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!
Related
How I can automate displaying only 1 in every n values on a discrete axis?
I can get every other value like this:
library(ggplot2)
my_breaks <- function(x, n = 2) {
return(x[c(TRUE, rep(FALSE, n - 1))])
}
ggplot(mpg, aes(x = class, y = cyl)) +
geom_point() +
scale_x_discrete(breaks = my_breaks)
But I don't think it's possible to specify the n parameter to my_breaks, is it?
Is this possible another way? I'm looking for a solution that works for both character and factor columns.
Not quite like that, but scale_x_discrete can take a function as the breaks argument, so you we just need to adapt your code to make it a functional (a function that returns a function) and things will work:
every_nth = function(n) {
return(function(x) {x[c(TRUE, rep(FALSE, n - 1))]})
}
ggplot(mpg, aes(x = class, y = cyl)) +
geom_point() +
scale_x_discrete(breaks = every_nth(n = 3))
Since ggplot 3.3.0 it is also possible to solve the problem of dense labels on discrete axis by using scale_x_discrete(guide = guide_axis(n.dodge = 2)), which gives (figure from documentation):
See the rewrite of axis code section of the release notes for more details.
This question is motivated by a previous post illustrating various ways to change how axes scales are plotted in a ggplot figure, from the default exponential notation to the full integer value (when ones axes values are very large). While I am able to convert the axes scales from exponential notation to full values, I am unclear how one would achieve the same goal for the values appearing in the legend.
While I understand that one can manually change the length of the legend scale with "scale_color..." or "scale_fill..." followed by the "limits" argument, this does not appear to be a solution to getting my legend values to show "6000000000" rather than "6e+09" (or "0" rather than "0e+00" for that matter).
The following example should suffice. My hope is someone can point out how to implement the 'scales' package to apply for legend scales rather than axes scales.
Thanks very much.
library(ggplot2)
library(scales)
Data <- data.frame(
pi = c(2,71,828,1828,45904,523536,2874713,52662497,757247093,6999595749),
e = c(3,14,159,2653,58979,311599,7963468,54418516,1590576171, 99),
face = 1:10)
p <- ggplot(data = Data, aes(x=face, y=e, colour = pi))
myplot <- p + geom_point() +
scale_y_continuous(labels = comma) +
scale_color_gradientn(colours = rainbow(2), limits=c(0,7000000000))
myplot
Use the Comma formatter in scale_color_gradientn by setting labels = comma e.g.:
p <- ggplot(data = Data, aes(x=face, y=e, colour = pi))
myplot <- p + geom_point() +
scale_y_continuous(labels = comma) +
scale_color_gradientn(colours = rainbow(2), limits=c(0,7000000000), labels = comma)
myplot
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.
How can we change y axis to percent like the figure? I can change y axis range but I can't make it to percent.
Use:
+ scale_y_continuous(labels = scales::percent)
Or, to specify formatting parameters for the percent:
+ scale_y_continuous(labels = scales::percent_format(accuracy = 1))
(the command labels = percent is obsolete since version 2.2.1 of ggplot2)
In principle, you can pass any reformatting function to the labels parameter:
+ scale_y_continuous(labels = function(x) paste0(x*100, "%")) # Multiply by 100 & add %
Or
+ scale_y_continuous(labels = function(x) paste0(x, "%")) # Add percent sign
Reproducible example:
library(ggplot2)
df = data.frame(x=seq(0,1,0.1), y=seq(0,1,0.1))
ggplot(df, aes(x,y)) +
geom_point() +
scale_y_continuous(labels = function(x) paste0(x*100, "%"))
ggplot2 and scales packages can do that:
y <- c(12, 20)/100
x <- c(1, 2)
library(ggplot2)
library(scales)
myplot <- qplot(as.factor(x), y, geom="bar")
myplot + scale_y_continuous(labels=percent)
It seems like the stat() option has been taken off, causing the error message. Try this:
library(scales)
myplot <- ggplot(mtcars, aes(factor(cyl))) +
geom_bar(aes(y = (..count..)/sum(..count..))) +
scale_y_continuous(labels=percent)
myplot
Borrowed from #Deena above, that function modification for labels is more versatile than you might have thought. For example, I had a ggplot where the denominator of counted variables was 140. I used her example thus:
scale_y_continuous(labels = function(x) paste0(round(x/140*100,1), "%"), breaks = seq(0, 140, 35))
This allowed me to get my percentages on the 140 denominator, and then break the scale at 25% increments rather than the weird numbers it defaulted to. The key here is that the scale breaks are still set by the original count, not by your percentages. Therefore the breaks must be from zero to the denominator value, with the third argument in "breaks" being the denominator divided by however many label breaks you want (e.g. 140 * 0.25 = 35).
I want to recreate an "image" plot in ggplot (because of some other aspects of the package). However, I'm facing a problem caused by my y-scale, which is defined by unequally but logically spaced values, e.g. I would have z values for y = 2,4,8,16,32. This causes the tiles to not be equally large, so I have these white bands in my figure. I can solve this by transforming the y values in a factor, but I don't want to do this because I'm also trying to plot other geom objects on the figure which require a numeric scale.
This clearifies my problem a bit:
# random data, with y scale numeric
d <- data.frame(Var1=rep(1901:2000,10),Var2=rep(c(2,4,8,16,32),each=100),value=rnorm(500,50,5))
line=data.frame(Var1=1901:2000,Var2=rnorm(50,1.5,0.5))
ggplot(d, aes(x=Var1, y=Var2)) +
geom_tile(aes(fill=value)) +
geom_line(data=line)
# y as factor
d2 = d
d2$Var2=as.factor(d2$Var2) ggplot(d2, aes(x=Var1, y=Var2)) +
geom_tile(aes(fill=value)) +
geom_line(data=line)
I tried attributing the line values to the value of the nearest factor level, but this introduces a big error. Also, I tried the size option in geom_tile, but this didn't work out either.
In the example the y data is log transformed, but this is just for the ease of making a fake dataset.
Thank you.
Something like this??
ggplot(d, aes(x=Var1, y=Var2)) +
geom_tile(aes(fill=value)) +
geom_line(data=line)+
scale_y_continuous(trans="log2")
Note the addition of scale_y_continuous(trans="log2")
EDIT Based on OP's comment below.
There is no built-in "reverse log2 transform", but it is possible to create new transformations using the trans_new(...) function in package scales. And, naturally, someone has already thought of this: ggplot2 reverse log coordinate transform. The code below is based on the link.
library(scales)
reverselog2_trans <- function(base = 2) {
trans <- function(x) -log(x, base)
inv <- function(x) base^(-x)
trans_new(paste0("reverselog-", format(base)), trans, inv, log_breaks(base = base), domain = c(1e-100, Inf))
}
ggplot(d, aes(x=Var1, y=Var2)) +
geom_tile(aes(fill=value)) +
geom_line(data=line)+
scale_y_continuous(trans="reverselog2")
Perhaps another approach using a discrete scale and facets might be a possibility:
d <- data.frame(Var1=rep(1901:2000,10),Var2=rep(c(2,4,8,16,32),each=100),value=rnorm(500,50,5), chart="tile" )
d$Var2 <- factor(d$Var2, levels=rev(unique(d$Var2)))
line <- data.frame(Var1=1901:2000,Var2=rnorm(50,1.5,0.5), chart="line")
ggplot(d, aes(x=Var1, y=Var2)) +
geom_tile(aes(y = Var2, fill=value) ) +
geom_line( data=line ) +
scale_y_discrete() +
facet_grid( chart ~ ., scale = "free_y", space="free_y")
which gives a chart like: