similar to: Change positions of columns in data frame

Hi all, I've tried to make a 3D plot, but have run into some problems. I'd like to have a plot that I can rotate interactively using the mouse, which is possible using the plots3d {R.basic}. However, I would like to change the symbols used as the points, but there's no pch in plot3d(). If I use the Scatterplot3d package, I'm able to change this, but not able to rotate

Hello everybody, I'm using the lattice package and the xyplot to make several graphs like below. However, I can just print the three grouped plots onto one page as I'm putting them into a pdf-file, which gives me a huge amount of pages... Is it possible to put them all, or at least more than one on the same page, for instance put three groups beside each other like columns? ...

Hi all, I've got some problems when changing the trellis settings for the lattice plots. The plots look exactly as I want them to when calling show.settings() as well as when plotting them in the graphical window. But when printing to a pdf file, none of the settings are used!? Does anyone know what might have happened? Because the when changing the trellis settings, these should remain in

Hi all, I'm new to PCA in R, so this might be a basical thing, but I cannot find anything on the net about it. I need to make a PCA plot with two response variables (df$resp1 and df$resp2) against eight metabolites (df$met1, df$met2, ...) and I don't have a clue how to do... and I've only used the simplest PCAs before, like this: pcaObj=prcomp(t(df[idx, c(40:47)]))

Hi everybody, I'm using the method described here to make a linear regression: http://www.apsnet.org/education/advancedplantpath/topics/Rmodules/Doc1/05_Nonlinear_regression.html > ## Input the data that include the variables time, plant ID, and severity > time <- c(seq(0,10),seq(0,10),seq(0,10)) > plant <- c(rep(1,11),rep(2,11),rep(3,11)) > > ## Severity

Hi all, I guess this might be an easy question, but I've searched multiple help pages without finding any answear... so now I put my trust in you! I have a data frame (36 variables and 556 observations). One column contains three factors, and I would like to divide the data frame into three new ones, based on the value of the factors, thereby having only one value for all elements of the

Hi all, I'm making a PCA plot with eight variables (columns taken from a larger data frame "fieldTrial0809[idx,c(39:46)]"). I then want the symbols in the plot to be colored as a gradient from red to blue, depending on the value of another column in "fieldTrial0809[idx, c(48)]" containg temperatures from -12.1 to -5.4. I don't want to use the heat.colors(n)

Hi all, I'm searching for a way to exclude outliers from my dataset while making xyplots. While plotting using pairs(), I exclude specific row in my data frame and save the settings as a variable which I later include as an argument: # Discard outliers and save settings as idx idx=with(fieldTrial0809, which(Pro>0 & Pro<0.95 & Fum>0 & Fum<0.4 & Mal>0.1 &

Hi all, I would like to remove rows from a matrix, based on the frequency of missing values. If there are more than 10 % missing values, the row should be deleted. I use the following to calculate the frequencies, thereby getting a new matrix with the frequencies: freqNA=rowMeans(is.na(exprdata)) But is there a shorter way to remove the rows based on "(1-freqNA)>0.1"

Hi all, I have two question. First, I wonder how to remove a part of the column names in a matrix? I would like to remove the "_ACCX" or "_NAX" part below. Is there a method where the "_" as well as all characters after i can be removed? > dim(exprdata) [1] 88 512 > > colnames(exprdata[,c(1:20)]) [1] "Akita_ACC1" "Akita_ACC2"

Hi all, I'm trying to write a script that changes all negative values in a data frame column to a small positive value, based on the the minimum value of the column. However, I get the following error: Error in if (x[i] < 0) { : argument is of length zero As well, I would "minimum" to be the smallest of the non-negative values...

Hi all, I'm have a matrix (X) with observations as rows and parameters as columns. I'm trying to exchange all missing values in a column by the column mean using the code below, but so far, nothing happens with the NAs... Can anyone see where the problem is? N<-nrow(X) # Calculate number of rows = 108 p<-ncol(X) # Calculate number of columns = 88 # Replace by columnwise

Hi all, I need to replace missing values in a matrix by 10 % of the lowest available value in the matrix. I've got a function I've used earlier to replace negative values by the lowest value, in a data frame, but I'm not sure how to modify it... nonNeg = as.data.frame(apply(orig.df, 2, function(col) # Change negative values to a small value, close to zero { min.val =

Hi all, Does anyone know how to get the independent components and loadings from an Independent Component Analysis (ICA), as well as principal components and loadings from a Pricipal Component analysis (PCA) using the fastICA package? Or perhaps if there's another way to do ICAs in R? Below is an example from the fastICA manual (http://cran.r-project.org/web/packages/fastICA/fastICA.pdf)

Hi all, Anyone experienced in the LaTeX format? I'm trying to use the xtable package to create nice anova tables, but how do I do to produce a pdf from the resulting LaTeX table? I've tried WinShell and MiKTeX, but I couldn't get any of them working... Here's an example of the output in R: % latex table generated in R 2.9.2 by xtable 1.5-6 package % Tue Nov 24

I'm sorry everyone for the inconvenience of spamming the R-help... Here's the complete post: Hi everyone, > > Since it's quite a while that I used the reshape package, I now feel kind > of rusty. > > I have a data.frame like this: > > > > id Sample.Name Marker Allele.1 > Allele.2 sample_id species

Data has the first row for variable name and the first column for sample name. I want to take "Log" for all data, but how to compute without the first column for sample name. That is, column 1: sample ID column 2-10: data I want to find an average on each column (2-10) > apply(raw_data,2,mean) Error in Math.data.frame(list(sample_id = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, :

I have hundreds of humans who have undergone SNP genotyping at hundreds of loci. Some have even undergone the procedure twice or thrice (kind of an internal control). So obviously I need to find those replications, and confirm that the results are the same. If there is discordance then I need to address it. I tried to use the aggregate function nr.attempts

Hi, I have a page were users can start jobs that may take several hours to run. BackgrounDrb is perfect for me and seems to be working well most of the time but some times I have the following problem: My worker is set up like this: class UploadWorker < BackgrounDRb::MetaWorker set_worker_name :upload_worker set_no_auto_load(true) def create(args = nil ) file = args[:file]

hi guys..please help me with this i am working on two data frames one goes like this: DF1 Sample_id RepairHours Denatured Dose ZeroMean FourtyFiveMean NinetyMean 1 SDM071 0 1 B 60.5 19.0 45.0 2 SDM071 1 1 B 46.0 23.0 42.5 3 SDM071 2 1 B 52.5 24.0 40.0 4 SDM071