similar to: Speeding up casting a dataframe from long to wide format

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

I forgot the reshape equivalent for converting from wide to long format. Can someone help as my matrix is very big. The followin is just an example. > m <- matrix(1:20, nrow=4, dimnames=list(LETTERS[1:4], letters[1:5])) > m a b c d e A 1 5 9 13 17 B 2 6 10 14 18 C 3 7 11 15 19 D 4 8 12 16 20 > as.data.frame(cbind(rep(rownames(m), ncol(m)), rep(colnames(m), each=nrow(m)),

Simple illustration, > df3 <- data.frame(id=c(3,2,1,4), age=c(40,50,60,50), dose1=c(1,2,1,2), dose2=c(2,1,2,1), dose4=c(3,3,3,3))> df3 id age dose1 dose2 dose41 3 40 1 2 32 2 50 2 1 33 1 60 1 2 34 4 50 2 1 3> melt.data.frame(df3, id.var=1:2, na.rm=T) id age variable value1 3 40 dose1 12 2 50 dose1 23 1

I tried cast and melt in reshape package, but still can't convert this data frame m m [,1] [,2] [1,] "A" "1" [2,] "A" "2" [3,] "B" "3" to this form. m1 [,1] [,2] [1,] "A" "B" [2,] "1" "3" [3,] "2" NA Please help. [[alternative HTML version deleted]]

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]]

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

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 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

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

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

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

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]]

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]]

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,

Hello, I came up with this scenario of the use of batch mode while thinking of back-up schemes to use for myself. However, it could be that the last step needed in this scenario is not supported by rsync! Here's the scenario: At one time, /c/home/wer/work and /e/gold had identical content and were really huge (say, 200 GBytes). After some complex, intricate work, Mr. Wer

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

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]]

Instead of > m <- c(400000000, 50000000000) > paste("A", m, "B", sep="") [1] "A4e+08B" "A5e+10B" I want "A400000000" and "A50000000000"