similar to: can't find and install reshape2??

Hi everyone, I’m working with some very big datasets (each dataset has 11 million rows and 2 columns). My first step is to merge all my individual data sets together (I have about 20) I’m using the following command from sqldf data1 <- sqldf("select A.*, B.* from A inner join B using(ID)") But it’s taking A VERY VERY LONG TIME to merge just 2 of the datasets

Hi everyone, I’ve recently added a private library as a way to manage my R libraries. And I did this by simply copying my old library to a new folder and then linking this to R by setting my R_LIBS environmental variable in .Renviron. However I have run into a problem. When I update my packages it is not updating those that are current in the base R library. This means I can’t load

Hi everyone, I’m looking for a clever bit of code to replace NA’s with a specific score depending on an indicator variable. I can see how to do it using lots of if statements but I’m sure there most be a neater, better way of doing it. Any ideas at all will be much appreciated, I’m dreading coding up all those if statements!!!!! My problem is as follows: I have a data set with

Afternoon everyone, I''ve spent the last week or so looking at all the experimental design packages I can find in R. AlgDesign, design.conf and BHH2 being the best one I could find. Unfortunately none of these do a particularly good job for complex designs, in particular for conjoint or discrete choice. (or perhaps they do, and I can''t make them work correctly)

Hi, I have read several threads about memory issues in R and I can't seem to find a solution to my problem. I am running a sort of LASSO regression on several subsets of a big dataset. For some subsets it works well, and for some bigger subsets it does not work, with errors of type "cannot allocate vector of size 1.6Gb". The error occurs at this line of the code: example <-

(Sorry if this is a repost, I got a bounce reply from the r-help server) Hi, I’m using the biglm() function to create some linear models for a very large data set than lm() can’t fit due to memory issues (the problem is with the number of interactions, I can fit the main effects model) I need to determine if the 2-way interactions are necessary or not. Ideally I’d like to use anova() to

Dear R users, In order to install reshape2 package, I gave the following command: install.packages("reshape2",dep=TRUE) However, it is not getting installed. The message that I am getting is: Warning: dependencies ‘plyr’, ‘stringr’, ‘testthat’ are not available trying URL ' http://ftp.ctex.org/mirrors/CRAN/src/contrib/reshape2_1.2.2.tar.gz' Content type

Hi, I have a list made up of character strings with each item a different length (each item is between 1and 6 strings long). Is there a way to convert a "ragged" list to a matrix such that each item is its own row? Here is a simple example: a=list(); a[[1]] = c("a", "b", "c"); a[[2]] = c("d", "e"); a[[3]] = c("f",

I seem to be running into the same problem reported in https://stat.ethz.ch/pipermail/r-help/2010-November/258265.html I cannot seem to transform a dataset from long to wide using reshape2. Clearly I am missing something very simple but a look at the manual and the reshape paper in JSS does not suggest anything. Any advice would be welcome ===========================load

> library(reshape2) > x = melt(airquality, id=c('month', 'day')) With reshape I can cast with multiple functions: > library(reshape) > cast(x, month+variable~., c(mean,sd)) month variable mean sd 1 5 ozone 23.615385 22.224449 2 5 solar.r 181.296296 115.075499 3 5 wind 11.622581 3.531450 4 5 temp 65.548387

This does not use reshape/reshape2, but it is pretty straightforward. Assuming X is your example data: > Y <- split(X[, 2], X[, 1]) > vals <- sapply(Y, length) > pad <- max(vals) - vals > Y2 <- lapply(seq_along(Y), function(x) c(Y[[x]], rep(NA, pad[x]))) > names(Y2) <- names(Y) > X2 <- do.call(cbind, Y2) > X2[, 1:6] 1957 1958 1959

Hi, I'd like to get mean values for the margins of my casted data.frame. For the casting I am using dcast() from reshape2. However, when I set the margins parameter (margins=c("grand\_row")) I get following error concerning an unrecognized escape character '\_'. So what is the correct command to get the outermost margins only in reshape2? /johannes [[alternative HTML

Hi! I updated to reshape2 yesterday and tried to make it work. Unfortunately, it mainly throws error messages at me (good thing it's reshape2 1.0 and not reshape 2.0). The most recent is: Error in match.fun(FUN) : object 'id' not found When I manually create an object 'id', it says: Error in get(as.character(FUN), mode = "function", envir = envir) : object

Hi again all, Several replied ASAP that I also needed reshape loaded and not just reshape2. Hmmm tried that and I had some output but not the correct format. What I need is to run simulations of time overlap between species as per the simulation program data input constraints: The basis for the simulations is a species by _time-use matrix in which species are arranged in rows, and time

Running 2.15.0 on Slackware-13.1 with all packages in /usr/lib/R/library. Package reshape2 is in the library but there are no vignettes seen by R. If this is the result of something I did incorrectly, please point out how to install the vignettes with the package. I can get help for melt and cast but no reference on how to access the vignettes. Pointer appreciated, Rich

The reason it doesn't work easily with reshape/reshape2 is that the order of the rows is not determined. Your answer could be 1957 1958 ... 1985 1986 0.8625000 0.7500000 ... 0.7307692 0.23750000 0.0733945 0.6435644 ... NA 0.05769231 0.5096154 NA ... NA 0.65137615 or 1957 1958 ... 1985 1986 0.0733945 0.6435644 ... NA

Hi again all, As the original code lines I had dated back to 2007 that may have predated reshape2? In any case the use of *dcast *rather than /*cast*/ solved the issue. Then with 3 steps: Stop read Think I saw I just needed to change the line input.cast <- cast(input.melt, Species ~ *Date*, fun.aggregate = sum) to input.cast <- cast(input.melt, Species ~ *Time*, fun.aggregate = sum)

I get the following message when using the reshape2 package line > tDat.m<- melt(Dataset) Using Item, Subject as id variables > tDatCast<- acast(tDat.m,Subject~Item) Aggregation function missing: defaulting to length Note Problem Statement- convert dataframe Subject Item Score 1 Subject 1 Item 1 1 2 Subject 1 Item 2 0 3 Subject 1 Item 3 1 4 Subject 2 Item 1 1 5

Hi Tom, Or perhaps: #assume the data frame is named "tadf" library(prettyR) stretch_df(tadf,1,2) Jim On Thu, Jul 6, 2017 at 6:50 AM, Ista Zahn <istazahn at gmail.com> wrote: > The reason it doesn't work easily with reshape/reshape2 is that the > order of the rows is not determined. Your answer could be > > 1957 1958 ... 1985 1986 >

I've successfully reformatted data frames from long to wide with reshape2, but this time I'm getting errors that I want to understand and resolve. Here's the data frame structure and the results of the melt() and dcast() functions: str(waterchem) 'data.frame': 128412 obs. of 8 variables: $ site : Factor w/ 64 levels "D-1","D-2","D-3",..: 1 1