Related
I'd like to have some labels stacked on top of a geom_bar graph. Here's an example:
df <- data.frame(x=factor(c(TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE)))
ggplot(df) + geom_bar(aes(x,fill=x)) + opts(axis.text.x=theme_blank(),axis.ticks=theme_blank(),axis.title.x=theme_blank(),legend.title=theme_blank(),axis.title.y=theme_blank())
Now
table(df$x)
FALSE TRUE
3 5
I'd like to have the 3 and 5 on top of the two bars. Even better if I could have the percent values as well. E.g. 3 (37.5%) and 5 (62.5%). Like so:
(source: skitch.com)
Is this possible? If so, how?
To plot text on a ggplot you use the geom_text. But I find it helpful to summarise the data first using ddply
dfl <- ddply(df, .(x), summarize, y=length(x))
str(dfl)
Since the data is pre-summarized, you need to remember to change add the stat="identity" parameter to geom_bar:
ggplot(dfl, aes(x, y=y, fill=x)) + geom_bar(stat="identity") +
geom_text(aes(label=y), vjust=0) +
opts(axis.text.x=theme_blank(),
axis.ticks=theme_blank(),
axis.title.x=theme_blank(),
legend.title=theme_blank(),
axis.title.y=theme_blank()
)
As with many tasks in ggplot, the general strategy is to put what you'd like to add to the plot into a data frame in a way such that the variables match up with the variables and aesthetics in your plot. So for example, you'd create a new data frame like this:
dfTab <- as.data.frame(table(df))
colnames(dfTab)[1] <- "x"
dfTab$lab <- as.character(100 * dfTab$Freq / sum(dfTab$Freq))
So that the x variable matches the corresponding variable in df, and so on. Then you simply include it using geom_text:
ggplot(df) + geom_bar(aes(x,fill=x)) +
geom_text(data=dfTab,aes(x=x,y=Freq,label=lab),vjust=0) +
opts(axis.text.x=theme_blank(),axis.ticks=theme_blank(),
axis.title.x=theme_blank(),legend.title=theme_blank(),
axis.title.y=theme_blank())
This example will plot just the percentages, but you can paste together the counts as well via something like this:
dfTab$lab <- paste(dfTab$Freq,paste("(",dfTab$lab,"%)",sep=""),sep=" ")
Note that in the current version of ggplot2, opts is deprecated, so we would use theme and element_blank now.
Another solution is to use stat_count() when dealing with discrete variables (and stat_bin() with continuous ones).
ggplot(data = df, aes(x = x)) +
geom_bar(stat = "count") +
stat_count(geom = "text", colour = "white", size = 3.5,
aes(label = ..count..),position=position_stack(vjust=0.5))
So, this is our initial plot↓
library(ggplot2)
df <- data.frame(x=factor(c(TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE)))
p <- ggplot(df, aes(x = x, fill = x)) +
geom_bar()
p
As suggested by yuan-ning, we can use stat_count().
geom_bar() uses stat_count() by default. As mentioned in the ggplot2 reference, stat_count() returns two values: count for number of points in bin and prop for groupwise proportion. Since our groups match the x values, both props are 1 and aren’t useful. But we can use count (referred to as “..count..”) that actually denotes bar heights, in our geom_text(). Note that we must include “stat = 'count'” into our geom_text() call as well.
Since we want both counts and percentages in our labels, we’ll need some calculations and string pasting in our “label” aesthetic instead of just “..count..”. I prefer to add a line of code to create a wrapper percent formatting function from the “scales” package (ships along with “ggplot2”).
pct_format = scales::percent_format(accuracy = .1)
p <- p + geom_text(
aes(
label = sprintf(
'%d (%s)',
..count..,
pct_format(..count.. / sum(..count..))
)
),
stat = 'count',
nudge_y = .2,
colour = 'royalblue',
size = 5
)
p
Of course, you can further edit the labels with colour, size, nudges, adjustments etc.
I have a set of code that produces multiple plots using facet_wrap:
ggplot(summ,aes(x=depth,y=expr,colour=bank,group=bank)) +
geom_errorbar(aes(ymin=expr-se,ymax=expr+se),lwd=0.4,width=0.3,position=pd) +
geom_line(aes(group=bank,linetype=bank),position=pd) +
geom_point(aes(group=bank,pch=bank),position=pd,size=2.5) +
scale_colour_manual(values=c("coral","cyan3", "blue")) +
facet_wrap(~gene,scales="free_y") +
theme_bw()
With the reference datasets, this code produces figures like this:
I am trying to accomplish two goals here:
Keep the auto scaling of the y axis, but make sure only 1 decimal place is displayed across all the plots. I have tried creating a new column of the rounded expr values, but it causes the error bars to not line up properly.
I would like to wrap the titles. I have tried changing the font size as in Change plot title sizes in a facet_wrap multiplot, but some of the gene names are too long and will end up being too small to read if I cram them on a single line. Is there a way to wrap the text, using code within the facet_wrap statement?
Probably cannot serve as definite answer, but here are some pointers regarding your questions:
Formatting the y-axis scale labels.
First, let's try the direct solution using format function. Here we format all y-axis scale labels to have 1 decimal value, after rounding it with round.
formatter <- function(...){
function(x) format(round(x, 1), ...)
}
mtcars2 <- mtcars
sp <- ggplot(mtcars2, aes(x = mpg, y = qsec)) + geom_point() + facet_wrap(~cyl, scales = "free_y")
sp <- sp + scale_y_continuous(labels = formatter(nsmall = 1))
The issue is, sometimes this approach is not practical. Take the leftmost plot from your figure, for example. Using the same formatting, all y-axis scale labels would be rounded up to -0.3, which is not preferable.
The other solution is to modify the breaks for each plot into a set of rounded values. But again, taking the leftmost plot of your figure as an example, it'll end up with just one label point, -0.3
Yet another solution is to format the labels into scientific form. For simplicity, you can modify the formatter function as follow:
formatter <- function(...){
function(x) format(x, ..., scientific = T, digit = 2)
}
Now you can have a uniform format for all of plots' y-axis. My suggestion, though, is to set the label with 2 decimal places after rounding.
Wrap facet titles
This can be done using labeller argument in facet_wrap.
# Modify cyl into factors
mtcars2$cyl <- c("Four Cylinder", "Six Cylinder", "Eight Cylinder")[match(mtcars2$cyl, c(4,6,8))]
# Redraw the graph
sp <- ggplot(mtcars2, aes(x = mpg, y = qsec)) + geom_point() +
facet_wrap(~cyl, scales = "free_y", labeller = labeller(cyl = label_wrap_gen(width = 10)))
sp <- sp + scale_y_continuous(labels = formatter(nsmall = 2))
It must be noted that the wrap function detects space to separate labels into lines. So, in your case, you might need to modify your variables.
This only solved the first part of the question. You can create a function to format your axis and use scale_y_continous to adjust it.
df <- data.frame(x=rnorm(11), y1=seq(2, 3, 0.1) + 10, y2=rnorm(11))
library(ggplot2)
library(reshape2)
df <- melt(df, 'x')
# Before
ggplot(df, aes(x=x, y=value)) + geom_point() +
facet_wrap(~ variable, scale="free")
# label function
f <- function(x){
format(round(x, 1), nsmall=1)
}
# After
ggplot(df, aes(x=x, y=value)) + geom_point() +
facet_wrap(~ variable, scale="free") +
scale_y_continuous(labels=f)
scale_*_continuous(..., labels = function(x) sprintf("%0.0f", x)) worked in my case.
Previously in ggplot2, I used a formatter function to multiply values in the Y axis by 100:
formatter100 <- function(x){
x*100 }
With the new ggplot2 (v0.9.1), I am having trouble converting axis labels with a new transformation function:
mult_trans <- function() {
trans_new("mult", function(x) 100*x, function(x) x/100) }
Here is the example plot function
library(scales)
test<-data.frame(ecdf=c(0.02040816,0.04081633,0.06122449,0.08163265,0.10204082,0.14285714,0.14285714,0.16326531,0.24489796,0.24489796,0.24489796,0.24489796,0.26530612,0.28571429,0.30612245,0.32653061,0.36734694,0.36734694,0.38775510,0.40816327,0.42857143,0.46938776,0.46938776,0.48979592,0.53061224,0.53061224,0.59183673,0.59183673,0.59183673,0.61224490,0.63265306,0.65306122,0.67346939,0.69387755,0.71428571,0.73469388,0.75510204,0.77551020,0.79591837,0.81632653,0.83673469,0.85714286,0.87755102,0.89795918,0.91836735,0.93877551,0.95918367,0.97959184,0.99900000),lat=c(50.7812,66.4062,70.3125,97.6562,101.5620,105.4690,105.4690,109.3750,113.2810,113.2810,113.2810,113.2810,125.0000,136.7190,148.4380,164.0620,167.9690,167.9690,171.8750,175.7810,183.5940,187.5000,187.5000,191.4060,195.3120,195.3120,234.3750,234.3750,234.3750,238.2810,261.7190,312.5000,316.4060,324.2190,417.9690,507.8120,511.7190,562.5000,664.0620,683.5940,957.0310,1023.4400,1050.7800,1070.3100,1109.3800,1484.3800,1574.2200,1593.7500,1750.0000))
xbreaks<-c(50,100,150,200,300,500,1000,2000)
ybreaks<-c(1,2,5,10,20,30,40,50,60,70,80,90,95,98,99,99.5,99.9)/100
p <- ggplot( test, aes(lat, ecdf) )
p<-p +
geom_point()+
scale_x_log10(breaks=xbreaks, labels = comma(xbreaks))+
scale_y_continuous(trans='probit',
labels = trans_format(mult_trans()),
"cumulative probability %",
breaks=ybreaks)+
xlab("latency ms")
p
this returns the error:
Error in scale$labels(breaks) : could not find function "trans"
Looks like I've misunderstood how to use transforms properly.
Transformations actually transform the scale itself. In the case of your y axis, you're just formatting the breaks. So you don't really want to use trans_new, just a regular format function. Similarly, you want to use comma_format rather than comma, as the former actually returns a function as needed:
mult_format <- function() {
function(x) format(100*x,digits = 2)
}
p <- ggplot( test, aes(lat, ecdf) )
p<-p +
geom_point()+
scale_x_log10(breaks = xbreaks,labels = comma_format()) +
scale_y_continuous(trans='probit',
labels = mult_format(),
breaks=ybreaks) +
xlab("latency ms")
p
I had multiplied the values of the y axis by 6 but I wanted to display the unmultiplied values as labels, so I ended up adding this:
scale_y_continuous(breaks=seq(-100,100,2)*6,labels=seq(-100,100,2))
I'd like to have some labels stacked on top of a geom_bar graph. Here's an example:
df <- data.frame(x=factor(c(TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE)))
ggplot(df) + geom_bar(aes(x,fill=x)) + opts(axis.text.x=theme_blank(),axis.ticks=theme_blank(),axis.title.x=theme_blank(),legend.title=theme_blank(),axis.title.y=theme_blank())
Now
table(df$x)
FALSE TRUE
3 5
I'd like to have the 3 and 5 on top of the two bars. Even better if I could have the percent values as well. E.g. 3 (37.5%) and 5 (62.5%). Like so:
(source: skitch.com)
Is this possible? If so, how?
To plot text on a ggplot you use the geom_text. But I find it helpful to summarise the data first using ddply
dfl <- ddply(df, .(x), summarize, y=length(x))
str(dfl)
Since the data is pre-summarized, you need to remember to change add the stat="identity" parameter to geom_bar:
ggplot(dfl, aes(x, y=y, fill=x)) + geom_bar(stat="identity") +
geom_text(aes(label=y), vjust=0) +
opts(axis.text.x=theme_blank(),
axis.ticks=theme_blank(),
axis.title.x=theme_blank(),
legend.title=theme_blank(),
axis.title.y=theme_blank()
)
As with many tasks in ggplot, the general strategy is to put what you'd like to add to the plot into a data frame in a way such that the variables match up with the variables and aesthetics in your plot. So for example, you'd create a new data frame like this:
dfTab <- as.data.frame(table(df))
colnames(dfTab)[1] <- "x"
dfTab$lab <- as.character(100 * dfTab$Freq / sum(dfTab$Freq))
So that the x variable matches the corresponding variable in df, and so on. Then you simply include it using geom_text:
ggplot(df) + geom_bar(aes(x,fill=x)) +
geom_text(data=dfTab,aes(x=x,y=Freq,label=lab),vjust=0) +
opts(axis.text.x=theme_blank(),axis.ticks=theme_blank(),
axis.title.x=theme_blank(),legend.title=theme_blank(),
axis.title.y=theme_blank())
This example will plot just the percentages, but you can paste together the counts as well via something like this:
dfTab$lab <- paste(dfTab$Freq,paste("(",dfTab$lab,"%)",sep=""),sep=" ")
Note that in the current version of ggplot2, opts is deprecated, so we would use theme and element_blank now.
Another solution is to use stat_count() when dealing with discrete variables (and stat_bin() with continuous ones).
ggplot(data = df, aes(x = x)) +
geom_bar(stat = "count") +
stat_count(geom = "text", colour = "white", size = 3.5,
aes(label = ..count..),position=position_stack(vjust=0.5))
So, this is our initial plot↓
library(ggplot2)
df <- data.frame(x=factor(c(TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE)))
p <- ggplot(df, aes(x = x, fill = x)) +
geom_bar()
p
As suggested by yuan-ning, we can use stat_count().
geom_bar() uses stat_count() by default. As mentioned in the ggplot2 reference, stat_count() returns two values: count for number of points in bin and prop for groupwise proportion. Since our groups match the x values, both props are 1 and aren’t useful. But we can use count (referred to as “..count..”) that actually denotes bar heights, in our geom_text(). Note that we must include “stat = 'count'” into our geom_text() call as well.
Since we want both counts and percentages in our labels, we’ll need some calculations and string pasting in our “label” aesthetic instead of just “..count..”. I prefer to add a line of code to create a wrapper percent formatting function from the “scales” package (ships along with “ggplot2”).
pct_format = scales::percent_format(accuracy = .1)
p <- p + geom_text(
aes(
label = sprintf(
'%d (%s)',
..count..,
pct_format(..count.. / sum(..count..))
)
),
stat = 'count',
nudge_y = .2,
colour = 'royalblue',
size = 5
)
p
Of course, you can further edit the labels with colour, size, nudges, adjustments etc.
I have the following problem: I would like to visualize a discrete and a continuous variable on a boxplot in which the latter has a few extreme high values. This makes the boxplot meaningless (the points and even the "body" of the chart is too small), that is why I would like to show this on a log10 scale. I am aware that I could leave out the extreme values from the visualization, but I am not intended to.
Let's see a simple example with diamonds data:
m <- ggplot(diamonds, aes(y = price, x = color))
The problem is not serious here, but I hope you could imagine why I would like to see the values at a log10 scale. Let's try it:
m + geom_boxplot() + coord_trans(y = "log10")
As you can see the y axis is log10 scaled and looks fine but there is a problem with the x axis, which makes the plot very strange.
The problem do not occur with scale_log, but this is not an option for me, as I cannot use a custom formatter this way. E.g.:
m + geom_boxplot() + scale_y_log10()
My question: does anyone know a solution to plot the boxplot with log10 scale on y axis which labels could be freely formatted with a formatter function like in this thread?
Editing the question to help answerers based on answers and comments:
What I am really after: one log10 transformed axis (y) with not scientific labels. I would like to label it like dollar (formatter=dollar) or any custom format.
If I try #hadley's suggestion I get the following warnings:
> m + geom_boxplot() + scale_y_log10(formatter=dollar)
Warning messages:
1: In max(x) : no non-missing arguments to max; returning -Inf
2: In max(x) : no non-missing arguments to max; returning -Inf
3: In max(x) : no non-missing arguments to max; returning -Inf
With an unchanged y axis labels:
The simplest is to just give the 'trans' (formerly 'formatter') argument of either the scale_x_continuous or the scale_y_continuous the name of the desired log function:
library(ggplot2) # which formerly required pkg:plyr
m + geom_boxplot() + scale_y_continuous(trans='log10')
EDIT:
Or if you don't like that, then either of these appears to give different but useful results:
m <- ggplot(diamonds, aes(y = price, x = color), log="y")
m + geom_boxplot()
m <- ggplot(diamonds, aes(y = price, x = color), log10="y")
m + geom_boxplot()
EDIT2 & 3:
Further experiments (after discarding the one that attempted successfully to put "$" signs in front of logged values):
# Need a function that accepts an x argument
# wrap desired formatting around numeric result
fmtExpLg10 <- function(x) paste(plyr::round_any(10^x/1000, 0.01) , "K $", sep="")
ggplot(diamonds, aes(color, log10(price))) +
geom_boxplot() +
scale_y_continuous("Price, log10-scaling", trans = fmtExpLg10)
Note added mid 2017 in comment about package syntax change:
scale_y_continuous(formatter = 'log10') is now scale_y_continuous(trans = 'log10') (ggplot2 v2.2.1)
I had a similar problem and this scale worked for me like a charm:
breaks = 10**(1:10)
scale_y_log10(breaks = breaks, labels = comma(breaks))
as you want the intermediate levels, too (10^3.5), you need to tweak the formatting:
breaks = 10**(1:10 * 0.5)
m <- ggplot(diamonds, aes(y = price, x = color)) + geom_boxplot()
m + scale_y_log10(breaks = breaks, labels = comma(breaks, digits = 1))
After executing::
Another solution using scale_y_log10 with trans_breaks, trans_format and annotation_logticks()
library(ggplot2)
m <- ggplot(diamonds, aes(y = price, x = color))
m + geom_boxplot() +
scale_y_log10(
breaks = scales::trans_breaks("log10", function(x) 10^x),
labels = scales::trans_format("log10", scales::math_format(10^.x))
) +
theme_bw() +
annotation_logticks(sides = 'lr') +
theme(panel.grid.minor = element_blank())
I think I got it at last by doing some manual transformations with the data before visualization:
d <- diamonds
# computing logarithm of prices
d$price <- log10(d$price)
And work out a formatter to later compute 'back' the logarithmic data:
formatBack <- function(x) 10^x
# or with special formatter (here: "dollar")
formatBack <- function(x) paste(round(10^x, 2), "$", sep=' ')
And draw the plot with given formatter:
m <- ggplot(d, aes(y = price, x = color))
m + geom_boxplot() + scale_y_continuous(formatter='formatBack')
Sorry to the community to bother you with a question I could have solved before! The funny part is: I was working hard to make this plot work a month ago but did not succeed. After asking here, I got it.
Anyway, thanks to #DWin for motivation!