similar to: Improved Data Aggregation and Summary Statistics in R

Dear Sebastian, Initially I was a bit hesitant to think about yet another way to summarize data, but your illustrations convinced me this is actually a great addition to the toolset currently available in different R packages. Many of us have written custom functions to get the required tables for specific data sets, but this would reduce that effort to simply using the right collap() call. Like

On 26/02/2019 8:25 a.m., Sebastian Martin Krantz wrote: > Dear Developers, > > Having spent time developing and thinking about how data aggregation and > summary statistics can be enhanced in R, I would like to present my > ideas/efforts in the form of two commands: > > The first, which for now I called 'collap', is an upgrade of aggregate that > accommodates and

Thanks Gabriel and Kevin for your inputs, regarding your points Gabriel, I think Python and Julia do allow multiple sub-assignment, but in-line with my earlier suggestion in response to Duncan to make multiple assignment an environment-level operation (like collapse::%=% currently works), this would not be possible in R. Regarding the [a] <- coolest_function() syntax, yeah it would mean do

On 12/03/2023 6:07 a.m., Sebastian Martin Krantz wrote: > Thinking more about this, and seeing Kevins examples at > https://github.com/kevinushey/dotty > <https://github.com/kevinushey/dotty>, I think this is the most R-like > way of doing it, > with an additional benefit as it would allow to introduce the useful > data.table semantics DT[, .(a = b, c, d)] to more

Kevins package is very nice as a proof of concept, no doubt about that, but it is not at the level of performance or convenience that a native R implementation would offer. I would probably not use it to translate matlab routines into R packages placed on CRAN, because it?s an additional dependency, I have a performance burden in every iteration, and utils::globalVariables() is everything but

Dear All, As a maintainer of large, complex packages, I can think of many places in which deconstructing assignment would simplify the code, as well as facilitate readability by breaking up larger functions into helpers, so I would be very glad to see this incorporated somehow. I think the crux of the matter is that while there is a number of ways to implement deconstructing assignment within R,

There are some other considerations too (apologies if these were mentioned above and I missed them). Also below are initial thoughts, so apologies for any mistakes or oversights. For example, if [a, b] <- my2valuefun() works the same as local({ tmp <- my2valuefun() stopifnot(is.list(tmp) && length(tmp) == 2) a <<- tmp[[1]] b <<- tmp[[2]] }) Do we expect [a[1], b[3]]

Yes, this is really a problem with the checks, not with the language. A simpler approach than your alternativeAssignment function would be simply to allow globalVariables() to be limited to a single function as the note in its help page says. This might be tedious to write by hand, but could be automated using methods like "dotify" in dotty. Duncan Murdoch On 12/03/2023 10:36

Dear R Core, working on my dynamic factor modelling package, which requires several subroutines to create and update several system matrices, I come back to the issue of being annoyed by R not supporting multiple assignment out of the box like Matlab, Python and julia. e.g. something like A, C, Q, R = init_matrices(X, Y, Z) would be a great addition to the language. I know there are several

Thanks Duncan and Ivan for the careful thoughts. I'm not sure I can follow all aspects you raised, but to give my limited take on a few: > your proposal violates a very basic property of the language, i.e. that all statements are expressions and have a value. > What's the value of 1 + (A, C = init_matrices()). I'm not sure I see the point here. I evaluated 1 + (d =

I think you are confusing package and function here. Plus some of the R Core packages, that you mention, contain functions that should probably be replaced by functions with better implementation from packages on CRAN. Best regards Morgan On Fri, 11 Oct 2019 15:22 Joris Meys, <jorismeys at gmail.com> wrote: > > > On Fri, Oct 11, 2019 at 3:55 PM Morgan Morgan <morgan.emailbox

On 31/01/2018 6:33 AM, Joris Meys wrote: > 3. given your criticism, I'd like your opinion on where I can improve > the documentation of https://github.com/CenterForStatistics-UGent/pim. > I'm currently busy updating the help files for a next release on CRAN, > so your input is more than welcome. After this invitation I sent some private comments to Joris. I would say his

Dear all, I tried to read in a 3.8Gb RDS file on a computer with 16Gb available memory. To my astonishment, the memory footprint of R rises quickly to over 13Gb and the attempt ends with an error that says "cannot allocate vector of size 5.8Gb". I would expect that 3 times the memory would be enough to read in that file, but apparently I was wrong. I checked the memory.limit() and that

Dear all, to my astonishment data.table cannot be installed on R 3.5 Windows. When checking the package page, the Windows binary is available for download. When checking the server however, I can't seem to find data.table. Also install.packages() says the package is only available in source form and may need compilation. Compiling using Rtools 35 is no problem. Is this merely an issue of

Dear R users, A colleague of mine asked me how to write a script (an executable text file containing R code) in R. After I showed him, he said that after extensive searching of the R archives, he had not found anything like these techniques. He suggested that I share these methods to enable others to leverage R as a better alternative to bash/perl scripts. So in the interest of giving back to

And now I've seen I copied the wrong part of ?is.na > The default method for is.na applied to an atomic vector returns a logical vector of the same length as its argument x, containing TRUE for those elements marked NA or, for numeric or complex vectors, NaN, and FALSE otherwise. Key point being "atomic vector" here. On Sat, Jun 9, 2018 at 1:41 PM, Joris Meys <jorismeys at

Indeed. as_date is from lubridate, but the same holds for as.Date. The output and it's interpretation should be consistent, otherwise it leads to confusion when programming. I understand that the difference exists after asking a question on Stack Overflow: https://stackoverflow.com/q/50766089/914686 This understanding is never mentioned in the documentation - that an Inf date is actually

Dear all, as a follow-up to the question asked on R-package-devel (see link below): Someone sent a package to CRAN with a few problems. There's more things wrong with the submission, but one thing that really caught my eye was the following error: Warning message: running command '"C:/PROGRA~1/R/R-33~1.2/bin/x64/R" CMD BATCH --vanilla "testthat.R"

I don't see the issue here. It would be helpful if people would report their sessionInfo() when reporting whether or not they see this issue. Mine is > sessionInfo() R version 3.4.3 (2017-11-30) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Arch Linux Matrix products: default BLAS/LAPACK: /usr/lib/libopenblas_haswellp-r0.2.20.so locale: [1] LC_CTYPE=en_US.UTF-8

Joris, the point is that 'z' is NOT used as a predictor in the model. Therefore it should not affect predictions. Also, I find it suspicious that the error only occurs when the response variable conitains missings and 'z' is unique (I have tested several other cases to confirm this). -Mark Op vr 16 mrt. 2018 om 13:03 schreef Joris Meys <jorismeys at gmail.com>: >