similar to: data conversion (possibly with reshape package)

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 all, Probably a simple question, but I just can't find a simple answear in the older threads or anywhere else. I've added some new vectors as columns in a data frame using cbind(). As they're all put as the last columns inte the data frame, I would like to move them to specific positions. How do you do to change the position of a column in a data frame? I know I can use

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

Many thanks for your responses. I realize I made the first-time-poster's error of not giving an example of the data. There actually are no NA values, so I'm not simply replacing values in the data frame. So, the number of species (and therefore abundance values) listed in each treatment differs, even though they all have the same number of plots sampled. Sample_ID Spec_num Species_ID