Thanks Gabor - I was able to use that for my purposes. On 11 June 2010 16:27, Bert Gunter <gunter.ber...@gene.com> wrote:
> So two time series? Fair enough. But less is more. Plot them as separates > series of points connected by lines, different colors for the two different > series. Or as two trellises plots. You may also wish to overlay a smooth to > help the reader see the "trend"(e.g via a loess or other nonparametric > smooth, or perhaps just a fitted line). > > The only part of a bar that conveys information is the top. The rest of the > fill is "chartjunk" (Tufte's term) and distracts. > > > I'll keep this in mind. I am just using this chart for my own analysis now, and probably won't include it later. > Bert Gunter > Genentech Nonclinical Biostatistics > > > > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] > On > Behalf Of Ian Bentley > Sent: Friday, June 11, 2010 12:15 PM > To: Bert Gunter > Cc: r-help@r-project.org; Hadley Wickham > Subject: Re: [R] Transforming simulation data which is spread > acrossmanyfiles into a barplot > > I'm not trying to see the relation between sent and received, but rather to > show how these grow across the increasing complexity of the 50 data points. > > On 11 June 2010 15:02, Bert Gunter <gunter.ber...@gene.com> wrote: > > > Ouch! Lousy plot. Instead, plot the 50 (mean sent, mean received)pairs > as > > a > > y vs x scatterplot to see the relationship. > > > > Bert Gunter > > Genentech Nonclinical Biostatistics > > > > > > > > -----Original Message----- > > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] > > On > > Behalf Of Hadley Wickham > > Sent: Friday, June 11, 2010 11:53 AM > > To: Ian Bentley > > Cc: r-help@r-project.org > > Subject: Re: [R] Transforming simulation data which is spread across > > manyfiles into a barplot > > > > On Fri, Jun 11, 2010 at 1:32 PM, Ian Bentley <ian.bent...@gmail.com> > > wrote: > > > I'm an R newbie, and I'm just trying to use some of it's graphing > > > capabilities, but I'm a bit stuck - basically in massaging the already > > > available data into a format R likes. > > > > > > I have a simulation environment which produces logs, which represent a > > > number of different things. I then run a python script on this data, > and > > > putting it in a nicer format. Essentially, the python script reduces > the > > > number of files by two orders of magnitude. > > > > > > What I'm left with, is a number of files, which each have two columns > of > > > data in them. > > > The files look something like this: > > > --1000.log-- > > > Sent Received > > > 405.0 3832.0 > > > 176.0 1742.0 > > > 176.0 1766.0 > > > 176.0 1240.0 > > > 356.0 3396.0 > > > ... > > > > > > This file - called 1000.log - represents a data point at 1000. What I'd > > like > > > to do is to use a loop, to read in 50 or so of these files, and then > > produce > > > a stacked barplot. Ideally, the stacked barplot would have 1 bar per > > file, > > > and two stacks per bar. The first stack would be the mean of the sent, > > and > > > the second would be the mean of the received. > > > > > > I've used a loop to read files in R before, something like this --- > > > > > > for (i in 1:50){ > > > tmpFile <- paste(base, i*100, ".log", sep="") > > > tmp <- read.table(tmpFile) > > > } > > > > > > > # Load data > > library(plyr) > > > > paths <- dir(base, pattern = "\\.log", full = TRUE) > > names(paths) <- basename(paths) > > > > df <- ddply(paths, read.table) > > > > # Compute averages: > > avg <- ddply(df, ".id", summarise, > > sent = mean(sent), > > received = mean(received) > > > > You can read more about plyr at http://had.co.nz/plyr. > > > > Hadley > > > > -- > > Assistant Professor / Dobelman Family Junior Chair > > Department of Statistics / Rice University > > http://had.co.nz/ > > > > ______________________________________________ > > R-help@r-project.org mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > > > > > > -- > Ian Bentley > M.Sc. Candidate > Queen's University > Kingston, Ontario > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > -- Ian Bentley M.Sc. Candidate Queen's University Kingston, Ontario [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
