I'm creating an overlapping bar graph with the code below:
library(ggplot2)
library(reshape)
library(scales)
x = data.frame('DB' = c('Table4annot', 'UCSC_old', 'UCSC_new'), 'all_elements' = c(595632, 605914, 711073), 'unique_loci' = c(264978, 265979, 274936), 'start_codons' = c(10661, 10714, 22815))
melted = melt(x, id="DB")
p = ggplot(melted, aes(x = DB, y = value, fill = variable))
p = p + geom_bar(stat = "identity", position = "identity", alpha = 0.7, color = 'black', size = 0.4)
p = p + geom_label(aes(label = comma(value), fill = variable), vjust = -0.2, size = 3, show.legend = FALSE, label.padding = unit(0.2, 'lines'))
p = p + scale_x_discrete(limits = c('Table4annot', 'UCSC_old', 'UCSC_new'), labels=c("Table4annot", "UCSC our archive", "UCSC current"))
p = p + scale_y_continuous(labels = comma, expand = c(0, 0), limits = c(0, 750000), breaks = seq(0, 700000, 100000))
p = p + theme(panel.border = element_rect(colour = 'black', fill = NA),
panel.background = element_rect(fill = "white"),
panel.grid.major.y = element_line(colour = "grey40", size = 0.3),
panel.grid.minor.y = element_line(colour = "grey40", size = 0.1),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title = element_blank(),
axis.ticks.x = element_blank(),
legend.title = element_blank(),
legend.position = 'top')
p = p + scale_fill_manual(labels = c('All annotated elements', 'Unique loci with annotation', 'Number of annotated start codons'), values = c(rgb(86, 180, 233, maxColorValue = 255, alpha = 1), rgb(240, 228, 66, maxColorValue = 255, alpha = 1), rgb(0, 0, 0, maxColorValue = 255, alpha = 1)))
p
Since I'm using geom_label(), I get these nice boxed labels filled with the color of the respective bar. But when using scale_fill_manual(), which I do because I didn't find a better way to customise the colours, the boxed labels get a white background. Anybody an idea why?
Any help would be greatly appreciated! Thanks :)
My sessionInfo() is a bit long, but if it's necessary I can add it later. Don't think it matters in this scenario.
Related
I have a data with over 700 observations but below is a sample. Using geom_curve I want to make a plot where the line size(total_trips) corresponds to a color say 3 different colors. For instance between 0-100 (total_trips) can have a color of red
df <- data.frame(
origin_x = c(659627.8,642136.2,648774.7,659627.8,659627.8,658455.7,659627.8,659620.6,661641.8,656246.4),
origin_y = c(6473200,6473200,6462166,6473200,6473200,6467413,6473200,6467163,6479577,6487039),
dest_x = c(642136.2,659627.8,659627.8,648774.7,659620.6,659627.8,658455.7,659627.8,659627.8,659627.8),
dest_y = c(6456563,6473200,6473200,6462166,6467163,6473200,6467413,6473200,6473200,6473200
),
total_trips = c(4002,49878,2011,500,100,3000,2500,654,900,600))
I tried
ggplot() + geom_sf(data=shapefile, colour='grey', fill='grey93', size = 0.25) +
geom_curve(
data = df),
aes(
x = origin_x,
xend = dest_x,
y = origin_y,
yend = dest_y,
size = n,
colour= as.factor(c('red','blue'))),
curvature = 0.3
) + scale_alpha_continuous(range = c(0.09,1)) +
theme(
axis.title = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
plot.title = element_text(hjust = 0.5, size = 6),
plot.caption = element_text(hjust = 1),
plot.caption.position = 'plot',
axis.ticks = element_blank(),
panel.background = element_rect(fill = 'white'),
panel.grid = element_blank(),
plot.background = element_rect(color = NA, size = 0.5, fill=NA),
panel.border = element_rect(color = 'black', fill = NA, size=0.2) ,
legend.position = c(0.89,0.15),
legend.key.size = unit(0.4, 'cm'),
legend.text = element_text(size=7)
) +
annotation_scale(location = 'br', style = 'ticks') + coord_sf(crs=3301) +
annotation_north_arrow(location = 'tr', width = unit(0.20, 'cm'),height = unit(0.5,'cm'))
If I understand correctly - you want to change the colour of the line according to a categorised continuous variable (total_trips), we can do this:
Use cut to categorise the variable and give labels to the groups
Add this new variable to the aes(colour =.
library(dplyr)
library(ggplot2)
df <- df |> mutate(trips = cut(total_trips, c(0, 2000, 5000, 50000),
labels = c("0-2k", "2k-5k", "5k-50k")))
ggplot() +
geom_curve(data = df, aes(x = origin_x,
xend = dest_x,
y = origin_y,
yend = dest_y,
size = total_trips,
colour = trips
))
Output:
Not sure if this is what you want, though – your sample dataset doesn't contain the variable n that you mention in size = n, and you haven't provided us with shapefile.
I'm trying to follow the code suggested in this post, but to no avail.
Specifically, I would like the legend associated with the red vertical line to have a white background.
Some toy data:
df1 <- data.frame(correlation = c(rnorm(1000, 0, 0.6), rnorm(1000, 0, 0.1)), type = c(rep("Real", 1000), rep("Permuted", 1000)))
corSig <- 0.24542
My code:
ggplot(df1, aes(correlation, fill = type)) +
geom_density(alpha = .5) +
geom_vline(aes(xintercept = signif(corSig, 2), linetype = 'FDR = .05'), colour = 'red') +
theme(plot.title = element_text(hjust = .5),
plot.subtitle = element_text(hjust = .5),
legend.title = element_blank(),
legend.position = c(.8, .8),
panel.background = element_blank()) +
guides(linetype = guide_legend(override.aes = list(fill = "#000000"))) +
ggtitle("Gene Expression Correlation", subtitle = paste(nrow(datExpr), "genes,", ncol(datExpr), "bulk sections")) +
xlab("Correlation") +
ylab("Density")
There doesn't seem to be a consistent solution for this issue (for me, at least) but I've got a solution here:
library(tidyverse)
df1 <- data.frame(correlation = c(rnorm(1000, 0, 0.6), rnorm(1000, 0, 0.1)), type = c(rep("Real", 1000), rep("Permuted", 1000)))
corSig <- 0.24542
ggplot(df1, aes(correlation, fill = type)) +
geom_density(alpha = .5) +
geom_vline(aes(xintercept = signif(corSig, 2), linetype = 'FDR = .05'), colour = 'red') +
theme(
plot.title = element_text(hjust = .5),
plot.subtitle = element_text(hjust = .5),
legend.title = element_blank(),
legend.position = c(.8, .8),
panel.background = element_blank(),
legend.key = element_rect(colour = "transparent", fill = "transparent")) +
ggtitle("Gene Expression Correlation", subtitle = paste(nrow(df1), "genes,", ncol(df1), "bulk sections")) +
xlab("Correlation") +
ylab("Density")
Fixed Gene Expression Correlation Plot
In short, I removed ...guides(linetype = guide_legend(override.aes = list(fill = "#000000")))... and added ...legend.key = element_rect(colour = "transparent", fill = "transparent"))...
Hopefully that helps!
I have created a linear gauge in R to be displayed within PowerBI.
My only issue is that the width of the plot cannot be adjusted so I am getting the following:
(Plot is being rendered in PowerBI)
Whereas I would like to obtain the same graph but half the width.
I tried using width within geom_bar but it resizes the bar and the final output is the same.
Ideally, the bar would be half its current width (I am building this graph for a PowerBI report).
This is the code I used:
library(ggplot2)
scores = factor(c('Inadequate','Adequate','Fair','Good','Great','Excellent','Exceptional'),
levels = (c('Inadequate','Adequate','Fair','Good','Great','Excellent','Exceptional')),
ordered = TRUE)
x <- data.frame(points = rep(1,7), scores= scores)
x %>%
ggplot(aes(x=points, fill=scores)) +
geom_bar(position = "stack", show.legend = FALSE) +
geom_text(aes(label=scores, y = seq(from=0.5, to=6.5, by = 1)), label.size = 0.25)+
coord_flip() +
theme(panel.background = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_blank(),
axis.title = element_blank(),
axis.ticks = element_blank(),
axis.text = element_blank()) +
geom_point(aes(x= 1.45, y=5), shape = 25, size=10, colour = "black", fill = "black") +
geom_point(aes(x= 0.55, y=3), shape = 24, size=10, colour = "black", fill = "black") +
geom_point(aes(x= 0.55, y=6), shape = 24, size=10, colour = "black", fill = "black") +
scale_fill_brewer(palette = "RdYlGn", direction = -1)
If simply resizing the Power BI visual is no option, you can use theme(plot.margin = unit(c(0, 0.2, 0, 0.2), "npc")) for increasing margins that ggplot draws around plot. Full code:
library(tidyverse)
scores = factor(c('Inadequate','Adequate','Fair','Good','Great','Excellent','Exceptional'),
levels = (c('Inadequate','Adequate','Fair','Good','Great','Excellent','Exceptional')),
ordered = TRUE)
x <- data.frame(points = rep(1,7), scores= scores)
x %>%
ggplot(aes(x=points, fill=scores)) +
geom_bar(position = "stack", show.legend = FALSE) +
geom_text(aes(label=scores, y = seq(from=0.5, to=6.5, by = 1)), label.size = 0.25)+
coord_flip() +
theme(panel.background = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_blank(),
axis.title = element_blank(),
axis.ticks = element_blank(),
axis.text = element_blank()) +
geom_point(aes(x= 1.45, y=5), shape = 25, size=10, colour = "black", fill = "black") +
geom_point(aes(x= 0.55, y=3), shape = 24, size=10, colour = "black", fill = "black") +
geom_point(aes(x= 0.55, y=6), shape = 24, size=10, colour = "black", fill = "black") +
scale_fill_brewer(palette = "RdYlGn", direction = -1) +
theme(plot.margin = unit(c(0, 0.2, 0, 0.2), "npc"))
I am having some troubles with the following piece of code:
ggplot(data = sb11.20194, aes(y = PROMLECTURACRITICA, x = año)) +
geom_boxplot(fill = "#3AAA35", color = "#3AAA35",outlier.color = "#95C11F",
outlier.size = 5) +
ylab("Puntajes promedio de Lectura Crítica") +
stat_boxplot(geom = "errorbar", colour = "#006633",
width = 0.6) +
stat_summary(geom = "crossbar", width=1.5, fatten=0,
color="white",
fun.data = function(x){ return(c(y=median(x),
ymin=median(x),
ymax=median(x))) }) +
theme(
panel.background = element_rect(fill = "white", colour = rgb(198,
198,
198,
maxColorValue = 255),
size = 1, linetype = "solid"),
panel.grid.minor = element_line(size = 0.1, linetype = 'dashed',
colour = rgb(198,198,198,
maxColorValue = 255)),
axis.ticks.x = element_blank(),
axis.text.x = element_blank(),
axis.title.x = element_blank(),
axis.text.y = element_text(family = "Montserrat"),
axis.title.y = element_text(family = "Montserrat")
) + geom_text(data = num, aes(label = num, y = num),
color = "#575756", hjust = -8,
family = "Montserrat")
which gives the following plot:
I would like to align the labels. Does anyone know how I might do this?
You didn't provide a sample data set, so I made some on my own. You can use two arguments in geom_text: nudge_x and hjust. You can use nudge_x in the way you're currently using hjust in your code. Then, we can use hjust to align the labels.
library(tidyverse)
set.seed(123)
# generate sample data and calculate quantiles
dat <- tibble(x = rnorm(1000))
dat_summary <- tibble(quants = quantile(dat$x))
ggplot(dat, aes(x = 1, y = x))+
geom_boxplot() +
geom_text(data = dat_summary, aes(x = 1.5, y = quants,
label = round(quants, 2)),
hjust = 'outward', nudge_x = 0.1)
I am trying to generate a barplot with dual Y-axis and error bars. I have successfully generated a plot with error bars for one variable but I don't know how to add error bars for another one. My code looks like this. Thanks.
library(ggplot2)
#Data generation
Year <- c(2014, 2015, 2016)
Response <- c(1000, 1100, 1200)
Rate <- c(0.75, 0.42, 0.80)
sd1<- c(75, 100, 180)
sd2<- c(75, 100, 180)
df <- data.frame(Year, Response, Rate,sd1,sd2)
df
# The errorbars overlapped, so use position_dodge to move them horizontally
pd <- position_dodge(0.7) # move them .05 to the left and right
png("test.png", units="in", family="Times", width=2, height=2.5, res=300) #pointsize is font size| increase image size to see the key
ggplot(df) +
geom_bar(aes(x=Year, y=Response),stat="identity", fill="tan1", colour="black")+
geom_errorbar(aes(x=Year, y=Response, ymin=Response-sd1, ymax=Response+sd1),
width=.2, # Width of the error bars
position=pd)+
geom_line(aes(x=Year, y=Rate*max(df$Response)),stat="identity",color = 'red', size = 2)+
geom_point(aes(x=Year, y=Rate*max(df$Response)),stat="identity",color = 'black',size = 3)+
scale_y_continuous(name = "Left Y axis", expand=c(0,0),limits = c(0, 1500),breaks = seq(0, 1500, by=500),sec.axis = sec_axis(~./max(df$Response),name = "Right Y axis"))+
theme(
axis.title.y = element_text(color = "black"),
axis.title.y.right = element_text(color = "blue"))+
theme(
axis.text=element_text(size=6, color = "black",family="Times"),
axis.title=element_text(size=7,face="bold", color = "black"),
plot.title = element_text(color="black", size=5, face="bold.italic",hjust = 0.5,margin=margin(b = 5, unit = "pt")))+
theme(axis.text.x = element_text(angle = 360, hjust = 0.5, vjust = 1.2,color = "black" ))+
theme(axis.line = element_line(size = 0.2, color = "black"),axis.ticks = element_line(colour = "black", size = 0.2))+
theme(axis.ticks.length = unit(0.04, "cm"))+
theme(plot.margin=unit(c(1,0.1,0.1,0.4),"mm"))+
theme(axis.title.y = element_text(margin = margin(t = 0, r = 4, b = 0, l = 0)))+
theme(axis.title.x = element_text(margin = margin(t = 0, r = 4, b = 2, l = 0)))+
theme(
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank())+
ggtitle("SRG3")+
theme(legend.position="top")+
theme( legend.text=element_text(size=4),
#legend.justification=c(2.5,1),
legend.key = element_rect(size = 1.5),
legend.key.size = unit(0.3, 'lines'),
legend.position=c(0.79, .8), #width and height
legend.direction = "horizontal",
legend.title=element_blank())
dev.off()
and my plot is as follows:
A suggestion for future questions: your example is far from being a minimal reproducible example. All the visuals an the annotations are not related to your problem but render the code overly complex which makes it harder for others to work with it.
The following would be sufficient:
ggplot(df) +
geom_bar(aes(x = Year, y = Response),
stat = "identity", fill = "tan1",
colour = "black") +
geom_errorbar(aes(x = Year, ymin = Response - sd1, ymax = Response + sd1),
width = .2,
position = pd) +
geom_line(aes(x = Year, y = Rate * max(df$Response)),
color = 'red', size = 2) +
geom_point(aes(x = Year, y = Rate * max(df$Response)),
color = 'black', size = 3)
(Notice that I've removed stat = "identity" in all geom_s because this is set by default. Furthermore, y is not a valid aestetic for geom_errorbar() so I omitted that, too.)
Assuming that the additional variable you would like to plot error bars for is Rate * max(df$Response)) and that the relevant standard deviation is sd2, you may simply append
+ geom_errorbar(aes(x = Year, ymin = Rate * max(df$Response) - sd2,
ymax = Rate * max(df$Response) + sd2),
colour = "green",
width = .2)
to the code chunk above. This yields the output below.