similar to: transforming a dataset for association analysis RESHAPE2

Hi I would like to transform a data frame like Subject Item Score Subject 1 Item 1 1 Subject 1 Item 2 0 Subject 1 Item 3 1 Subject 2 Item 1 1 Subject 2 Item 2 1 Subject 2 Item 3 0 .... *to * Subject Item1 Item2 Item3 .....Item N Subject1 1 0 1 Subject2 1 1 0 ........ SubjectP.. Apologize for the simple nature of my query but I am stuck.

Dear List Sorry if this question seems very basic. Is there a function to pro grammatically find number of processors in my system _ I want to pass this as a parameter to snow in some serial code to parallel code functions Regards Ajay Websites- http://decisionstats.com http://dudeofdata.com Linkedin- www.linkedin.com/in/ajayohri

Dear List Forgive me for the slightly off topic query Force.com and Salesforce have many (1009) apps at http://sites.force.com/appexchange/home for cloud computing for businesses, but very few forecasting and statistical simulation apps. Example of Monte Carlo based app is here http://sites.force.com/appexchange/listingDetail?listingId=a0N300000016cT9EAI# These are like iPhone apps except

Dear List Forgive me for the slightly off topic query Force.com and Salesforce have many (1009) apps at http://sites.force.com/appexchange/home for cloud computing for businesses, but very few forecasting and statistical simulation apps. Example of Monte Carlo based app is here http://sites.force.com/appexchange/listingDetail?listingId=a0N300000016cT9EAI# These are like iPhone apps except

I seem to be running into the same problem reported in https://stat.ethz.ch/pipermail/r-help/2010-November/258265.html I cannot seem to transform a dataset from long to wide using reshape2. Clearly I am missing something very simple but a look at the manual and the reshape paper in JSS does not suggest anything. Any advice would be welcome ===========================load

Hi all, Has any folk tested or been using RKward? Please shed me some light whether it takes data from the spreadsheet, analyzes the data and puts the data back to the spreadsheet, similar to RExcel and "R and Calc". Or RKward is only an editor of R, working on front-end? I have tested RExcel but it works on Windows. I need a Linux version of similar package. "R and

Hi, who of you in this forum uses R (http://www.r-project.org/) with the multicore, SNOW or CUDA packages, so for advanced calculations that need more power than a workstation CPU? On which hardware do you compute these scripts? At home/ at work or do you have data center access somewhere? The background of these questions is the following: I am currently writing my M.Sc. thesis about R and

Dear List I just downloaded and installed R 2.12.0 and then installed R Commander . First it got RCmdr and Car, and then suggested for other packages for utilizing the full functionality- I clicked yes! I got 140 packages installed!!! Cran Mirror was UCLA... Here is the list. Is this intentional- I can see some packages like snow and multicore which are desirable but quite optional.(see list

The Rserve documentation at http://rosuda.org/Rserve/doc.shtml#start states that even when making multiple connections to the Rserve, Windows won't separate workspaces physically and share environments, which will obviously cause problems and should therefore not be used. Are there any alternatives for the windows platform? Ralf

Hi Bill, I put stringsAsFactors = FALSE still did not work. tdat <- read.table(textConnection("A B C Y A12 B03 C04 0.70 A23 B05 C06 0.05 A14 B06 C07 1.20 A25 A23 A12 3.51 A16 A25 A14 2,16"),header = TRUE ,stringsAsFactors = FALSE) tdat$D <- 0 tdat$E <- 0 tdat$D <- (ifelse(tdat$B %in% tdat$A, tdat$A[tdat$B], 0)) tdat$E <- (ifelse(tdat$B %in% tdat$A, tdat$A[tdat$C], 0))

Hello, Here is one way. tdat$D <- ifelse(tdat$B %in% tdat$A, tdat$A[tdat$B], 0) tdat$E <- ifelse(tdat$B %in% tdat$A, tdat$A[tdat$C], 0) Hope this helps, Rui Barradas On 12/13/2017 9:36 PM, Val wrote: > Hi all, > > I have a data frame > tdat <- read.table(textConnection("A B C Y > A12 B03 C04 0.70 > A23 B05 C06 0.05 > A14 B06 C07 1.20 > A25 A23 A12 3.51

Thank you Rui, I did not get the desired result. Here is the output from your script A B C Y D E 1 A12 B03 C04 0.70 0 0 2 A23 B05 C06 0.05 0 0 3 A14 B06 C07 1.20 0 0 4 A25 A23 A12 3.51 1 1 5 A16 A25 A14 2,16 4 4 On Wed, Dec 13, 2017 at 4:36 PM, Rui Barradas <ruipbarradas at sapo.pt> wrote: > Hello, > > Here is one way. > > tdat$D <- ifelse(tdat$B %in% tdat$A,

Use the stringsAsFactors=FALSE argument to read.table when making your data.frame - factors are getting in your way here. Bill Dunlap TIBCO Software wdunlap tibco.com On Wed, Dec 13, 2017 at 3:02 PM, Val <valkremk at gmail.com> wrote: > Thank you Rui, > I did not get the desired result. Here is the output from your script > > A B C Y D E > 1 A12 B03 C04 0.70 0 0

Hi all, I have a data frame tdat <- read.table(textConnection("A B C Y A12 B03 C04 0.70 A23 B05 C06 0.05 A14 B06 C07 1.20 A25 A23 A12 3.51 A16 A25 A14 2,16"),header = TRUE) I want match tdat$B with tdat$A and populate the column values of tdat$A ( col A and Col B) in the newly created columns (col D and col E). please find my attempt and the desired output below Desired output

Hey Folks, Could somebody help me rewrite the following code? I am looping through all records across 5 fields to calculate the cumulative percentage of each record (relative to each individual field). Is there a way to rewrite it so I don't have to loop through each individual record? ##### tdat is my data frame ##### j is my field index ##### k is my record index ##### tsum is the sum of

Dear Group, I'm having lots of problems getting RMySQL on a 64 bit machine. I followed all instructions available but couldn't get it working yet! Please help. See the output below. I did a install of RMySQL binary from the revolution cran source. It seems to have unpacked fine but gives this error when I call RMySQL Error: package 'RMySQL' is not installed for 'arch=x64'

Hello Everyone,   Just finished reading A Handbook of Statistical Analyses using R by Everitt and Hothorn. I'll begin by saying that I quite liked the book. It's both little and mighty in the sense that it's very compact but contains a tremendous amount of useful material.   The last chapter of the book deals with cluster analysis.  There's a package used in this chapter (I believe

Hi Hadley et all, I am struggling with reshape2 and melt works and melt_check (filtered151) seems fine My cast command was acast (filtered151, Time ~ Species ~ Number) > melt_check (filtered151) Using time, Species as id variables $id [1] "time" "Species" $measure [1] "Number" When I execute cast the data matrix is in the correct order but the data

... and similar to Jim's suggestion but perhaps slightly simpler (or not!): > cross <- xtabs( Y ~ stat + year, data = tdat) > keep <- apply(cross, 1, all) > keep <- names(keep)[keep] > cross[keep,] year stat 2003 2004 2006 2007 2009 2010 AL 38 21 20 12 16 15 NY 50 51 57 98 183 230 > ## for counts just do: > xtabs( ~ stat + year, data

Thank you Bert and Jim, Jim, FYI , I have an error message generated as Error in allstates : object 'allstates' not found Bert, it is working. However, If I want to chose to include only mos years example, 2003,2004,2007 and continue the analysis as before. Where should I define the years to get as follow. 2003 2004 2007 AL 2 1 1 NY 1 1 2 Thank you