similar to: taking the median across similar data

Hello all, I have what feels like a simple problem, but I can't find an simple answer. Consider this data frame: > x <- data.frame(sample1=c(35,176,182,193,124), sample2=c(198,176,190,23,15), sample3=c(12,154,21,191,156), class=c('a','a','c','b','c')) > x sample1 sample2 sample3 class 1 35 198 12 a 2 176 176

This is what I am starting with: initial<- matrix(c(1,5,4,8,4,4,8,6,4,2,7,5,4,5,3,2,4,6), nrow=6, ncol=3,dimnames=list(c("1900","1901","1902","1903","1904","1905"), c("sample1","sample2","sample3"))) And I need to apply a filter (in this case, any value <5) to give me one dataframe with only the

[Perhaps someone could rename this list to dtrace-matt-problems-discuss?] If I run this script against my binary (which contains a USDT probe called ''concurrentq-latency''): ::: / probename == "concurrentq-latency" / { printf("[%s]:[%s]:[%s]\n", probeprov, probefunc, probename); } I get this output: dtrace: script ''testq.d'' matched 46056

Dear experts, Please forgive the puzzled title and the length of this message - I thought it would be best to be as complete as possible and to show the avenues I have explored. I'm trying to fit a linear model to data with a binary dependent variable (i.e. Target.ACC: accuracy of response) using lrm, and thought I would start from the most complex model (of which "sample1.lrm1" is

Hi all, I am processing 24 samples data and combine them in single table called CombinedSamples using following: CombinedSamples<-rbind(Sample1,Sample2,Sample3) Now variables Sample1, Sample2 and Sample3 have many different columns. To make it more flexible for other samples I'm replacing above code with a for loop: #Sample is a string vector containing all 24 sample names for (k in

Hi Group, I have a data frame below. Within this data frame there are samples (columns) that are measured more than once. Samples are indicated by "idx". So "id1" is present in columns 1, 3, and 5. Not every id is repeated. I would like to create a new data frame so that the repeated ids are averaged. For example, in the new data frame, columns 1, 3, and 5 of the original

Dear all, Here is my code which am using to combine 5th column from different data sets. Here is the function to do my job genesymbol.append.file <-NULL gene.column <- NULL readGeneSymbol <- function(files,genesymbol.column=5){ for(i in fnames){ temp <- read.table(fnames,header=T,sep="\t",stringsAsFactors=F,quote="\"")

Hi, I just started using R for about one week and I have few problems. i)I have a problem in finding right function to convert a table of natural numbers to bitwise. For a simple example; I have the below table:- Column Col1 Col2 Col3 Sample1 5 7 10 Sample2 0 2 1 Sample3 4 0 0 Supposedly i wanted to convert to :- Column Col1 Col2 Col3

Hello R list members, I'm a bio informatics student from the Leiden university (netherlands). We were asked to make a program with different clustering methods. The problem we are experiencing is the following. we have a matrix with data like the following research1 research2 research3 enz sample1 0.5 0.2 0.4 sample2 0.4

[1] Predicates in one-liners I would like to list the probe modules in my executable and then dynamically create a dscript to trace execution of those modules alone (by excluding the 3rd party and system libraries). I tried the below script without success. The conditional given in the predicate is not taking effect. Why is this so ? $ dtrace -ln ''pid$target:::

Hi, I've restarted my Elsa/LLVM project after three months of having real life intrude. I upgraded my LLVM source to the current trunk. I had to make a few changes to my source, e.g. LLVMFoldingBuilder became IRBuilder and several instances of "new" became "Create". Now, a test case that previously succeeded fails. I run the following script: #!/bin/sh if [ 1 -ne 0 ]

Hi all, As a molecular biologist by training, I'm fairly new to R (and statistics!), and was hoping for some advice. First of all, I'd like to apologise if my question is more methodological rather than relating to a specific R function. I've done my best to search both in the forum and elsewhere but can't seem to find an answer which works in practice. I am carrying out

I am wanting to plot a 95% confidence band using segplot, yet I am wanting to have groups. For example if I have males and females, and then I have them in different races, I want the racial groups in different panels. I have this minor code, completely made up but gets at what I am wanting, 4 random samples and 4 samples of confidence, I know how to get A & B into one panel and C&D in to

Dear R experts, code: >m<-read.table("test.txt",sep='\t',header=TRUE,colClasses=c('character','integer','integer','rep('numeric',150)) > s<-data.frame(c(rle(m$Sample1)[[2]],rle(m$Sample2)[[2]],rle(m$Sample3)[[2]]),c(rle(m$Sample1)[[1]],rle(m$Sample2)[[1]],rle(m$Sample3)[[1]])) > names(s)=c("Values","Probes")

Dear Dr.Goslee and anyone may intrested in matrix manipulate, I am using your ecodist to do mantel and partial mantel test, I have locality data and shape variation data, and the two distance matrixs are given as belowings. When I run the analysis, it is always report that the matrix is not square, but I didn't know what's wrong with my data. Would you please help me on this. I am quite

Dear group, I have a matrix like the following: Name Sample1 sample2 sample3 sample4 ..... sample(n) nm1 10.5 13.5 30 31 nm2 8 11 34 29 nm3 9 10.3 27.8 35 nm(j) I want to be able to calculate correlation between all pairs of names. For example (nm1,nm2),

Dear R-Helpers, I have a data.frame (df) and the head of data.frame looks like ProbeUID ControlType ProbeName GeneName SystematicName 1665 1577 0 pSysX_50_22_1 pSysX_50 pSysX_50 5422 5147 0 pSysX_49_8_1 pSysX_49 pSysX_49 4042 3843 0 pSysX_51_18_1 pSysX_51 pSysX_51 3646 3466 0 sll1514_0_2 sll1514 sll1514

[CC:ing package maintainer of 'impute' package and crossposting to r-devel and bioc-devel because this affects both audiences] Hi, the 'impute' package is published both on CRAN and Bioconductor; http://cran.r-project.org/web/packages/impute/ http://bioconductor.org/packages/2.3/bioc/html/impute.html The one on CRAN is v1.0-5, and the one on BioC is v1.14.0. The two

Hello, I have a data frame with a factor column, which uniquely identifies the observations in the data frame and it looks like this: sample1_condition1_place1 sample2_condition1_place1 sample3_condition1_place1 . . . sample3_condition3_place3 I want to turn it into three separate factor columns "sample", "condition" and "place". This is what I did so far: #

## you may need to install HH install.packagess("HH") library(HH) hellisheidi <- read.table(text=" Component Sample1 Sample2 Sample3 CaO 45 52 48 SiO2 25 22 18 Al2O3 15 11 14 TiO2 6 5