Dear Baptiste,
Thanks a lot for the excellent example, which convinced me to start
studying ggplot2.
A trivial question: is there an easy way to generate a boxplot without
outliers?
Using R standard plotting facilities, this amounts to giving
outline=FALSE within boxplot.
Can I easily achieve the same using ggplot2? Beside not plotting the
outliers, I also would like the y range to adjust automatically.
I did some online research, someone suggested preprocessing the data,
but I can hardly believe that this is the only way to go.
Cheers
Lorenzo
baptiste auguie wrote:
I forgot the base graphics way,
## divide the window in 4x4 cells
par(mfrow=n2mfrow(length(datasets)))
## loop over the list of datasets and plot each one
be.quiet <- lapply(datasets, function(ii) boxplot(y~x, data=ii))
ggplot2 has a website with many examples,
http://had.co.nz/ggplot2/
as well as a book.
Lattice also has a dedicated book, and a companion website with the figures,
http://r-forge.r-project.org/projects/lmdvr/
HTH,
baptiste
2009/12/29 baptiste auguie <baptiste.aug...@googlemail.com>:
Hi,
Here is some artificial data followed by minimal ggplot2 and lattice examples,
makeUpData <- function(){
data.frame(x=sample(letters[1:4], 100, repl=TRUE), y=rnorm(100))
}
datasets <- replicate(15, makeUpData(), simplify=FALSE)
names(datasets) <- paste("dataset", seq_along(datasets), sep="")
str(datasets)
require(reshape)
## combine the datasets in one long format data.frame
m <- melt(datasets, meas=c("y"))
str(m)
require(ggplot2)
ggplot(m)+
geom_boxplot(mapping=aes(x, value))+
facet_wrap(~L1)
# or more concisely
qplot(x, value, data=m, geom="boxplot", facets=~L1)
require(lattice)
bwplot(value~x | L1, data=m)
HTH,
baptiste
2009/12/29 Lorenzo Isella <lorenzo.ise...@gmail.com>:
Dear All,
I am given 15 different data sets and I would like to generate a panel
showing all of them.
Each dataset will be presented either as a boxplot or as a histogram.
There are several possible ways to achieve this (as far as I know)
(1) using plot and mfrow()
(2) using lattice
(3) using ggplot/ggplot2
I am not very experienced (to be euphemistic) about (2) and (3).
My question then is: how would you try to organize these 15
histograms/boxplots into a single figure?
Can anyone provide me with a simple example (with artificial data) for
(2) and (3) (or point me to some targeted online resource)?
Any suggestion is welcome.
Many thanks
Lorenzo
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