Maybe this is a very basic question but I'm a ggplot and R beginner.
I'm using this command to get a barplot:
ggplot(data=melt, aes(x=variable, y=value, fill=value)) +
geom_bar(width=.8, stat="identity") +
xlab("Samples") + ylab("Expression") + ggtitle("Gapdh") +
theme(plot.title=element_text(face="bold", size=12)) +
theme(axis.text.x = element_text(angle = 45, hjust = 1, size=10)) +
theme(axis.text.y = element_text(size=10))
I want to change the colors of barplot, but keeping the gradient of the colors depending on value column. I've tried this but I lose the gradient:
ggplot(data=melt, aes(x=variable, y=value, fill=value)) +
geom_bar(width=.8, stat="identity", fill="red") +
xlab("Samples") + ylab("Expression") + ggtitle("Gapdh") +
theme(plot.title=element_text(face="bold", size=12)) +
theme(axis.text.x = element_text(angle = 45, hjust = 1, size=10)) +
theme(axis.text.y = element_text(size=10))
The data is simple, only two columns( variable - value ):
variable value
1 nu73 13576.49
2 nu73t 10891.88
3 nu81 12673.33
4 nu81t 12159.91
5 nu83 12570.82
6 nu83t 11828.04
Thank you guys in advance
You want to adjust the scale, in particular the continuous scale of fill colors, hence the function scale_fill_continuous().
ggplot(data = melt, aes(x = variable, y = value, fill = value)) +
geom_bar(width = .8, stat = "identity") +
labs(x = "Samples", y = "Expression", title = "Gapdh") +
theme(plot.title = element_text(face = "bold", size = 12),
axis.text.x = element_text(angle = 45, hjust = 1, size = 10),
axis.text.y = element_text(size = 10)) +
scale_fill_continuous(low = "firebrick4", high = "firebrick1")
(I slightly modified your plotting code: you can call theme once with multiple arguments, and I find labs nicer than a bunch of individual labeling calls.)
One other option is to use the palettes from the RColorBrewer package (which are incorporated into ggplot2). The scale_fill_brewer() scale if for discrete color scales, you can "distill" them into continuous scales with scale_fill_distiller(). For example
scale_fill_distiller(type = "seq", palette = "Reds")
To see all of the available scales, run RColorBrewer::display.brewer.all().
Related
I have created a R visualisation in Power BI and looking at having only 1 grid line where the horizontal axis value crosses the axis value at 1.
I am not good with words and not sure if I have explained it well in words. Please see the screenshots below to get a better understanding of what I want to achieve.
Any help is greatly appreciated.
First screenshot is from Excel where I was able to do it and I want to replicate the same in the R chart (second screenshot)
library(ggplot2)
ggplot(unique(dataset), aes(x = reorder(Condition, Rate), y = Rate)) +
labs(x = "Condition")+
geom_point(size = 5, stroke = 0, shape = 18, colour="brown") +
geom_point() + geom_line() +
geom_errorbar(aes(ymin = LL, ymax = UL), width=.2, position=position_dodge(.9), colour="brown", alpha=0.6, size=.7) +
theme_bw()+
theme(panel.grid.major = element_blank()) +
theme(axis.text.x = element_text(angle=90, hjust = 1))+
theme(axis.text.x = element_text(size = 10))
Let p is your original ggplot object
step 1: remove the original x axis
p + theme(axis.line.x = element_blank(),
axis.ticks.x = element_blank(),
axis.text.x = element_blank()) +
labs(x = '') -> p1
step 2: add a line at 1
p1 + geom_hline(yintercept = 1, color = "black")
As you have not provided any data, so I am using iris dataset. You can use the following code
library(ggplot2)
ggplot(unique(iris), aes(x = Species, y = Petal.Width)) +
labs(x = "Condition")+
geom_point(size = 5, stroke = 0, shape = 18, colour="brown") +
geom_point() + geom_line() +
theme_bw()+
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank()) +
theme(axis.text.x = element_text(angle=90, hjust = 1))+
theme(axis.text.x = element_text(size = 10)) +
geom_abline(slope=0, intercept=1, col = "darkblue",lty=1,size = 0.5)
I am trying to include labels to a stacked bar chart for proportions. I have been able to create the chart but I haven't been able to successfully add the labels. I've gotten labels but they are centered and overwriting one another....I know this has been asked, but I haven't found a solution that works.
The data is tidy in the sense that it is long
ggplot(data=dat) +
geom_bar(stat="identity",
mapping = aes(x=Vintage, y=OrigAmt, fill=fct_rev(Grade)),
position = "fill") +
ggtitle("Proportions by Grade") +
scale_fill_manual(values = c("grey", "gray40", "black")) +
guides(fill = guide_legend(reverse = TRUE, title="Grade")) +
scale_y_continuous(name="Proportion",label=percent_format()) +
theme_bw() +
theme(plot.title = element_text(hjust=0.5),
panel.border = element_blank(),
panel.grid = element_blank(),
axis.text.x = element_text(angle = 90))
Try adding this after geom_bar
geom_text(aes(y = cumsum(OrigAmt)-OrigAmt/2, label = Grade), show.legend = F)
Changing the y to a cumulative summation (cumsum) of the y variable minus half the y variable places the text in the middle of each section of each bar.
You can also add a color aesthetic and maybe turn Grade into a factor with defined color values
This appears to work.
ggplot(data = dat,
aes(y = freq, x = Vintage, fill = fct_rev(Grade))) +
geom_col() +
geom_text(aes(label = paste0(freq,"%")),
position = position_stack(vjust = 0.5), size = 2) +
scale_y_continuous(
labels = dollar_format(suffix = "%", prefix = "")) +
labs(title = "Distribution by Vintage",
subtitle = "xxx") +
labs(x = NULL, y = "Percentage") +
theme_bw() +
theme(legend.position = "bottom",
legend.direction = "horizontal",
legend.title = element_blank()) +
guides(fill = guide_legend(reverse = T)) +
scale_fill_manual(values = c("grey", "gray40", "brown")) +
theme(axis.text.x = element_text(angle = 90),
axis.text.x.bottom = element_text(vjust = 0.5))
However, I want to change the font colors and I can't see to be able to do that successfully.
For example, I want the label fonts to be BOLD and the font for A and B to be WHITE and the font for C to be BLACK. Thanks!
I am not able to increase the font size of the names of the variables in a graphic realized with ggplot.
I tried to include these codes inside ggplot code, but unsuccessfully :
theme(text = element_text(size=20))
theme(axis.text=element_text(size=20))
theme(axis.title=element_text(size=14))
theme_grey(base_size = 20)
geom_text(size=20)
My code is :
library(ggplot2)
library(reshape2)
dataplot <- read.csv("/Documents/R.csv",header=T,sep=";")
dataPlotMelt <- melt(data = dataplot, id.vars = c("variable"),variable.name = "Method",value.name = "SMD")
varNames <- as.character(dataplot$variable)
dataPlotMelt$variable <- factor(dataPlotMelt$variable,levels = varNames)
ggplot(data=dataPlotMelt,mapping=aes(x=variable,y=SMD,group=Method, color=Method))+
ylab("Standardizedmeandifference(%)")+
xlab("") +
geom_point(aes(shape=Method),size=2) +
geom_hline(yintercept=15,color="black",size=0.1,linetype="dashed") +
geom_hline(yintercept=-15,color="black",size=0.1,linetype="dashed") +
coord_flip() +
theme(axis.text.x=element_blank()) +
scale_y_continuous(breaks=c(-65,-15,15,105)) +
theme_bw() +
theme(legend.text=element_text(size=12)) +
theme(legend.title=element_blank(),legend.key=element_blank()) +
scale_colour_manual(values=c("grey","black"))
I'd like to increase the font size of the names of the variables in the graphic and, besides, increase the text "Standardized mean difference (%)" and remove the vertical line between the yintercept and ybreak on both sides
new graphic
Thank you Richard for giving me the solution.
As you suggested I used theme after theme_bw
I managed to suppress the useless vertical lines as well with the command theme(panel.grid.minor = element_blank())
Here is the new code for ggplot :
ggplot(data = dataPlotMelt, mapping = aes(x = variable, y = SMD,group = Method,
color = Method)) +
ylab("Standardized mean difference (%)") + xlab("") +
geom_point(aes(shape = Method),size=2) +
geom_hline(yintercept = 15, color = "black", size = 0.1, linetype = "dashed") +
geom_hline(yintercept = -15, color = "black", size = 0.1, linetype = "dashed") +
coord_flip() +
theme(axis.text.x = element_blank()) +
scale_y_continuous(breaks=c(-65,-15,0,15,105)) +
theme_bw() + theme(legend.text = element_text(size=13)) +
scale_colour_manual(values= c("grey","black")) +
theme(axis.text.y = element_text(size=12)) +
theme(axis.title.x = element_text(size=13)) +
theme(panel.grid.minor = element_blank()) +
theme(legend.title = element_blank(), legend.key=element_blank())
I'm using ggplot2 with both + geom_line() + geom_point(). I have the colors/shapes worked out, but I can't scale the legend appropriately. If I do nothing it's tiny, and if I enlarge it, the color blocks the shape.
For example:
You can see that the shapes and colors are both in the legend, but the shapes are being drawn over by the colors. I would like to have shapes of the appropriate color drawn in the legend, but can't figure out how to do it.
My plot is being drown as follows:
ggplot(data=melted, aes(x=gene, y=value, colour=variable, shape=variable, group = variable, stroke=3, reorder(gene, value)))
+ theme_solarized()
+ scale_colour_solarized("blue")
+ geom_line()
+ geom_point()
+ theme(axis.text.x = element_text(angle = 90, hjust = 1), plot.title = element_text(size=16, face="bold"), legend.title=element_blank(), legend.text=element_text(size=20))
+ ggtitle('Signiture Profiles')
+ labs(x="Gene", y=expression(paste("Expression"), title="Expression"))
+ scale_colour_manual(name = "Virus / Time", labels = c("Mock", "ACali09_day1", "ACali09_day3", "ACali09_day8", "AShng113_day1", "AShng113_day3", "AShng113_day8", "AChkShng113_day1", "AChkShng113_day3", "AChkShng113_day8"), values = c("#ff420e","#89da59","#89da59","#89da59","#376467","#376467","#376467","#00293c","#00293c","#00293c"))
+ scale_shape_manual(name = "Virus / Time", labels = c("Mock", "ACali09_day1", "ACali09_day3", "ACali09_day8", "AShng113_day1", "AShng113_day3", "AShng113_day8", "AChkShng113_day1", "AChkShng113_day3", "AChkShng113_day8"), values = c(0,1,2,3,1,2,3,1,2,3))
+ guides(colour = guide_legend(override.aes = list(size=12)))
Here is some example data as requested:Example Data
Thanks in advance for any help you can provide.
You could perhaps rethink how you are differentiating your variables.
You could do something like the following. Note the changes in the first line, where I have separated the component parts of variable rather than setting colours and shapes via your scale statements. (I haven't got your theme, so I left that out).
ggplot(data=melted, aes(x=gene,
y=value,
colour=gsub("_.*","",variable),
shape=gsub(".*_","",variable),
group = variable,
stroke=3,
reorder(gene, value))) +
geom_line() +
geom_point() +
theme(axis.text.x = element_text(angle = 90, hjust = 1),
plot.title = element_text(size=16, face="bold"),
legend.title=element_blank(),
legend.text=element_text(size=20)) +
ggtitle('Signiture Profiles') +
labs(x="Gene", y=expression(paste("Expression"), title="Expression")) +
guides(shape = guide_legend(override.aes = list(size=5)),
colour = guide_legend(override.aes = list(size=5)))
I would like to produce a plot using facet_wrap that has a different y scale for each row of the wrap. In other words, with fixed scales on the same row, free scales on different rows, with a fixed x scale. Free scales doesn't give me exactly what I'm looking for, nor does facet_grid. If possible, I'd like to avoid creating 2 separate plots and then pasting them together. I'm looking for a result like the plot below, but with a y scale max of 300 for the first row, and an y scale max of 50 in the second row. Thanks for any help!
Here is my code:
library(ggplot2)
library(reshape)
# set up data frame
dat <- data.frame(jack = c(150,160,170),
surgeon = c(155,265,175),
snapper = c(10,15,12),
grouper = c(5,12,50))
dat$island<-c("Oahu","Hawaii","Maui")
df<-melt(dat)
# plot
ggplot(df, aes(fill=variable, y=value, x=island)) +
geom_bar(width = 0.85, position= position_dodge(width=0.5),stat="identity", colour="black") +
facet_wrap(~variable, scales = "free_y",ncol=2) +
theme_bw() +
theme(strip.text = element_text(size=15, face="bold"))+
theme(legend.position="none")+
theme(panel.grid.major = element_line(colour = "white", size = 0.2))+
theme(panel.grid.minor = element_line(colour = "white", size = 0.5))+
theme(axis.text.x = element_text(angle = 90, hjust =1, vjust =0.5, size=18))+
labs(y = expression(paste("Yearly catch (kg)")))
Drawing on one of the lower ranked answers from the link Eric commented, you can add a layer that blends into the background to enforce the axes.
Here I created a second data frame (df2) that puts a single point at "Hawaii" and the max value you wanted (300 or 50) for the four variable/fish types. By manually setting the color of the geom_point white, it fades into the background.
library(ggplot2)
library(reshape)
# set up data frame
dat <- data.frame(jack = c(150,160,170),
surgeon = c(155,265,175),
snapper = c(10,15,12),
grouper = c(5,12,50))
dat$island<-c("Oahu","Hawaii","Maui")
df<-melt(dat)
#> Using island as id variables
df2 <- data.frame(island = rep("Hawaii",4), variable = c("jack","surgeon","snapper","grouper"),value = c(300,300,50,50))
ggplot(df, aes(fill=variable, y=value, x=island)) +
geom_bar(width = 0.85, position= position_dodge(width=0.5),stat="identity", colour="black") +
geom_point(data = df2, aes(x = island, y = value), colour = "white") +
facet_wrap(~variable, scales = "free_y",ncol=2) +
theme_bw() +
theme(strip.text = element_text(size=15, face="bold"))+
theme(legend.position="none")+
theme(panel.grid.major = element_line(colour = "white", size = 0.2))+
theme(panel.grid.minor = element_line(colour = "white", size = 0.5))+
theme(axis.text.x = element_text(angle = 90, hjust =1, vjust =0.5, size=18))+
labs(y = expression(paste("Yearly catch (kg)")))