similar to: faster row by row data frame processing

Dear list, A while ago I found in the web a function (sadly I can't credit the author as I don't remember where I picked it up from) whose output is a dataframe that lists for every object in the global environment its class, mode, dim & length (where applicable). It is meant to be an upgrade to the ls () function with a far more informative and detailed output and it quickly became

Hi All, My group is looking for any suggestions on what to purchase to achieve the most powerful number crunching system that $50k can buy. The main application that will be used is R so input on what hardware benefits R most will be appreciated. The requirements are that it be a single standalone server (i.e. not a cluster solution), and it that must be able to run unix/linux. If

Folks, I often build up R objects starting from NULL and then repeatedly using rbind() or cbind(). This yields code like: a <- NULL for () { onerow <- craft one more row a <- rbind(a, onerow) } This works because rbind() and cbind() are forgiving when presented with a NULL arg: they act like nothing happened, and you get all.equal(x,rbind(NULL,x)) or all.equal(x,cbind(NULL,x)).

Dear useRs, I have a function that creates several global objects with assign("obj",obj,.GlobalEnv), and which I need to run iteratively in another function. The code is similar to f <- function(...) { assign("obj",obj,.GlobalEnv) } fct <- function(...) { for (i in 1:1000) { ... f(...) ...obj... rm(obj) #code fails without this line } } I don't understand

Dear useRs, I timed the same code (simulation with for loops) on the same box (dual Xeon EM64T, 1.5 Gb RAM) under 3 OSs and was surprised by the results: Windows XP Pro (32-bit): Time difference of 5.966667 mins 64-bit GNU/Linux (Fedora Core 4): Time difference of 6.966667 mins 32-bit GNU/Linux (FC4): Time difference of 9.2 mins (R 2.1.0 binaries downloaded from CRAN) I searched the

Classification: UNCLASSIFIED Caveats: NONE Thanks for your quick response. The program you mentioned below available from R is based on number of runs (up or down) not based on a longest length of runs of same events. To be more specific, for example, from a series, HHTHTTTTHHH, the number of runs are 5, and the longest length of runs of the same events is 4. I'll check for the website you

Dear R users, I have a column with dates (character) in a data frame: 12-Jan-01 11-Jan-01 10-Jan-01 9-Jan-01 8-Jan-01 5-Jan-01 and I need to convert them to (Julian) dates so that I can sort the whole data frame by date. I thought it would be very simple, but after checking the documentation and the list I still don't have something that works. 1. as.Date returns the error below. What am I

Dear useRs, I have a data frame and I want to plot all rows. Each row is represented as a line that links the values in each column. The plot looks like this: dfr <- data.frame(A=sample(1:50,10),B=sample(1:50,10), C=sample(1:50,10),D=sample(1:50,10)) xa <- 10*1:4 plot(c(10,40),c(0,50)) for (i in 1:nrow(dfr)) { lines(xa,dfr[i,],pch=20,type="o") } Things get more complicated

I agree with Martin "R Graph Gallery" has a lot of neat stuff. I also think there should be a on CRAN website a list of "R websites". And in a perfect world one of the search engines scope would get extended to search them all. Jarek ====================================================\==== Jarek Tuszynski, PhD. o / \ Science Applications

Dear R users, I need to rename the columns of a series of data frames. The names of the data frames and those of the columns need to be pulled from some vectors. I tried a couple of things but only got errors. What am I missing? #---create data frame dframes <- c("a","b","c") assign(dframes[2],data.frame(11:20,21:30)) #---rename the columns cols <-

Hello, Please forget me if I am asking something that is well documented. I have read documentation but there are points that are not clear for me. I am not expert in R nor Databases, but if someone direct me to a tutorial, I will appreciate it.. 1. In my understanding, I can install and use RMySQL withouth having to install MySQL in my PC, to have access to and to create new tables . Is this

Dear R community, I tried to optimized my R code by using Rprof. In my R code I'm using MySQL database connections intensively. After a bunch of queries R fails with the following error message: Error in .Call("RS_MySQL_newConnection", drvId, con.params, groups, PACKAGE = .MySQLPkgName) : RS-DBI driver: (could not connect mylogin@mydatabase on dbname "myDB"

Dear useRs, Given this code I end up with a list of class "by": a <- sample(1:5,200,replace=TRUE) b <- sample(c("v1","v2","v3"),200,replace=TRUE) c <- sample(c(11,22,33),200,replace=TRUE) data <- runif(200) grouped <- by(data,list(a,b,c),function(x) {c(min=min(x),max=max(x), median=round(median(x),digits=2),mean=round(mean(x),digits=2))})

Dear useRs, How come the first attempt to sort a POSIXt vector fails (Error: non-atomic type in greater), while the second succeeds? (Code inserted below.) The documentation says that POSIXt is used to allow operations such as subtraction, so I'd expect sorting to work. Is this perhaps an OS issue? (I run R 2.0.1 on Win xp.) Thank you, b. #------------code test <- c("2005-02-08

I noticed that btrfs fi defrag -c<method> can''t be used to compress files unless they are fragmented. This patch corrects the problem, by informing should_defrag_range if compression is enabled, and skipping tests for extent and adjacent extents if it is. Andrew Mahone (1): btrfs: ignore unfragmented file checks in defrag when compression enabled fs/btrfs/ioctl.c | 10

Hi: I have encountered problems with imodwt and universal.thresh.modwt and cannot find any reference in R Search. Hope someone can give me some ideas: Starting with modwt.la8 <- modwt(xdata, "la8", n.level=6) <-- this seems to work fine (1) ydata <- imodwt(modwt.la8) will always give ydata as numeric(0) (no values) instead of being a time series data with

Dear all, I get a strange error when I find polychoric correlations with the ML method, which I have been able to reproduce using randomly-generated data. What is wrong? I realize that the data that I generated randomly is a bit strange, but it is the only way that I duplicate the error message. > n<-100 > test.x<-rnorm(n, mean=0, sd=1) > test.c<-test.x + rnorm(n, mean=0,

On Fri, 07 Jan 2005 17:05:59 +0000 David Woodhouse <dwmw2@infradead.org> wrote: > On Sat, 2004-12-18 at 08:50 +0100, Andi Kleen wrote: > > It's not really an oops, just a warning that stack space got quiet > > tight. > > > > The problem seems to be that the br netfilter code is nesting far too > > deeply and recursing several times. Looks like a design

From: Leitch, Matthew C. Sent: Monday, January 24, 2011 6:53 PM To: 'info at network-theory.co.uk' Subject: question about the pt() calculation Hello Thank you for your time. I am a graduate student at the University of Texas Medical Branch, and I was wondering if you could help me with a R program I am writing. I have some data that is stored a file that has 1733 rows and 4 columns.

Dear useRs, I'm wondering why the for() loop below runs slower as it progresses. On a Win XP box, the iterations at the beginning run much faster than those at the end: 1%, iteration 2000, 10:10:16 2%, iteration 4000, 10:10:17 3%, iteration 6000, 10:10:17 98%, iteration 196000, 10:24:04 99%, iteration 198000, 10:24:24 100%, iteration 200000, 10:24:38 Is there something that can be done about