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For example, strings <- c("aaaa", "bbbb","ccba"). How to get "aaaa", "bbbb" that do not contain "ba" ? _________________________________________________________________ [[alternative HTML version deleted]]

For example, c("dog.is.an.animal", "cat.is.an.animal", "rat.is.an.animal"). How can I identify the common prefix is ".is.an.animal" and delete it to give c("dog", "cat", "rat") ? Thanks _________________________________________________________________ [[alternative HTML version deleted]]

I am generating a report containing several R scripts in the appendix. Is there any way to "beautify" the R source codes in microsoft word, similar to what we see in tinn-R ? Thanks _________________________________________________________________ [[alternative HTML version deleted]]

Any better solution than this ? sum(strsplit("TCGGGGGACAATCGGTAACCCGTCT", "")[[1]] == "G") _________________________________________________________________ [[alternative HTML version deleted]]

I tried aggregate, apply etc, but can't get the right result. For example, m <- cbind(c(LETTERS[1:5]), c("aa", "bb", "cc", "aa", "cc")) [,1] [,2][1,] "A" "aa"[2,] "B" "bb"[3,] "C" "cc"[4,] "D" "aa"[5,] "E" "cc" how to obtain

Given a dataframe m > m X Y V3 V4 1 1 A 0.5 1.2 2 1 B 0.2 1.4 3 2 A 0.1 0.9 How do I convert m to this with V4 as the cell values ? A B 1 1.2 1.4 2 0.9 NA

Hi, I have developed some scripts that basically ask for input tab-limited format files, do some processing, and output several pictures or csv. Now I need to have some gui to wrap on top of the scripts, so that end-users can select their input files, adjust some parameters for processing, and select output folder or filenames. Please advice me if there is any tools or project suitable for

The aggregate function does "almost" all that I need to summarize a datasets, except that I can't specify exclusion of NAs without a little bit of hassle. > set.seed(143) > m <- data.frame(A=sample(LETTERS[1:5], 20, T), B=sample(LETTERS[1:10], 20, T), C=sample(c(NA, 1:4), 20, T), D=sample(c(NA,1:4), 20, T)) > m A B C D 1 E I 1 NA 2 A C NA NA 3 D I NA 3 4 C I

How to optimize the for-loop to be reasonably fast for sample.size=100000000 ? You may want to change sample.size=1000 to have an idea what I am achieving. set.seed(143) A <- matrix(sample(0:1, sample.size, TRUE), ncol=10, dimnames=list(NULL, LETTERS[1:10])) B <- list() for(i in 1:10) { B[[i]] <- apply(combn(LETTERS[1:10], i), 2, function(x) { sum(apply(data.frame(A[,x]), 1,

I have a folder full of pngs and jpgs, and would like to consolidate them into a pdf with appropriate title and labels. Can this be done via R ? _________________________________________________________________ Easily publish your photos to your Spaces with Photo Gallery. [[alternative HTML version deleted]]

Hi, I am casting a dataframe from long to wide format. The same codes that works for a smaller dataframe would take a long time (more than two hours and still running) for a longer dataframe of 2495227 rows and ten different predictors. How to make it more efficient ? wer <- data.frame(Name=c(1:5, 4:5), Type=c(letters[1:5], letters[4:5]), Predictor=c("A", "A",

My two matrices are roughly the sizes of m1 and m2. I tried using two apply and cor.test to compute the correlation p.values. More than an hour, and the codes are still running. Please help to make it more efficient. m1 <- matrix(rnorm(100000), ncol=100) m2 <- matrix(rnorm(10000000), ncol=100) cor.pvalues <- apply(m1, 1, function(x) { apply(m2, 1, function(y) { cor.test(x,y)$p.value

Hi, How do I collapse (average in the simplest case) the values of those duplicated ids (i.e., 2, 5, 6, 9) to give a table of unique ids ? t <- cbind(id=c(1:10, 2,5,6,9), value=rnorm(14)) _________________________________________________________________ [[alternative HTML version deleted]]

I have successfully installed ADaCGH package, and trying the example in SegmentPlotWrite did produce alot of pngs and html. I tried again the same example this morning (after a long night of installation), ADaCGH crashes at mpiInit() showing the error: Loading required package: Rmpi ELAN_EXCEPTION @ --: 6 (Initialisation error) elan_init: Can't get capability from environment Aborted I

m1 <- matrix(rnorm(40), ncol=4) m2 <- matrix(rnorm(40), ncol=4) I would like to subtract first column of m1 from all columns of m2, subtract 2nd of m1 from all columns of m2, and so on. Obviously, I am not using the appropriate function outer(m1, m1, "-"), since the first column isn't all 0s. _________________________________________________________________

Given a vector of numeric of length n, I need to find segments that are >= 0.2, compute the average of individual segments, and replace the original values in each segment by their corresponding averages. For example, there are three segments that are >= 0.2, the average of 1st segment is 0.3, 2nd is 0.5, and the 3rd is 0.5333333 >

Instead of prepend or append new columns to a matrix, how to insert them to a matrix ? For example, I would like to insert 3 new columns after the 5th column of matrix m. _________________________________________________________________ [[elided Hotmail spam]] [[alternative HTML version deleted]]

unique(c(1:10,1)) gives 1:10 (i.e. unique values), is there any method to get only 2:10 (i.e. values that are unique) ? _________________________________________________________________ Easily edit your photos like a pro with Photo Gallery. [[alternative HTML version deleted]]

I need to capture matching words in a string, any ideas ? I tried using gregexpr, but it was no help. In this example, I need to capture ID23423424 and ID324234325 > s <- "sID23423424 apple pID324234325 orange"> gregexpr("ID[0-9]+", s)[[1]][1] 2 20attr(,"match.length")[1] 10 11 _________________________________________________________________

With smaller tab-limited files, I could load them using read.table and the likes. Now I have a gigantic 10^8 rows and 1^3 columns tab-limited file for processsing, please throw some ideas how to handle it. Thanks _________________________________________________________________ Publish your photos to your Space easily with Photo Gallery. [[alternative HTML version deleted]]