[R] Neat way of using R for pivoting?

[Liaw, Andy]

> From: Greg Snow
> 
> >>> "BANNISTER, Keith" <keith.bannister at astrium.eads.net> 09/20/05
> 09:46AM >>>
> >> 
> >> Hi,
> >> 
> >> I'd like to use R to do what excel pivot tables do, and plot
> results.
> 
> R does not have pivot tables and I hope that it never does.
> 
> My experiance with pivot tables is that they encourage poor initial
> design followed
> by non-easily-reproducable post-hoc twiddling.
> 
> R encourages proper initial design followed by fixing the core design
> in cases
> where things don't turn out the way you intended. 
>  
> In R I prefer to work with script files and save the file.  If the
> table or graph
> does not turn out the way I intended, then I just edit the script file
> and rerun it.
> While this may be a little more work than clicking on a pivot table at
> first, in the 
> long run I find it saves more time.

Actually, it's even better to write functions for repetitive tasks.
This is one of the things Martin talked about at useR! 2004:
http://www.ci.tuwien.ac.at/Conferences/useR-2004/Keynotes/Maechler.pdf

For Keith's problem, here's one possibility (using plotCI() from gplots):

myErrorBarPlot <- function(SNR, timeError, ...) {
    stopifnot(require(gplots))
    m <- aggregate(timeError, list(SNR), mean)
    d <- aggregate(timeError, list(SNR), sd)
    dat <- cbind(m, d[, 2])
    names(dat) <- c("SNR", "mean", "sd")
    dat$SNR <- as.numeric(as.character(dat$SNR))
    with(dat, plotCI(SNR, mean, uiw=3*sd, ...))
    invisible(dat)
}

vn <- read.table("clipboard", header=TRUE)

myErrorBarPlot(vn$SNR, vn$timeError)

Andy
 
> Consider the situation where you create a table/graph, then a month
> later your
> boss/client/coworker finds some typos in the original data and needs
> the table
> and/or graph recreated with the corrected data (or maybe a new dataset
> that
> needs a similar graph/table).  With the pivot table you need 
> to try and
> remember
> everything that you clicked on and click on it again.  With the R
> script file you 
> just fix the data (or load in the new data) and rerun the script and
> your done.
> 
> OK, enough of my ranting, on to helping with your problem.
> 
> 
> >> I've never used R before, and I've managed to do 
> something, but it's
> quite a
> >> lot of code to do something simple. I can't help but think I'm not
> "Doing it
> >> the R way".
> >> 
> >> I could be using R for the wrong thing, in which case, please tell
> me off.
> [snip]
> 
> "by" is a bit of an overkill for this situation, tapply will probably
> work better.
> 
> try this basic script as a starting place:
> 
> ### start ###
> my.df <- data.frame( SNR=rep( c(4,6,8), each=3), 
> 	timeError = c(1.3,2.1,1.2,2.1,2.2,2.1,3.2,3.7,3.1))
> 
> tmp.mean <- tapply( my.df$timeError, my.df$SNR, mean)
> tmp.sd   <- tapply( my.df$timeError, my.df$SNR, sd)
> 
> tmp.x <- unique(my.df$SNR)
> 
> plot( tmp.x, tmp.mean,
> ylim=range(tmp.mean+3*tmp.sd,tmp.mean-3*tmp.sd),
> 	xlab='SNR',ylab='timeError')
> 
> segments(tmp.x, tmp.mean-3*tmp.sd, tmp.x, tmp.mean+3*tmp.sd,
> col='green')
> 
> ### optional
> points(tmp.x, tmp.mean+3*tmp.sd, pch='-',cex=3,col='green')
> points(tmp.x, tmp.mean-3*tmp.sd, pch='-',cex=3,col='green')
> points(tmp.x, tmp.mean)
> 
> ### end script ###
> 
> This may be even simpler with a loaded package. a quick search shows
> the following functions (package in parens) that may help:
> 
> plotCI(gplots)          Plot Error Bars and Confidence Intervals
> errbar(Hmisc)           Plot Error Bars
> xYplot(Hmisc)           xyplot and dotplot with Matrix Variables to
> Plot Error Bars and Bands
> 
> plotCI(plotrix)         Plot confidence intervals/error bars
> 
> errbar(sfsmisc)         Scatter Plot with Error Bars
> plotCI(sfsmisc)         Plot Confidence Intervals / Error Bars
> 
> 
> 
> 
> >> Appreciate any helpful hints from the pros.
> >> 
> 
> hope this helps,
> 
> >> Cheers!
> >> 
> >> p.s. We've been having rather a good time around the 
> office recently
> with
> >> "International Talk Like a Pirate Day" (www.yarr.org.uk). R fits in
> very
> >> well: "I be usin' Arrrgghhhh for my post processin'".
> >> 
> >> 
> >> Keith Bannister
> 
> 
> Greg Snow, Ph.D.
> Statistical Data Center, LDS Hospital
> Intermountain Health Care
> greg.snow at ihc.com
> (801) 408-8111
> 
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