(colour=ln_clr, fill=bk_clr, size=1))
How about this:
ggplot(df, aes(x=clone, y=value, group=interaction(clone,donor))) +
geom_boxplot(coef=1, outlier.shape=NA, lwd=0.3) +
geom_point(size=1.8, alpha=0.9) +
facet_wrap(~ machine, ncol=2, scales="free_x") +
scale_y_log10(expand = c(0.02, 0)) +
theme(axis.text.x= element_text(size=rel(1), colour = "black", angle=45, hjust=1),
strip.background=element_rect(colour=ln_clr, fill=bk_clr, size=1))
I found a work around for this problem but its not very elegant. I'd be super happy if some one came up with a better solution. Using the code to create a function for a "multiplot" found here and adding the code below I was able to do what I wanted. However, This is a slightly wonky solution in that I can't really format my titles with boxes around them and there are still two "clone" titles on the x axis that I can't replace easily with a single x-axis title. Also, had I of had many "machines" in my example this solution would have been painful to scale. All-in-all not ideal but passible for what I need. Special thanks to Eipi10 for their help, I appreciate it.
# Creates a multi-plot function for use in the graphs below
multiplot <- function(..., plotlist=NULL, file, cols=1, layout=NULL) {
library(grid)
# Make a list from the ... arguments and plotlist
plots <- c(list(...), plotlist)
numPlots = length(plots)
# If layout is NULL, then use 'cols' to determine layout
if (is.null(layout)) {
# Make the panel
# ncol: Number of columns of plots
# nrow: Number of rows needed, calculated from # of cols
layout <- matrix(seq(1, cols * ceiling(numPlots/cols)),
ncol = cols, nrow = ceiling(numPlots/cols))
}
if (numPlots==1) {
print(plots[[1]])
} else {
# Set up the page
grid.newpage()
pushViewport(viewport(layout = grid.layout(nrow(layout), ncol(layout))))
# Make each plot, in the correct location
for (i in 1:numPlots) {
# Get the i,j matrix positions of the regions that contain this subplot
matchidx <- as.data.frame(which(layout == i, arr.ind = TRUE))
print(plots[[i]], vp = viewport(layout.pos.row = matchidx$row,
layout.pos.col = matchidx$col))
}
}
}
# Call multiplot function after storing each of the below plots as variables
ln_clr <- "black"
bk_clr <- "white"
bp3 <- ggplot(df[df$machine=="Machine1",], aes(x=clone, y=value)) +
geom_boxplot(coef=1, outlier.shape=NA, lwd=0.3) +
geom_point(size=1.8, alpha=0.9) +
ggtitle("Machine 1") +
expand_limits(y=c(0.001,10^5)) +
facet_wrap(~ donor, nrow=1, scales="free_x") + scale_y_log10(expand = c(0, 0)) +
theme(axis.text.x= element_text(size=rel(1), color = ln_clr, angle=45, hjust=1),
panel.spacing = unit(0.25, "lines"), axis.title.x= element_blank(),
plot.title = element_text(hjust=0.5),
strip.text.x = element_text(size=rel(1), face="bold", colour = ln_clr),
strip.background = element_rect(colour = ln_clr, fill = bk_clr, size = 1),
axis.line.x= element_line(size = 1.25, colour = ln_clr),
axis.line.y= element_line(size = 1.25, colour = ln_clr),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = bk_clr),
panel.border = element_blank(),
plot.background = element_rect(fill = bk_clr))
bp4 <- ggplot(df[df$machine=="Machine2",], aes(x=clone, y=value)) +
geom_boxplot(coef=1, outlier.shape=NA, lwd=0.3) +
geom_point(size=1.8, alpha=0.9) +
ggtitle("Machine 2") +
expand_limits(y=c(0.001,10^5)) +
facet_wrap(~ donor, nrow=1, scales="free_x") + scale_y_log10(expand = c(0, 0)) +
theme(axis.text.x= element_text(size=rel(1), colour = ln_clr, angle=45, hjust=1),
panel.spacing = unit(0.25, "lines"), plot.title = element_text(hjust=0.5),
strip.text.x = element_text(size=rel(1), face="bold", colour = ln_clr),
strip.background = element_rect(colour = ln_clr, fill = bk_clr, size = 1),
axis.line.x= element_line(size = 1.25, colour = ln_clr),
axis.line.y= element_line(size = 1.25, colour = ln_clr),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = bk_clr),
panel.border = element_blank(),
plot.background = element_rect(fill = bk_clr))
bp5 <- ggplot(df[df$machine=="Machine3",], aes(x=clone, y=value)) +
geom_boxplot(coef=1, outlier.shape=NA, lwd=0.3) +
geom_point(size=1.8, alpha=0.9) +
ggtitle("Machine 3") +
expand_limits(y=c(0.001,10^5)) +
facet_wrap(~ donor, nrow=1, scales="free_x") + scale_y_log10(expand = c(0, 0)) +
theme(panel.spacing = unit(0.25, "lines"), axis.title.y= element_blank(),
axis.title.x= element_blank(),axis.line.y= element_blank(),
axis.text.y=element_blank(),
axis.text.x= element_text(size=rel(1), colour = ln_clr, angle=45, hjust=1),
axis.ticks.y=element_blank(), plot.title = element_text(hjust=0.5),
strip.text.x = element_text(size=rel(1), face="bold", colour = ln_clr),
strip.background = element_rect(colour = ln_clr, fill = bk_clr, size = 1),
axis.line.x= element_line(size = 1.25, colour = ln_clr),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = bk_clr),
panel.border = element_blank(),
plot.background = element_rect(fill = bk_clr))
bp6 <- ggplot(df[df$machine=="Machine4",], aes(x=clone, y=value)) +
geom_boxplot(coef=1, outlier.shape=NA, lwd=0.3) +
geom_point(size=1.8, alpha=0.9) +
ggtitle("Machine 4") +
expand_limits(y=c(0.001,10^5)) +
facet_wrap(~ donor, nrow=1, scales="free_x") + scale_y_log10(expand = c(0, 0)) +
theme(axis.text.x= element_text(size=rel(1), colour = ln_clr, angle=45, hjust=1),
panel.spacing = unit(0.25, "lines"), plot.title = element_text(hjust=0.5),
strip.text.x = element_text(size=rel(1), face="bold", colour = ln_clr),
strip.background = element_rect(colour = ln_clr, fill = bk_clr, size = 1),
axis.line.x= element_line(size = 1.25, colour = ln_clr),
axis.line.y= element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.y= element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = bk_clr),
panel.border = element_blank(),
plot.background = element_rect(fill = bk_clr))
# Plot all 4 graphs and saves them as a output file
png(filename="graph3.png", width= 9, height= 7.5, units = "in", res=600)
multiplot(bp3, bp4, bp5, bp6, cols=2)
dev.off()
Alternatively, if I set the "strip.text.x = " and the "strip.background =" as element_blank(). I can generate the below:

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