search for: llply

...--------------------------------- NEW FEATURES * l*ply, d*ply, a*ply and m*ply all gain a .parallel argument that when TRUE, applies functions in parallel using a parallel backend registered with the foreach package: x <- seq_len(20) wait <- function(i) Sys.sleep(0.1) system.time(llply(x, wait)) # user system elapsed # 0.007 0.005 2.005 library(doMC) registerDoMC(2) system.time(llply(x, wait, .parallel = TRUE)) # user system elapsed # 0.020 0.011 1.038 This work has been generously supported by BD (Becton Dickinson). MINOR CHANGES * a*ply and m*ply...

...--------------------------------- NEW FEATURES * l*ply, d*ply, a*ply and m*ply all gain a .parallel argument that when TRUE, applies functions in parallel using a parallel backend registered with the foreach package: x <- seq_len(20) wait <- function(i) Sys.sleep(0.1) system.time(llply(x, wait)) # user system elapsed # 0.007 0.005 2.005 library(doMC) registerDoMC(2) system.time(llply(x, wait, .parallel = TRUE)) # user system elapsed # 0.020 0.011 1.038 This work has been generously supported by BD (Becton Dickinson). MINOR CHANGES * a*ply and m*ply...

...ry day of the week from the same folder. Let say, on day 1, I have about 100 files in the folder. By using this code, everything works perfectly (maybe there is a more efficient way to do it): filenames <-list.files(path="pathtofile", full.names=TRUE) library(plyr) import.list <- llply(filenames, read.table, header=TRUE, sep="", na.strings="NA", dec=".", strip.white=TRUE) # #MERGE and RESHAPE some of the files have different columns library(reshape) data3 <- merge_recurse(import.list) # At the end of each day I will export the file as a cvs file i...

...(plyr) > data(baseball) > summarise(baseball, + duration = max(year) - min(year), + nteams = length(unique(team))) Error: could not find function "summarise" > ddply(baseball, "id", summarise, + duration = max(year) - min(year), + nteams = length(unique(team))) Error in llply(.data = .data, .fun = .fun, ..., .progress = .progress) : object "summarise" not found -------------------------------------------- -- Professor of Family Medicine Boston University Tel: 617-414-6221, Fax:617-414-3345 emails: chettyvk@gmail.com,vchetty@bu.edu [[alternative HTML vers...

Hi group, I imported 16 data frames using the function "list.files" temp <- list.files(path="...........") myfiles = lapply(temp, read.table,sep = "") Now I have 16 data set imported in R window. I want to combine them by row and tried some thing like (Here I am considering only 20 columns) for(i in 1:16){ data<- cbind(myfiles[[i]][,1:20]) } but it

...e following behaviour, > d <- lapply(1:4, function(i) data.frame(x=rnorm(5), y=rnorm(5))) > str(d) > > lapply(d, "[", i= c(1)) # fine, this extracts the first columns > lapply(d, "[", j= c(1, 3)) # doesn't do nothing ?! > > library(plyr) > > llply(d, "[", j= c(1, 3)) # same Am i misinterpreting the meaning of "j", which I thought was an argument of the method "[.data.frame"? > args(`[.data.frame`) > function (x, i, j, drop = if (missing(i)) TRUE else length(cols) == > 1) > Many thanks, bap...

...e following behaviour, > d <- lapply(1:4, function(i) data.frame(x=rnorm(5), y=rnorm(5))) > str(d) > > lapply(d, "[", i= c(1)) # fine, this extracts the first columns > lapply(d, "[", j= c(1, 3)) # doesn't do nothing ?! > > library(plyr) > > llply(d, "[", j= c(1, 3)) # same Am i misinterpreting the meaning of "j", which I thought was an argument of the method "[.data.frame"? > args(`[.data.frame`) > function (x, i, j, drop = if (missing(i)) TRUE else length(cols) == > 1) > Many thanks, bap...

...onde bNames es la lista de los df que tengo cargados "qBlog001" "qBlog002"..."qBlog150"... algo así es lo que tengo en mente: for (i in bNames) { for (j in c_names) { j<- Corpus(VectorSource(i)) } } Pero no funciona, he probado con lapply, con sapply, con llply de la librería (plyr) y no encuentro la manera de hacerlo.. Cualquier sugerencia sera bienvenida! Muchas gracias por adelantado! -- Oscar Benitez [[alternative HTML version deleted]]

...put to data.frames, matrices and lists * progress bars to keep track of long running operations * built-in error recovery * the choice of passing chunks as rows or as variables plyr functions are named according to the type of object they input (first letter) and output (second letter): * llply = from a list to a list * alply = from an array (or vector, or matrix) to a list * ldply = from a list to a data.frame * d_ply = from a data.frame, ignore output * and so on for llply, laply, ldply, l_ply, alply, aaply, adply, a_ply, dlply, daply, dply, d_ply plyr also provides: * m*ply...

...put to data.frames, matrices and lists * progress bars to keep track of long running operations * built-in error recovery * the choice of passing chunks as rows or as variables plyr functions are named according to the type of object they input (first letter) and output (second letter): * llply = from a list to a list * alply = from an array (or vector, or matrix) to a list * ldply = from a list to a data.frame * d_ply = from a data.frame, ignore output * and so on for llply, laply, ldply, l_ply, alply, aaply, adply, a_ply, dlply, daply, dply, d_ply plyr also provides: * m*ply...

...he process of getting Rmpi running. For now, 32 cores should be (more than) adequate for me. My script is of the sort: |define a bunch of functions load the data call libraries require(doMC) require(plyr) registerDoMC(32) main.function <- function(data){ *thefunction* } results= llply(1:500, function(idx){out<-main.function(data)},.parallel=TRUE) save(results,file="trestles_results")| This runs fine on my own machine (setting it to run only a few times and registering only a couple of cores). But when I run it on the cluster, the output file shows that it ran e...

Hi, I have a list of 100 data frames, each data frame has 50 obs of 377 variables. I would like to replace all the NAs with 0 in all the dataframes. Should I have a for loop for every data frame? Below is an extract of how the data looks like. List of 100 $ :'data.frame': 50 obs. of 377 variables: ..$ ACHRPO: int [1:50] NA NA NA NA NA NA NA NA NA NA ... ..$ ACTEEX: int [1:50] NA

Dear all, I have 9 data frames, and I'm simply trying to sum the values of column 3 (on a row-by-row basis). However, there are a slightly different number of rows in each data frame, so I'm receiving the following error: "Error in Ops.data.frame(mrunoff_207101[3], mrunoff_207102[3]) : ? + only defined for equally-sized data frames". Here is what I'm attempting to do:

Hello, I am using the following script to run an anova for numerous species in a table that I have: SiteSpp <-

Hi all, I have the next problem: I have a matrix with size 8,000,000x18. My personal computer...blocks...so I have cut my original file into 100 different file. I have written a function that should be run on each of this file. So imagine I need to read data from q1 to q100 file data<-read.table("q1.txt",sep="") and each time I read 1 file execute my personal function

...unning Ubuntu 11.04, with R 2.12.1 and ESS+Emacs. For journal formatting requirements, I need to italicize all the greek letters in any plot. This is reasonably straight forward to do and I accomplished this task like so: library(ggplot2) label_parseall <- function(variable, value) { plyr::llply(value, function(x) parse(text = paste(x))) } dat <- data.frame(x = runif(270, 0, 125), z = rep(LETTERS[1:3], each = 3), yy = 1:9, stringsAsFactors = TRUE) #unicode italicized delta dat$gltr = factor(c("italic(\u03b4)^14*N","italic(\u03b4)^15*N","italic(\u03b4)^13*C&quo...

Folks, I am trying to get a loop to run which increments the object name as part of the loop. Here "fit1" "fit2" "fit3" and "fit4" are linear regression models that I have created. > for (ii in c(1:4)){ + SSE[ii]=rbind(anova(fit[ii])$"Sum Sq") + dfe[ii]=rbind(summary(fit[ii])$df) + } Error in anova(fit[ii]) : object 'fit' not found

...2"..."qBlog150"... >> >> algo así es lo que tengo en mente: >> >> for (i in bNames) { >> for (j in c_names) { >> j<- Corpus(VectorSource(i)) >> } >> } >> >> Pero no funciona, he probado con lapply, con sapply, con llply de la >> librería (plyr) y no encuentro la manera de hacerlo.. >> Cualquier sugerencia sera bienvenida! >> Muchas gracias por adelantado! >> >> >> -- >> Oscar Benitez >> >> [[alternative HTML version deleted]] >> >> _________...

I have a list of dataframes i.e. each list element is a dataframe with three columns and differing number of rows. The third column takes on only two values. I wish to split the list into two sublists based on the value of the third column of the list element.  Second issue with lists as well. I would like to reduce each of the sublist based on the range of the second column, i.e. if the range of

...lo que tengo en mente: >>>> >>>> for (i in bNames) { >>>> for (j in c_names) { >>>> j<- Corpus(VectorSource(i)) >>>> } >>>> } >>>> >>>> Pero no funciona, he probado con lapply, con sapply, con llply de la >>>> librería (plyr) y no encuentro la manera de hacerlo.. >>>> Cualquier sugerencia sera bienvenida! >>>> Muchas gracias por adelantado! >>>> >>>> >>>> -- >>>> Oscar Benitez >>>> >>>>...