similar to: Processing 10^8 rows and 1^3 columns

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]]

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

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]]

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]]

Is there a better or more efficent approach than this without the use of t() ? > (m <- matrix(1:40, ncol=4)) [,1] [,2] [,3] [,4] [1,] 1 11 21 31 [2,] 2 12 22 32 [3,] 3 13 23 33 [4,] 4 14 24 34 [5,] 5 15 25 35 [6,] 6 16 26 36 [7,] 7 17 27 37 [8,] 8 18 28 38 [9,] 9 19 29 39[10,] 10 20 30 40 >

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

This is my first post. I am running Mac OS X version 10.6.3. I am running R 2.11.0 GUI 1.33 64 bit. This may or may not be related to sqldf, but I experienced this problem while attempting to use an sqldf query. The same code runs with no problem on my Windows machine. Here is what happens: > r=sqldf("select ... ") Loading required package: tcltk Loading Tcl/Tk interface ... Then

Dear All, When one loads certain packages, some other dependent packages are loaded as well. Is there some way of detaching them automatically when one detaches the first package loaded? For instance, > library(sqldf) Loading required package: RSQLite Loading required package: DBI Loading required package: gsubfn Loading required package: proto but > detach(package:sqldf) > >

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

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]]

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

Dear All, Is sqldf equipped with delete queries? I have tried delete queries but with no success. Thanks in advance, Paul

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

In performing Rcmd check I am getting this output regarding using Argument '' and a NULL package not found and it stops with an error: * using log directory 'C:/Rpkgs/sqldf.Rcheck' * using ARGUMENT ' ' __ignored__ R version 2.5.1 (2007-06-27) * checking for file 'sqldf/DESCRIPTION' ... OK * this is package 'sqldf' version '0.1-0' * checking package

Dear all, I have a repository file (let's call it repo.txt) that contain two columns like this: # tag value AAA 0.2 AAT 0.3 AAC 0.02 AAG 0.02 ATA 0.3 ATT 0.7 Given another query vector > qr <- c("AAC", "ATT") I would like to find the corresponding value for each query above, yielding: 0.02 0.7 However, I want to avoid slurping whole repo.txt

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]]