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I am using below codes
p <- ggplot() +
geom_bar(data=filter(df, variable=="LA"), aes(x=Gen, y=Mean, fill=Leaf),
stat="identity", position="dodge")+
geom_point(data=filter(df, variable=="TT"),aes(x=Gen, y=Mean, colour=Leaf))+
geom_line(data=filter(df, variable=="TT"), aes(x=Gen, y=Mean, group=Leaf))+
ggtitle("G")+xlab("Genotypes")+ylab("Canopy temperature")+
scale_fill_hue(name="", labels=c("Leaf-1", "Leaf-2", "Leaf-3"))+
scale_y_continuous(sec.axis=sec_axis(~./20, name="2nd Y-axis"))+
theme(axis.text.x=element_text(angle=90, hjust=1), legend.position="top")
graph produced from above code
I want graph like that
data
https://docs.google.com/spreadsheets/d/1Fjmg-l0WTL7jhEqwwtC4RXY_9VQV9GOBliFq_3G1f8I/edit#gid=0
From data, I want variable LA to left side and TT from right side
Above part is resolved,
Now, I am trying to put errorbars on the bar graph with below code, it caused an error, can someone have a look for solution?
p + geom_errorbar(aes(ymin=Mean-se, ymax=Mean+se), width=0.5,
position=position_dodge(0.9), colour="black", size=.7)
For this you need to understand that even you have the second Y-Axis, it is just a markup and everything draw on the graph is still base on the main Y-Axis(left one).
So you need to do two things:
Convert anything that should reference to the second Y-Axis to same scale of the one on the left, in this case is the bar scale (LA variables) whose maximum is 15. So you need to divide the value of TT by 20.
Second Axis needs to label correctly so it will be the main Y-Axis multiply by 20.
p <- ggplot() +
geom_bar(data=filter(df, variable=="LA"), aes(x=Gen, y=Mean, fill=Leaf),
stat="identity", position="dodge") +
# values are divided by 20 to be in the same value range of bar graph
geom_point(data=filter(df, variable=="TT"),aes(x=Gen, y=Mean/20, colour=Leaf))+
geom_line(data=filter(df, variable=="TT"), aes(x=Gen, y=Mean/20, group=Leaf))+
ggtitle("G")+xlab("Genotypes")+ylab("Canopy temperature")+
scale_fill_hue(name="", labels=c("Leaf-1", "Leaf-2", "Leaf-3"))+
# second axis is multiply by 20 to reflect the actual value of lines & points
scale_y_continuous(
sec.axis=sec_axis(trans = ~ . * 20, name="2nd Y-axis",
breaks = c(0, 100, 200, 300))) +
theme(axis.text.x=element_text(angle=90, hjust=1), legend.position="top")
For the error par which is very basic here. You will need to adjust the theme and the graph to have a good looking one.
p + geom_errorbar(data = filter(df, variable=="TT"),
aes(x = Gen, y=Mean/20, ymin=(Mean-se)/20,
ymax=(Mean+se)/20), width=0.5,
position=position_dodge(0.9), colour="black", size=.7)
One final note: Please consider reading the error message, understand what it say, reference to the help document of packages, functions in R so you can learn how to do all the code yourself.
I'm making a box-and-whisker plot in R (y-axis # of reads and x-axis of 4 discrete conditions). I'm trying to switch the order in which the discrete conditions appear and to change them from the default white fill to a color of my choosing using the code below. I can get the order to change, but the color continues to stay white. I also have no idea why R cuts off my plot.
library(ggplot2)
capture_data = read.csv("tcp_for_r_plots.csv")
p <- ggplot(capture_data, aes(x=Protocol, y=raw_reads)) + geom_boxplot()
p <- p + scale_x_discrete(limits=c("Standard","TD-60","TD-55","TD-50"))
p <- p + scale_fill_manual(values=c("#999999","#FFFF00","#33FFFF","#FF33CC"))
Attached is the output I keep getting - no color change.
fill color: You need to add the fill option to the geom_boxplot() function as shown below (instead of using the scale_fill_manual function):
+ geom_boxplot(fill=c("#999999","#FFFF00","#33FFFF","#FF33CC"))
Order: the order is based on the alphabetical order of the factor values (Protocol). One solution is to recode the factor levels into the the order you want before running the generating the plot.
p <- ggplot(capture_data, aes(x=Protocol, y=raw_reads, fill=Protocol)) +
geom_boxplot() +
scale_x_discrete(limits=c("Standard","TD-60","TD-55","TD-50")) +
scale_fill_manual(values=c("#999999","#FFFF00","#33FFFF","#FF33CC"))
Add the colors in "fill" argument in ggplot:
p <- ggplot(capture_data, aes(x=Protocol, y=raw_reads)) + geom_boxplot()
should be
p <- ggplot(capture_data, aes(x=Protocol, y=raw_reads, fill = Protocol)) + geom_boxplot()
For example,
ggplot(mtcars, aes(x= as.factor(cyl), y=mpg, fill=as.factor(cyl))) + geom_boxplot()
gives me
I have been trying to look for an answer to my particular problem but I have not been successful, so I have just made a MWE to post here.
I tried the answers here with no success.
The task I want to do seems easy enough, but I cannot figure it out, and the results I get are making me have some fundamental questions...
I just want to overlay points and error bars on a bar plot, using ggplot2.
I have a long format data frame that looks like the following:
> mydf <- data.frame(cell=paste0("cell", rep(1:3, each=12)),
scientist=paste0("scientist", rep(rep(rep(1:2, each=3), 2), 3)),
timepoint=paste0("time", rep(rep(1:2, each=6), 3)),
rep=paste0("rep", rep(1:3, 12)),
value=runif(36)*100)
I have attempted to get the plot I want the following way:
myPal <- brewer.pal(3, "Set2")[1:2]
myPal2 <- brewer.pal(3, "Set1")
outfile <- "test.pdf"
pdf(file=outfile, height=10, width=10)
print(#or ggsave()
ggplot(mydf, aes(cell, value, fill=scientist )) +
geom_bar(stat="identity", position=position_dodge(.9)) +
geom_point(aes(cell, color=rep), position=position_dodge(.9), size=5) +
facet_grid(timepoint~., scales="free_x", space="free_x") +
scale_y_continuous("% of total cells") +
scale_fill_manual(values=myPal) +
scale_color_manual(values=myPal2)
)
dev.off()
But I obtain this:
The problem is, there should be 3 "rep" values per "scientist" bar, but the values are ordered by "rep" instead (they should be 1,2,3,1,2,3, instead of 1,1,2,2,3,3).
Besides, I would like to add error bars with geom_errorbar but I didn't manage to get a working example...
Furthermore, overlying actual value points to the bars, it is making me wonder what is actually being plotted here... if the values are taken properly for each bar, and why the max value (or so it seems) is plotted by default.
The way I think this should be properly plotted is with the median (or mean), adding the error bars like the whiskers in a boxplot (min and max value).
Any idea how to...
... have the "rep" value points appear in proper order?
... change the value shown by the bars from max to median?
... add error bars with max and min values?
I restructured your plotting code a little to make things easier.
The secret is to use proper grouping (which is otherwise inferred from fill and color. Also since you're dodging on multiple levels, dodge2 has to be used.
When you are unsure about "what is plotted where" in bar/column charts, it's always helpful to add the option color="black" which reveals that still things are stacked on top each other, because of your use of dodge instead of dodge2.
p = ggplot(mydf, aes(x=cell, y=value, group=paste(scientist,rep))) +
geom_col(aes(fill=scientist), position=position_dodge2(.9)) +
geom_point(aes(cell, color=rep), position=position_dodge2(.9), size=5) +
facet_grid(timepoint~., scales="free_x", space="free_x") +
scale_y_continuous("% of total cells") +
scale_fill_brewer(palette = "Set2")+
scale_color_brewer(palette = "Set1")
ggsave(filename = outfile, plot=p, height = 10, width = 10)
gives:
Regarding error bars
Since there are only three replicates I would show original data points and maybe a violin plot. For completeness sake I added also a geom_errorbar.
ggplot(mydf, aes(x=cell, y=value,group=paste(cell,scientist))) +
geom_violin(aes(fill=scientist),position=position_dodge(),color="black") +
geom_point(aes(cell, color=rep), position=position_dodge(0.9), size=5) +
geom_errorbar(stat="summary",position=position_dodge())+
facet_grid(timepoint~., scales="free_x", space="free_x") +
scale_y_continuous("% of total cells") +
scale_fill_brewer(palette = "Set2")+
scale_color_brewer(palette = "Set1")
gives
Update after comment
As I mentioned in my comment below, the stacking of the percentages leads to an undesirable outcome.
ggplot(mydf, aes(x=paste(cell, scientist), y=value)) +
geom_bar(aes(fill=rep),stat="identity", position=position_stack(),color="black") +
geom_point(aes(color=rep), position=position_dodge(.9), size=3) +
facet_grid(timepoint~., scales="free_x", space="free_x") +
scale_y_continuous("% of total cells") +
scale_fill_brewer(palette = "Set2")+
scale_color_brewer(palette = "Set1")
I want to add a textbox of 10 separate, stacked lines outside of my plot area in ggplot. My text is: t = c("a=1", "b=2", "c=3", ... , "j=10") but these labels are independent of the data.frame that I made my original ggplot. How can I add 10 lines outside of the plot area?
For example, I want to add a textbox around my vector t on the right of the following plot:
df = data.frame(y=rnorm(300), test=rep(c(1,2,3),each=100))
t = c("a=1", "b=2", "c=3", "d=4", "e=5", "f=6", "g=7", "h=8", "i=0", "j=10")
p <- ggplot(df, aes(x=factor(test), y=y))
p <- p + geom_violin() + geom_jitter(height=0, width=0.1)
p <- p + theme(legend.title=element_blank(), plot.margin=unit(c(0.1, 3, 0.1, 0.1), "cm"))
p
try
library(gridExtra)
grid.arrange(p, right = tableGrob(matrix(t,ncol=1),
theme = ttheme_minimal(padding = unit(c(3,1),"line"))))
You can create a geom_text layer using the label values in t in order to get the labels printed as a legend. But we set alpha=0 in geom_text so that these labels won't be included in the plot, and we use legend.key=element_blank() and override.aes(list(size=0)) to get the "legend" labels (the t values) printed without the meaningless legend key.
p +
geom_text(data = data.frame(t, test=NA, y=NA), aes(label=t, colour=t), alpha=0, x=1, y=1) +
theme(legend.key=element_blank(),
legend.margin=margin(l=-10)) +
guides(colour=guide_legend(override.aes=list(size=0)))
I have this data.frame which I want to plot in facets using ggplot + facet_wrap:
set.seed(1)
df <- data.frame(val=rnorm(36),
gt=c(sapply(c("wt","pd","md","bd"),function(x) rep(x,9))),
ts=rep(c(sapply(c("cb","hp","ac"),function(x) rep(x,3))),4),
col=c(sapply(c("darkgray","darkblue","darkred","darkmagenta"),function(x) rep(x,9))),
index=rep(1:9,4),
stringsAsFactors=F)
df$xlab <- paste(df$ts,df$index,sep=".")
df$gt <- factor(df$gt,levels=c("wt","pd","md","bd"))
Here's how I'm trying to plot:
require(ggplot2)
ggplot(df,aes(x=index,y=val,color=gt))+geom_point(size=3)+facet_wrap(~gt,ncol=4)+
scale_fill_manual(values=c("darkgray","darkblue","darkred","darkmagenta"),labels=levels(df$gt),name="gt",guide=F)+
scale_colour_manual(values=c("darkgray","darkblue","darkred","darkmagenta"),labels=levels(df$gt),name="gt",guide=F)+
labs(x="replicate",y="val")+scale_x_continuous(breaks=df$index,labels=df$xlab)+
theme_bw()+theme(axis.text=element_text(size=6),axis.title=element_text(size=7),legend.text=element_text(size=6),legend.key=element_blank(),panel.border=element_blank(),strip.background=element_blank())
Which gives:
The problem is that the x0axis tick labels repeat themselves, sinceI'm calling scale_x_continuous. How do I get it right with facet_wrap?
Use the actual x-values in xlab as the x aesthetic, along with scales="free_x" in facet_wrap and delete the call to scale_x_continuous. Note, however, that the axis labels are still the same in each panel, because they are the same for each level of gt in the data.
ggplot(df,aes(x=xlab, y=val, color=gt)) +
geom_point(size=3, show.legend=FALSE) +
facet_wrap(~gt, ncol=4, scales="free_x") +
# scale_fill_manual(values=c("darkgray","darkblue","darkred","darkmagenta"), labels=levels(df$gt), name="gt", guide=F) +
scale_colour_manual(values=c("darkgray","darkblue","darkred","darkmagenta")) +
labs(x="replicate", y="val") +
#scale_x_continuous(breaks=df$index, labels=df$xlab)+
theme_bw() +
theme(axis.text=element_text(size=8),
axis.title=element_text(size=7),
legend.text=element_text(size=6),
legend.key=element_blank(),
panel.border=element_blank(),
strip.background=element_blank())
Now let's change xlab, just to see how this works when different panels really do have different labels:
df$xlab[10:20] = LETTERS[1:11]
Now run the same plot code again to get the following:
One more contingency is the case where not all the panels have the same number of x-values. In that case, you can switch to facet_grid and add space="free_x" if you want the width of each panel to be proportional to the number of x-values in each panel.
ggplot(df[-c(1:5),], aes(x=xlab, y=val, color=gt)) +
geom_point(size=3, show.legend=FALSE) +
facet_grid(.~gt, space="free_x", scales="free_x") +
scale_colour_manual(values=c("darkgray","darkblue","darkred","darkmagenta")) +
labs(x="replicate", y="val") +
theme_bw() +
theme(axis.text=element_text(size=8),
axis.title=element_text(size=7),
legend.text=element_text(size=6),
legend.key=element_blank(),
panel.border=element_blank(),
strip.background=element_blank())
A few other things:
You don't need to add color names to your data frame. If you want to change the default color, you can just set the them using one of the scale_colour_*** functions (as you did in your code).
For future reference this c(sapply(c("darkgray","darkblue","darkred","darkmagenta"),function(x) rep(x,9))) can be changed to this rep(c("darkgray","darkblue","darkred","darkmagenta"), each=9).
You can remove the scale_fill_manual line, as you don't have a fill aesthetic in your graph.