similar to: performance of nchar

Hi all, I'm using R to find duplicates in a set of 6 files containing Part Number information. Before applying the intersect method to identify the duplicates I need to normalize the P/Ns. Converting the P/N to uppercase if alphanumerical and applying an 18 char long zero padding if numerical. When I apply the pn_formatting function (see code below) to "Part Number" column of the

I have noticed a significant performance degradation using merge in 2.9.1 relative to 2.8.1. Here is what I observed: N <- 100000 X <- data.frame(group=rep(12:1, each=N), mon=rep(rev(month.abb), each=N)) X$mon <- as.character(X$mon) Y <- data.frame(mon=month.abb, letter=letters[1:12]) Y$mon <- as.character(Y$mon) Z <- cbind(Y, group=1:12) system.time(Out

this function is supposed to canonicalize the language: --8<---------------cut here---------------start------------->8--- canonicalize.language <- function (s) { s <- tolower(s) long <- nchar(s) == 5 s[long] <- sub("^([a-z]{2})[-_][a-z]{2}$","\\1",s[long]) s[nchar(s) != 2 & s != "c"] <- "unknown" s }

In R 2.9.1 Windows: > nchar(factor(paste('sdf',1:10))) [1] 1 1 1 1 1 1 1 1 2 1 so it appears that nchar is counting the number of characters in the numeric representation, just like: > nchar(as.numeric(factor(paste('sdf',1:10)))) [1] 1 1 1 1 1 1 1 1 2 1 but ?nchar says explicitly: x: character vector, or a vector to be coerced to a character vector.

Hi all, I have a puzzling problem related to nchar. In R 3.2.1, the internal nchar gained an extra argument (see https://stat.ethz.ch/pipermail/r-announce/2015/000586.html) I've been testing code using the package copula, and at home I'm still running R 3.2.0 (I know, I know...). When trying the following code, I got an error: > library(copula) > fgmCopula(0.8) Error in

On 05/10/2015 8:25 PM, Matt Dowle wrote: > > On Mon, Oct 5, 2015 at 4:57 PM, Duncan Murdoch <murdoch.duncan at gmail.com > <mailto:murdoch.duncan at gmail.com>> wrote: > > On 05/10/2015 7:24 PM, Matt Dowle wrote: > > Joris Meys <jorismeys <at> gmail.com <http://gmail.com>> writes: > > > >> > >> Hi all,

Malcolm, I tested the code on a clean R 3.2.0 session. Not even in RStudio, just to rule that out. > sessionInfo() R version 3.2.0 (2015-04-16) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 8 x64 (build 9200) locale: [1] LC_COLLATE=English_United Kingdom.1252 [2] LC_CTYPE=English_United Kingdom.1252 [3] LC_MONETARY=English_United Kingdom.1252 [4] LC_NUMERIC=C [5]

Hello, This is about the new "line profiling" feature in R 3.0.0. As I was testing it, I find the results somewhat disappointing so I'd like to get your opinion. I put some poorly written code in a test.R file, here are the contents: double <- function(x) { out <- c() for (i in x) { out <- c(out, 2*i) # line 4 } return(out) } Then this how I source the file

I don't understand why nchar() gives different string lengths for vectors in a list than it does for vectors in a dataframe. Here's a snippet of code: > temp <- list(text=c("thug","jimbob","apple","thug"),numbers=1:4) > nchar(temp$text) [1] 4 6 5 4 > temp <- data.frame(temp) > nchar(temp$text) [1] 1 1 1 1 Could someone explain

Dear Rs: Hi, I am trying to read a big text file (nrows=243440, ncols=144). It seems the computational time of all the read methods (scan,readtable,read.delim) is not linear to the number of rows I want to read in: things became really slow once I tried to read in 100000 lines compare to 10000 lines). If I am reading the profiling result right, I guess scan wouldn't help either. My

I would propose to add " See also: `nchar' for counting the number of character in character vectors. " to the helpfile of length(), because it is rather difficult to find nchar() if one has only search terms as "length", "len", "strlen" in mind. Sincerly Wolfram Fischer

Those of you who track R development closely, will have noticed yesterday's commit of enhanced versions of nchar() and nzchar(). ------------------------------------------------------------------------ r68254 | maechler | 2015-04-23 18:06:37 +0200 (Thu, 23 Apr 2015) | 1 line Changed paths: M doc/NEWS.Rd M src/library/base/R/New-Internal.R M src/library/base/R/zzz.R M

Hello R-sig-debian and (hopefully) Dirk: On Debian wheezy, I have the R packaging that CRAN (you) provide. I run into a little trouble while trying to fiddle with alternative BLAS. I know you and I went around on this last year and I think perhaps I've found something wrong in the framework, or I've just done something wrong. I installed the packages openblas-base and openblas-dev, and

Hello there, I am not quite sure how to interpret the output of Rprof (in the following the output I was staring at). I was poking around the web a little bit for documentation but without much success. I guess if I want to figure out what takes so long in my code the 2nd table $by.total and the total.pct column (pct = percent) is the most helpful. What does it mean that [ or [.data.frame is

Hello, Is this expected ? > nchar( c( "", NA ) ) [1] 0 2 Should not the second one be NA ? Romain -- Romain Francois Professional R Enthusiast +33(0) 6 28 91 30 30 http://romainfrancois.blog.free.fr |- http://bit.ly/98Uf7u : Rcpp 0.8.1 |- http://bit.ly/c6YnCi : graph gallery collage `- http://bit.ly/bZ7ltC : inline 0.3.5

On 05/10/2015 7:24 PM, Matt Dowle wrote: > Joris Meys <jorismeys <at> gmail.com> writes: > >> >> Hi all, >> >> I have a puzzling problem related to nchar. In R 3.2.1, the internal > nchar >> gained an extra argument (see >> https://stat.ethz.ch/pipermail/r-announce/2015/000586.html) >> >> I've been testing code using the

Hi, I'm running some routines with standard matrix operations like solve() and diag(). When I do a profile, the lead item under total time is standardGeneric(). Furthermore, solve() and diag() have much greater total time than self time. ??? I assume there is some time-consuming decision going on in the usual functions; is there any way to avoid that and go straight to the calculaions? Thanks

I write a function to get the frequency and prop of a variable. freq<-function(x,digits=3) {naa<-is.na(x) nas<-sum(naa) if (any(naa)) x<-x[!naa] n<-length(x) ta<-table(x) prop<-prop.table(ta)*100 res<-rbind(ta,prop) rownames(res)<-c("Freq","Prop") cat("Missing value(s) are",nas,".\n") cat("Valid case(s)

Hello, (This is follow up from this thread: http://www.nabble.com/execution-time-of-.packages-td22304833.html but with a different focus) I am often confused by the result of the profiler, when a loop is involved. Consider these two scripts: script1: Rprof( ) x <- numeric( ) for( i in 1:10000){ x <- c( x, rnorm(10) ) } Rprof( NULL ) print( summaryRprof( ) ) script2:

Dear Martin, Does the work on nchar mean that bugs #16090 and #16091 will be resolved [1,2]? Thanks, Mark [1] https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16090 [2] https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16091 On Sat, Apr 25, 2015 at 11:06 PM, James Cloos <cloos at jhcloos.com> wrote: > >>>>> "GC" == G?bor Cs?rdi <csardi.gabor at