similar to: Reshape package: new version 0.7

Hi everyone, This is a short announcement for the users of ggplot and reshape. I have just released new versions of each that fix bugs when used with R 2.5.0: * reshape was having problems with missing combinations of variables * errorbars in ggplot weren't working. I've you've been having problems with either of these, please upgrade. About ggplot ===================== An

Hi everyone, This is a short announcement for the users of ggplot and reshape. I have just released new versions of each that fix bugs when used with R 2.5.0: * reshape was having problems with missing combinations of variables * errorbars in ggplot weren't working. I've you've been having problems with either of these, please upgrade. About ggplot ===================== An

Reshape version 0.7.1 ===================== Reshape is an R package for flexibly restructuring and aggregating data. It's inspired by Excel's pivot tables, and it (hopefully) makes it very easy to get your data into the shape that you want. You can find out more at http://had.co.nz/reshape What's new in this version? * A 25 page introductory vignette, also available at

Reshape version 0.7.1 ===================== Reshape is an R package for flexibly restructuring and aggregating data. It's inspired by Excel's pivot tables, and it (hopefully) makes it very easy to get your data into the shape that you want. You can find out more at http://had.co.nz/reshape What's new in this version? * A 25 page introductory vignette, also available at

Reshape version 0.8 http://had.co.nz/reshape Reshape is an R package for flexibly restructuring and aggregating data. It's inspired by Excel's pivot tables, and it (hopefully) makes it very easy to get your data into the shape that you want. You can find out more at http://had.co.nz/reshape This version brings a few minor changes to make the output more attractive and less surprising.

Reshape version 0.8 http://had.co.nz/reshape Reshape is an R package for flexibly restructuring and aggregating data. It's inspired by Excel's pivot tables, and it (hopefully) makes it very easy to get your data into the shape that you want. You can find out more at http://had.co.nz/reshape This version brings a few minor changes to make the output more attractive and less surprising.

Reshape2 is a reboot of the reshape package. It's been over five years since the first release of the package, and in that time I've learned a tremendous amount about R programming, and how to work with data in R. Reshape2 uses that knowledge to make a new package for reshaping data that is much more focussed and much much faster. This version improves speed at the cost of functionality,

Reshape2 is a reboot of the reshape package. It's been over five years since the first release of the package, and in that time I've learned a tremendous amount about R programming, and how to work with data in R. Reshape2 uses that knowledge to make a new package for reshaping data that is much more focussed and much much faster. This version improves speed at the cost of functionality,

Reshape version 0.6 =================== Reshape is an R package for flexibly restructuring and aggregating data. It's inspired by Excel's pivot tables, and it (hopefully) makes it very easy to get your data into the shape that you want. You can find out more at http://had.co.nz/reshape What's new in this version? * a new function, stamp, which is kind of a cross between by and

Dear all, I have been working on an idempotent version of apply, such that applying a function f(x) = x (ie. force) returns the same array (or a permutation of it depending on the order of the margins): a <- array(1:27, c(2,3,4)) all.equal(a, iapply(a, 1, force)) all.equal(a, iapply(a, 1:2, force)) all.equal(a, iapply(a, 1:3, force)) all.equal(aperm(a, c(2,1,3)), iapply(a, 2, force))

ID: T8dfe471e360ac80264c6c Dear, I'm using R 2.8.1 with the package reshape version 0.8.2 . It seems that the combine_factor function has problems with combining levels to an empty level: #EXAMPLE WORKING test<-sample(c(1:10),1000,replace=T) testf<-factor(test, c(1:10), LETTERS[1:10]) table(testf,exclude=NULL) testc<-combine_factor(testf, c(1,1,1,1,1,2,2,2,2,2))

Reshape2 is a reboot of the reshape package. It's been over five years since the first release of the package, and in that time I've learned a tremendous amount about R programming, and how to work with data in R. Reshape2 uses that knowledge to make a new package for reshaping data that is much more focussed and much much faster. This version improves speed at the cost of functionality,

Reshape2 is a reboot of the reshape package. It's been over five years since the first release of the package, and in that time I've learned a tremendous amount about R programming, and how to work with data in R. Reshape2 uses that knowledge to make a new package for reshaping data that is much more focussed and much much faster. This version improves speed at the cost of functionality,

Reshape version 0.5 =================== Reshape is an R package for flexibly restructuring and aggregating data. It's very much pivot table inspired, and it (hopefully) makes it very easy to view your data the way you want. You can find out more at http://had.co.nz/reshape The big news in this version of reshape is that I've renamed all the functions so they no longer conflict with any

Reshape version 0.5 =================== Reshape is an R package for flexibly restructuring and aggregating data. It's very much pivot table inspired, and it (hopefully) makes it very easy to view your data the way you want. You can find out more at http://had.co.nz/reshape The big news in this version of reshape is that I've renamed all the functions so they no longer conflict with any

Hello I am reshaping a data.frame bids --> reshaped as shown below. I thought this should be possible with a single invocation of reshape, but the only way I came up with is reshaping subsets for each keyword and then joining them together. Does anyone have an idea how to solve this in a more elegant way? Efficiency is a concern as the datasets are very large. Is there a way to specify

I know there are a lot of reshape questions on the mailing list, but I haven't been able to find an answer to this particular issue. I am trying to get a datafame structured like this: > sub <- rep(1:5) > ta1 <- rep(1,5) > ta2 <- rep(2,5) > tb1<- rep(3,5) > tb2 <- rep(4,5) > DF <- data.frame(sub,ta1,ta2,tb1,tb2) > DF sub ta1 ta2 tb1 tb2 1

Hi R-core, I have been performance testing R packages for wide-to-tall data reshaping and for the most part I see they differ by constant factors. However in one test, which involves converting into multiple output columns, I see that stats::reshape is in fact quadratic in the number of input columns. For example take the iris data, which has 4 input columns to reshape, and the desired output

Hello R users and developers, I have a general question about reshaping a wide data frame using the "reshape" command. I have a data frame consisting of 108 columns that I would like to convert to a long table and remove the metadata (embedded in the column names of the wide table) to new metadata columns in the long format. #example data frame. NOTE column names contain metadata::

Hello everyone, I'm having a problem performing reshape() on a large data frame. The operation is fairly trivial but it makes R run out of memory. The data frame has the following structure: ID DATE1 DATE2 VALTYPE VALUE 'abcd1233' 2009-11-12 2009-12-23 'TYPE1' 123.45 ... VALTYPE is a string and is a factor with