Normally, vjsust = adjust the label distanace with the max y value, which is not beautiful when the sd is different, is it possible to adjust it with an equal relative distance with upper error bar?
In the following example, the a and b should be move down and c up, how to plot it?
df <- data.frame(dose=c("D0.5", "D1", "D2"),
len=c(4.2, 10, 29.5), sd = c(0.2, 2, 5),
label = c('a', 'b', 'c'))
ggplot(df, aes(x = dose, y = len)) +
geom_errorbar(aes(ymin = len, ymax = len + sd), width=.1, position=position_dodge(.6)) +
geom_bar(position = position_dodge(), stat="identity", width=.4)+
geom_text(aes(label = label, angle = 0),vjust = -2.5)
Use the y parameter in the geom_text aestethics to set up the position of the labels according to the error bars:
ggplot(df, aes(x = dose, y = len)) +
geom_errorbar(aes(ymin = len, ymax = len + sd), width=.1, position=position_dodge(.6)) +
geom_bar(position = position_dodge(), stat="identity", width=.4)+
geom_text(aes(y = len + sd, label = label, angle = 0),vjust = -2.5) +
ylim(0, 40)
Related
I'm trying to create a plot like this image below where the individual data lines are in between the box plots. Image to create in R ggplot2
The closest I am getting is something like this:
Image using ggplot2 but it looks a bit cluttered with the lines/points behind.
data1 %>%
ggplot(aes(Time,Trait)) +
geom_line(aes(group=ID), position = "identity")+
geom_point(aes(group=ID), shape=21, colour="black", size=2, position = "identity")+
geom_boxplot(width=.5,position = position_dodge(width=0.9), fill="white") +
stat_summary(fun.data= mean_cl_boot, geom = "errorbar", width = 0.1, position = position_dodge(width = .9)) +
stat_summary(fun = mean, geom = "point", shape = 18, size=3, position = "identity")+
facet_wrap(~Cond) +
theme_classic()
Any tips would be greatly appreciated!
One option to achieve your desired result would be to make use of continuous x scale. Doing so makes it possible to shift the box plots to the left or to right and vice versa for the points and lines:
Making use of some random data to mimic your real data set.
data1$Time1 <- as.numeric(factor(data1$Time, levels = c("Pre", "Post")))
data1$Time_box <- data1$Time1 + .1 * ifelse(data1$Time == "Pre", -1, 1)
data1$Time_lp <- data1$Time1 + .1 * ifelse(data1$Time == "Pre", 1, -1)
library(ggplot2)
ggplot(data1, aes(x = Time_box, y = Trait)) +
geom_line(aes(x = Time_lp, group=ID), position = "identity")+
geom_point(aes(x = Time_lp, group=ID), shape=21, colour="black", size=2, position = "identity")+
geom_boxplot(aes(x = Time_box, group=Time1), width=.25, fill="white") +
stat_summary(fun.data = mean_cl_boot, geom = "errorbar", width = 0.1) +
stat_summary(fun = mean, geom = "point", shape = 18, size=3, position = "identity") +
scale_x_continuous(breaks = c(1, 2), labels = c("Pre", "Post")) +
facet_wrap(~Cond) +
theme_classic()
DATA
set.seed(42)
data1 <- data.frame(
ID = rep(1:10, 4),
Time = rep(c("Pre", "Post"), each = 10),
Trait = runif(40),
Cond = rep(c("MBSR", "SME"), each = 20)
)
EDIT If you want to two boxplots side by side it's basically the same. However in that case you have to map the interaction of Time1 and the variable mapped on fill on the group aesthetic in geom_boxplot (and probably the error bars as well):
library(ggplot2)
set.seed(42)
data1 <- data.frame(
ID = rep(1:10, 4),
Time = rep(c("Pre", "Post"), each = 10),
Fill = rep(c("Fill1", "Fill2"), each = 5),
Trait = runif(40),
Cond = rep(c("MBSR", "SME"), each = 20)
)
ggplot(data1, aes(x = Time_box, y = Trait)) +
geom_line(aes(x = Time_lp, group=ID, color = Fill), position = "identity")+
geom_point(aes(x = Time_lp, group=ID, fill = Fill), shape=21, colour="black", size=2, position = "identity")+
geom_boxplot(aes(x = Time_box, group=interaction(Time1, Fill) , fill = Fill), width=.25) +
stat_summary(fun.data = mean_cl_boot, geom = "errorbar", width = 0.1) +
stat_summary(fun = mean, geom = "point", shape = 18, size=3, position = "identity") +
scale_x_continuous(breaks = c(1, 2), labels = c("Pre", "Post")) +
facet_wrap(~Cond) +
theme_classic()
as mentioned above, I have the following problem:
Error: Aesthetics must be either length 1 or the same as the data (5): label
I'm quite new to R, so I'm not sure what is wrong. If anyone has any input on what I need to change, that would be great!
AvgPadCount <- ggplot(APD) +
aes(x = Species, y = mean, fill = Plot.Type) +
geom_col(position = "dodge") +
geom_errorbar(aes(x = Species, ymin = mean - se, ymax = mean + se), position = position_dodge(0.9), width = 0.2, colour="gray0", alpha=0.9, size=1.3) +
geom_text(label = c("A", "A", "B", "B"), position = position_dodge(0.9), aes(y = mean+se, x = Species), vjust = -0.5, size = 6) +
ylim(0,6) +
ggtitle("Plot Size Effect on Average Pad Count") +
xlab("Species") +
ylab("Average Pad Count per Plant")
MaxClumpHeight <- ggplot(MCH) +
aes(x = Species, y = mean, fill = Plot.Type) +
geom_col(position = "dodge") +
geom_errorbar(aes(x = Species, ymin = mean - se, ymax = mean + se), position = position_dodge(0.9), width =0.2, colour="gray0", alpha=0.9, size=1.3) +
geom_text(label = c("A", "A", "B", "C"), position = position_dodge(0.9), aes(y = mean+se, x = Species), vjust = -0.5, size = 6) +
ylim(0,32) +
ggtitle("Plot Size Effect on Max Clump Height") +
xlab("Species") +
ylab("Mean Max Clump Height (cm)")
AvgPadCount
MaxClumpHeight
I'm new to R and I've scripted the interaction plot below, for which I want two dotted lines connecting both "coral" and both "darkgoldenrod2" points respectively:
df <- tibble::tribble(~Proportion, ~Lower,~Upper, ~Area,~Time,
invlogit(-0.033886), invlogit(-0.517223067), invlogit(0.449451067), "SNP", "Day",
(invlogit(-0.9231219)+invlogit(-0.3786)), 0.5727 ,0.8087, "SNP", "Night",
invlogit(-0.9231219), invlogit(-1.406458967), invlogit(-0.439784833),"LGCA", "Day",
invlogit(-0.1604356), invlogit(-0.643772667) ,invlogit(0.322901467), "LGCA","Night")
df
dfnew <- df %>%
mutate(ymin = Proportion - Lower,
ymax = Proportion + Upper)
p <- ggplot(data = dfnew, aes(x = Time, y = Proportion, color=Area)) +
geom_point(size = 6, stroke = 0, shape = 16,
position = position_dodge(width = 0.1))+
geom_errorbar(aes(y=Proportion, ymin = Lower, ymax = Upper),width=0.1,size=1,
position = position_dodge(width = 0.1)) +
theme(axis.text=element_text(size=15),
axis.title=element_text(size=20)) +
scale_color_manual(values = c("SNP" = "coral",
"LGCA" = "darkgoldenrod2"))
p
Reading other posts here on SO, I've used the command line: +geom_line(aes(group = 1),size=2)
This however isn't producing the desired plot as you can see below:
Any help with this is truly appreciated!
You should add group=Area to your ggplot mapping and then you just need to call geom_line. You also don't need y=Position in geom_errorbar.
p <- ggplot(data = dfnew, aes(x = Time, y = Proportion, color=Area, group=Area)) +
geom_point(size = 6, stroke = 0, shape = 16,
position = position_dodge(width = 0.1))+
geom_errorbar(aes(ymin = Lower, ymax = Upper), width=0.1, size=1,
position = position_dodge(width = 0.1)) +
theme(axis.text=element_text(size=15),
axis.title=element_text(size=20)) +
scale_color_manual(values = c("SNP" = "coral",
"LGCA" = "darkgoldenrod2")) +
geom_line(size=2)
p
I am try to do a plot whith means lines by group (in ggplot), and i have my code like this
ggplot(gama, aes(x = distancia, y= glipidoscmtejido, colour= estado)) +
geom_point(position=position_dodge(.5), alpha= 1, size=3) +
geom_crossbar(data=gama,aes(x=distancia,ymin=mean(glipidoscmtejido),
ymax=mean(glipidoscmtejido),y=mean(glipidoscmtejido),colour=estado), width = 0.5)
and I get this
but i need the mean line by distancia and by estado. how can i make it?
thanks.
How about this using stat_summary to plot the means per estado per distancia:
# Generate some sample data
set.seed(2017);
df <- cbind.data.frame(
x = rnorm(100),
estado = sample(c("sana", "lesionada"), 100, replace = T),
distancia = sample(c("0-1", "2.5-3.5", "5.6"), 100, replace = T));
require(ggplot2);
ggplot(df, aes(x = distancia, y = x, colour = estado)) +
geom_point(position = position_dodge(width = 0.3)) +
stat_summary(
fun.y = mean,
geom = "errorbar",
aes(ymax = ..y.., ymin = ..y..),
position = position_dodge(width = 0.3),
width = 0.25);
I am having trouble with geom_errorbars particularly in utilizing position_dodge() effectively in this script.
library(ggplot2)
library(plyr)
Dose <- rep(c(3,10,30,100), each = 6)
Visit <- rep(c(1,28), each = 3, times = 4)
Animal <- rep(1:3, times = 8)
Estimate <- runif(24)
Dose <- factor(Dose)
Visit <- factor(Visit)
df <- data.frame(Animal, Dose, Visit, Estimate)
e <- ddply(df, .(Dose, Visit), summarise, mean = mean(Estimate), sd = sd(Estimate), n = length(Estimate))
e$se = e$sd/sqrt(e$n)
trace.out <- ggplot(data = e, aes(x = Visit, y = mean, colour = Dose))
trace.out <- trace.out +
geom_point(data = e, aes(y = mean), size = 3, postion = position_dodge(width = 0.2)) +
geom_line(data = e, aes(y = mean, group = Dose), position = position_dodge(width = 0.2)) +
geom_errorbar(aes(ymin= mean - se, ymax = mean + se), postion = position_dodge(0.2), colour='black', width= 0.3) +
labs(y = 'Estimate') +
theme_bw()
print(trace.out)
The output for me looks like:
I would like for the points, lines and error bars to line up and to have the errorbars not overlap. Is there some way to do that? Additionally I get an error of:
ymax not defined: adjusting position using y instead
Would this have anything to do with it? Thanks in Advance!
Maybe facets are an option:
trace.out <- ggplot(data = e, aes(x = Visit, y = mean, colour = Dose, ymin= mean - se, ymax = mean + se, group = Dose))
trace.out <- trace.out +
geom_point(size = 3, postion = position_dodge(width = 0.2)) +
geom_line(position = position_dodge(width = 0.2), ) +
geom_errorbar(postion = position_dodge(0.2), colour='black', width= 0.3) +
labs(y = 'Estimate') +
theme_bw()
print(trace.out + facet_grid(~Dose) )