similar to: data.table vs plyr reg output

Hi, I have been trying to use the new .parallel argument with the most recent version of plyr [1] to speed up some tasks. I can run the example in the NEWS file [1], and it seems to be working correctly. However, R will only use a single core when I try to apply this same approach with ddply(). 1. http://cran.r-project.org/web/packages/plyr/NEWS Watching my CPUs I see that in both cases

Hello everyone, I have got the same problem, with the same error message. Using R 2.14.1, plyr 1.7.1, R.Studio 0.94.110, Windows XP The plyr mailing list does not provide any help until now. >require(plyr) >c(sample(c(1:100), 50, replace=TRUE))->V1 >c(rep( 1:5, 10))->f1 #variable to group V1 >data.frame(cbind(V1, f1))->DF >str(DF) >ddply(DF$V1, DF$f1,

Hello everyone, I was asked to repost this again, sorry for any inconvenience. I'm looking replacement for ddply function from plyr package. Function allows to apply function by category stored in any column/columns. Regular loops or lapplys slow down greatly because my unique combination count exceeds 9000. Is there any available solution which allow me to apply function by category?

If I have data: dat<-data.frame(a=rnorm(20),b=rnorm(20),c=rnorm(20),d=rnorm(20),site=rep(letters[5:8],each=5)) And want to plot like this: ctr<-1 for(i in c('a','b','c','d')){ png(file=paste('/tmp/plot_number_',ctr,'.png',sep=''),height=8.5, width=11,units='in',pointsize=9,res=300) print(ggplot(dat[,names(dat) %in%

Issue with PLYR. Now using R 2.14 and this data and plyr command line worked with 2.13 I am also loading the same saved data that worked previously, but now some issue. > library(plyr) > UNESCO <- dget('C:/Carbon-GJ/BZE_ecosys.robj') > df2 <- ddply(df, "UNESCO", summarise, total_ha = sum(Ha)) *Error in if (empty(.data)) return(.data) : missing value where

Hi all, In short: I'm running ddply on an admittedly (somehow) large data.frame (not that large). It runs fine until it finishes and gets to the "collating" part where all subsets of my data.frame have been summarized and they are being reassembled into the final summary data.frame (sorry, don't know the correct plyr terminology). During collation, my R workspace RAM usage goes

Hello, This is my first time trying to use plyr, and I'm getting nowhere. I have teacher ratings data (1:4), on 10 components, by external observers and internal observers, in schools in areas. I want to calculate the percentage of each rating given on each component, by each type of observer, within each school, within each area. The data look like this: unit area ext.obs rating comp 11

plyr is a set of tools for a common set of problems: you need to break down a big data structure into manageable pieces, operate on each piece and then put all the pieces back together. For example, you might want to: * fit the same model to subsets of a data frame * quickly calculate summary statistics for each group * perform group-wise transformations like scaling or standardising *

plyr is a set of tools for a common set of problems: you need to break down a big data structure into manageable pieces, operate on each piece and then put all the pieces back together. For example, you might want to: * fit the same model to subsets of a data frame * quickly calculate summary statistics for each group * perform group-wise transformations like scaling or standardising *

# plyr plyr is a set of tools for a common set of problems: you need to __split__ up a big data structure into homogeneous pieces, __apply__ a function to each piece and then __combine__ all the results back together. For example, you might want to: * fit the same model each patient subsets of a data frame * quickly calculate summary statistics for each group * perform group-wise

# plyr plyr is a set of tools for a common set of problems: you need to __split__ up a big data structure into homogeneous pieces, __apply__ a function to each piece and then __combine__ all the results back together. For example, you might want to: * fit the same model each patient subsets of a data frame * quickly calculate summary statistics for each group * perform group-wise

Hi,I am using the amazing package 'plyr". I have one problem. I would appreciate help to fix the following error: Thanks. ______________________________ > library(plyr) > data(baseball) > summarise(baseball, + duration = max(year) - min(year), + nteams = length(unique(team))) Error: could not find function "summarise" > ddply(baseball, "id", summarise, +

# plyr plyr is a set of tools for a common set of problems: you need to __split__ up a big data structure into homogeneous pieces, __apply__ a function to each piece and then __combine__ all the results back together. For example, you might want to: * fit the same model each patient subsets of a data frame * quickly calculate summary statistics for each group * perform group-wise

# plyr plyr is a set of tools for a common set of problems: you need to __split__ up a big data structure into homogeneous pieces, __apply__ a function to each piece and then __combine__ all the results back together. For example, you might want to: * fit the same model each patient subsets of a data frame * quickly calculate summary statistics for each group * perform group-wise

Dear R forum, Please refer to my query regarding "Error with function". I forgot to mention that I am using "plyr" library. Sorry for inconvenience. Regards Katherine --- On Tue, 23/4/13, Katherine Gobin <katherine_gobin@yahoo.com> wrote: From: Katherine Gobin <katherine_gobin@yahoo.com> Subject: [R] Error with function To: r-help@r-project.org Date:

Hi dear three helpers, Thanks a lot! Your solutions worked great. Again I learned a lot. Tagmarie Am 25.10.2012 18:36, schrieb Felipe Carrillo: > Another option using plyr, > library(plyr) > myframe <- data.frame (ID=c("Ernie", "Ernie", "Ernie", "Bert", "Bert", > "Bert"), Timestamp=c("24.09.2012 09:00",

Hello, Apologies for a similar earlier post. I didn't include enough details in that one. I am having a little trouble subsetting some data based on a grouping variable. I am using an instrument that does depth profiles of a water column. The instrument records on the way down as well as the way up. So thanks to an off-list reply I can subset the data so that all data collected at the

Hi Together, I have a problem with the plyr package - more precisely with the ddply function - and would be very grateful for any help. I hope the example here is precise enough for someone to identify the problem. Basically, in this step I want to identify observations that are identical in terms of certain identifiers (ID1, ID2, ID3) and just want to save those observations (in this step,

Dear all, I have a question regarding the possibility of parallel computation in plyr version 1.7. The help files of the following functions mention the argument '.parallel': ddply, aaply, llply, daply, adply, dlply, alply, ldply, laply However, the help files of the following functions do not mention this argument: ?d_ply, ?aply, ?lply Is it because parallel computation is not

Dear all, I'm stuck with a problem using plyr to process a rather large junk of data. What I'm trying to do is applying a moving average to all the subparts of the dataframe (the example data can be found here https://dl.dropboxusercontent.com/u/2414056/testData.Rdata). require(plyr) load("testData.Rdata") applyfilter<-function(x){ return(filter(x,rep(1/5, times=5))) }