similar to: Dual axis labeling of a single quantity

All: I am using the command: qplot(date,MAE,data=data,facets=INTERVAL~type) which works fine except that the dates for my date axes are crunched together so much that they are unreadable. I can not find an option that I can set that will automatically reduce the x-axis labels to fit the available space. regards to all? -- Thomas E Adams National Weather Service Ohio River Forecast Center

I'm interested in creating a graphic -like- this: c <- ggplot(mtcars, aes(qsec, wt)) c + geom_point() + stat_smooth(fill="blue", colour="darkblue", size=2, alpha = 0.2) but I need to show 2 sets of bands (with different shading) using 5%, 25%, 75%, 95% limits that I specify and where the heavy blue line is the median. I don't understand how to do this with

All: I am using RSqlite and want to be able to update individual values in a record, such as with this simple example: library(RSQLite) drv<-dbDriver("SQLite") con<-dbConnect(drv,"test.db") my.data<-data.frame(countries=c("US","UK","Canada","Australia","NewZealand"),vals=c(52,36,74,10,98))

List: I have 2 related questions: (1) first I have x-y-z data, where x & y are the geographic locations of point values, z. I need to perform a normal score transform on the z-values and maintain their geographic location. So, how do I go from columns x-y-z to x-y-z-t (or x-y-t), where the t-values are the normal score transforms of the z-values? Can I use qnorm(ppoints(data)) to do

I have data that I read in using: data<-read.table("RAVK2.obs.data",sep="\t") 'data' looks like this: V1 V2 1 2009-03-25 06:00:00 12.86 2 2009-03-25 12:00:00 12.80 3 2009-03-25 18:00:00 12.76 4 2009-03-26 00:00:00 12.68 5 2009-03-26 06:00:00 12.66 6 2009-03-26 12:00:00 12.64 7 2009-03-26 18:00:00 12.83 8 2009-03-27 00:00:00 13.33 9

List, I have looked through several R books and searched the web to find answers to my questions with no results. I have a ensembles of time series data (essentially from Monte Carlo simulations) which I would like to summarize as a time series of boxplots. I don't know how to do this and I am not sure how I should structure the data to get what I want. Another related question: while

All: Attached is the output file from building R 2.10.0 on RedHat Linux. I have never previously experienced any problems when building R from source with new releases. But, now I get a compile error with the Matrix package: CHOLMOD/Include/cholmod.h:87:22: error: UFconfig.h: No such file or directory make[3]: *** [CHMfactor.o] Error 1 make[3]: Leaving directory

Please, I am receiving lot of e-mails that I do not want. Please could you delete my e-mail. Thank, Judit -----Original Message----- From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Thomas Adams Sent: Monday, December 12, 2011 3:22 PM To: Bert Gunter Cc: r-help at r-project.org Subject: Re: [R] Boxplot of multiple vectors with different lengths Bert,

I am trying to use t.test on the following data: date type INTERVAL nCASES MTF SDF MTO SDO nFST MF nOBS MO MB BIASCV BIASEV ME MAE RMSE CRCF 2001-06-15 avn GE1.00 4385 0.246 0.300 1.502 0.556 1367 1.373 4385 1.502 1.471 0.285 0.164 -1.256 1.266 1.399 0.056 2001-06-15 avn

I have looked at many examples and tried many different combinations of doing this, but with no luck. I have something like this: plot(1:10, xaxt = "n") axis(1, xaxp=c(2, 9, 7)) axis(4) but, what I need is to have different labels for axis-4 than those for axis-2 (the vertical axes) ? that is, rather than 2,4,6,8,10 for both the left and right vertical axes, I need A,B,C,D,E on the

Hello, I'm attempting to write a code that automatically imports data from different files (with different lengths-just one variable) and makes tidy box plots for comparison. I can successfully import the data and create a list of the vectors I want to compare. But I cannot, for the life of me, figure out how to generate box plots using the "list" option. Suppose these are my data:

I'm getting a MacBook and I'd like to stick with OS X rather than convert it to Linux just yet. However, my main concern is having decent performance. What's my best option: *use the existing binary for R? *compile R fresh under OS X? * install Linux and run R under that? Does anyone have any recent experience they can share? Thanks! -- I can answer any question. "I

Dear all, is Sweave working on MAC ? I installed R-2.5.1 but seems like Sweave is not coming with the distribution as it comes on linux. Do I need to install it separately ? In that case is there a .dmg for mac ? Thanks for the help! Regards Marco [[alternative HTML version deleted]]

Hi, I like to know the simple way to list the R package names in our linux system. Thanks Ying [[alternative HTML version deleted]]

Hi, I've been using R on my OS X machine this school year, and have been really enjoying it. I recently formatted my machine and installed OS X Leopard. When I try to install the OS X R package on Leopard, R's installer tells me I have the wrong version of R for my version of OS X. I downloaded the most recent version, and looked for a Leopard-specific one, but haven't found one.

Quoting from today's PhD Comics, available at: http://www.phdcomics.com/comics.php?f=1476 What the methodology section says: "Analysis was performed using a commercially available software package." What it really means: "I put the numbers into this magic box and out came my thesis!" -- Sarah Goslee http://www.functionaldiversity.org

http://www.cs.purdue.edu/homes/jv/pubs/ecoop12.pdf A new paper out on R the language -- I'm not all the way through it but it's been an interesting read so far. Thought it might be of interest to the list. Michael Weylandt [[alternative HTML version deleted]]

Dear R-helpers, I am trying to download some netcdf4 files from the Climate Explorer Website: http://climexp.knmi.nl/start.cgi?id=someone at somewhere In fact, there are 78 distinct files. I have found a way to download a particular file and open it in R, but I have been informed that there exists some code to automatically download all the files. Do you have any clue regarding how to achieve

Hi, Is there any method in R by which I can solve PDEs? Thank you, Amit [[alternative HTML version deleted]]

Hello, are there people outside who use R for analysis of wind-measurement data (meteorological or for planning of wind power stations)? Are there already scripts/modules available for analysing and displaying/plotting wind data in the way it is done in projection/planning of wind power stations? If not, would it be of interest to use R for this, and therefore adapt data-logger output to R (by