similar to: separate row averages for different parts of an array

Hi all, I have a dataframe with survey data. Now I want to calculate means from several but not all columns (e.g. a1, a2, a3) and save them in a new separate column (e.g. a). Like: a = mean(a1, a2, a3) Can someone help me or give me the right key word to look for? Thanks [[alternative HTML version deleted]]

[text file is also attached in case you find the format of email difficult to understand] Dear useRs,You must all the planning for the christmas, but i am stucked in my office on the following issue i had a file containg information about station name, year, month, day, and discharge information. i opened it by using following command > dat1<-read.table("EL.csv",header=TRUE,

Hello , I can not get apply function to do what I want when doing stuff on rows. Let's say I want to divide the rows of matrix by their mean, the below show you get the same result weather you use 1 or 2, i.e. same result for columns than for means..:( Thanks a lot for the help, m = matrix( c(1,4,7,4,5,8,7,8,9), nrow = 3 ) divideByMean = function( v ){ return(

Greetings listeRs - Given a data frame such as times time1 time2 time3 time4 1 70.408543 48.92378 7.399605 95.93050 2 17.231940 27.48530 82.962916 10.20619 3 20.279220 10.33575 66.209290 30.71846 4 NA 53.31993 12.398237 35.65782 5 9.295965 NA 48.929201 NA 6 63.966518 42.16304 1.777342 NA one can use "transform" to

Hi, Currently, the "base" has colSums, colMeans. It seems that it would be useful to extend this to also include colMin, colMax (of course, rowMin and rowMax, as well) in order to facilitate faster computations for large vectors (compared to using apply). Has this been considered before? Please forgive me if this has already been discussed before. Thanks, Ravi Ravi Varadhan, Ph.D.

Hello, I have some dataset, which i read it from external file using the (data <- read.csv("my file location")) and read as a dataframe > is(data) [1] "data.frame" "list" "oldClass" "vector" but i have also converted this into a matrix and tried to apply my code but didnt work. Anyways, suppose i have the following data.

useRs, I have a data frame where four of the columns of the data frame represent the values of a two-by-two matrix. I'd like to, row-by-row, go through the data frame and use the four columns, in matrix form, to perform calculations necessary to create new values for variables in the data frame. My first idea was to use apply: apply(as.array(data.frame[,1:4]), 1, matrix, nrow=2) Though

Suppose I have the following: x1<-as.vector(rnorm(10)) x2<-as.vector(rnorm(10)) x3<-as.vector(rnorm(10)) x4<-as.vector(rnorm(10)) x5<-as.vector(rnorm(10)) x6<-as.vector(rnorm(10)) x7<-as.vector(rnorm(10)) x8<-as.vector(rnorm(10)) x9<-as.vector(rnorm(10)) x10<-as.vector(rnorm(10)) I would like the mean of x1 to x6 for each vector position. I would do something else

Hi, I have a matrix: mymat <- matrix(runif(10*4), ncol=4) I wish to subtract the column means, down the colums, subtract the row means from the rows and add back the grand mean - all the means should be the means of mymat rather than of the new matrix. How can I do this? Any help much appreciated. Thanks Tom _________________________________________________________________

Hi everyone, I have dataset which I make a sample of it couple of times and each time I get the mean and standard deviation of each row for each sample. I have a function for that, which takes the name of the file and number of times to sample and then returns the mean and standard deviation for each row in each sample. Sample=function(name, n){

Hi, I am analysing gene expression data using the heatmap.2 function in R and I was wondering what is the formula of the "raw z-score" bar which shows the colors for each pixel. According to that post: https://mailman.stat.ethz.ch/pipermail/r-help/2006-September/113598.html, it is the (actual value - mean of the group) / standard deviation. But, mean of which group? Mean of the gene

In a newly downloaded version (today) of R-2-4-0alpha, with all packages from CRAN also installed today, I get: > library(Matrix) Erro en loadNamespace(package, c(which.lib.loc, lib.loc), keep.source = keep.source) : in 'Matrix' methods specified for export, but none defined: BIC, anova, coef, confint, deviance, fitted, fixef, formula, head, lmer, logLik, mcmcsamp, plot,

Hi All, I am illustrating a simple, two-way ANOVA using the following data and I'm having difficulty in expressing the predicted values succinctly in R. X<- data.frame(read.table(textConnection(" Machine.1 Machine.2 Machine.3 53 61 51 47 55 51 46 52 49 50

Hi everyone! I'm trying to teach myself R in order to do some data analysis. I'm a mathematics student and (only) familiar with matlab and latex. I'm working trough the "official" introduction to R at the moment, while simultaneously solving some exercises I found in the web. Before I post my (probably stupid) question, I'd like to ask you for some general advice. How do

Dear all, I am so ashamed to pollute the list with a trivial question, but it is a long time I have not used R, and I need a result in the next one or two hour... I have a table which I have loaded with read.table, and I want to make the mean of its columns. > slides <- read.table("slides.txt") > slides [1:5,] V1 V2 V3 V4 V5 V6 V7 V8 1

Hi people, If there is a fn "colMeans" why isn't there a "colSDs" etc Thanks, Phil. -- Philip Rhoades Pricom Pty Limited (ACN 003 252 275) GPO Box 3411 Sydney NSW 2001 Australia Mobile: +61:0411-185-652 Fax: +61:2:8923-5363 E-mail: pri at chu.com.au -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

I have a list of data frames like the following: set.seed(123) a<- data.frame(x=runif(10), y = runif(10), sample = seq(1,10)) b<- data.frame(x=runif(10), y = runif(10), sample = seq(1,10)) L<- list(a,b) All data frames in the list have the same dimensions. I need to calculate the sample means for x and y. The real data are lists of several thousand quite large dataframes, so I need

Hi naive question. It is possible to get R command for omitting rows or cols with missing values present. But if i want to omit rows or cols with i.e . >20% missing values, I could´t find any package-based command, probably because it is too simple for anyone to do that manually, though not for me. Can anyone please help me ? - vickie [[alternative HTML version

Dear, I'm doing analysis where I need to work on relatively large (50-60 MB) text files, though I'm really interested only in parts with binary variables (named indicators1, indicators2, ... etc.) Every text file contains other numeric columns, but not always the same and not always in the same order - therefore I would rather need a method connecting to file and reading only colums with

I need to calculate a large number of t statistics, and would like to do so via matrix operations. So far I have figured out a way to calculate the mean of each row of the matrix: d <- matrix(runif(100000,1,10), 1000, 10) # some test data s <- rep(1,ncol(d)) # a sum vector to use for matrix multiplication means <- (d%*%s)/ncol(d) This is at least 1 order of magnitude faster than