similar to: lapply (and friends) with data.frames are slow

Dear R developers, Reviewing my code, I have realized that about 80% of the time in the lapply I need to access the names of the objects inside the loop. In such cases I iterate over indexes or names: lapply(names(x), ... [i]), lapply(seq_along(x), ... x[[i]] ... names(x)[i] ), or for(i in seq_along(x)) ... which is rather inconvenient. How about an argument to lapply which would specify the

Hi, A common idiom in the R sources is to convert objects between LANGSXP and LISTSXP by using SET_TYPEOF. However, this is soon going to be disallowed in packages. From what I can see, there isn't currently a direct way to convert between these two object types using the available API. At the R level, one can convert calls to pairlists with: >

This message is about a curious difference in timing between two ways of computing the same function. One uses expm, so is expected to be a bit slower, but "a bit" turned out to be a factor of >1000. The code is below. We would be grateful if anyone can point out any egregious bad practice in our code, or enlighten us on why one approach is so much slower than the other. The problem

The "Summary" group generics always throw errors for a data.frame with zero rows, for example: > sum(data.frame(x = numeric(0))) #> Error in FUN(X[[i]], ...) : #> only defined on a data frame with all numeric variables Same behaviour for min, max, any, all, ... . I believe this is inconsistent with what these methods do for other empty objects (vectors, matrices), where the

Dear all, I am looking for some procedure to apply 'ifelse' condition on function. I have created an alternative to lapply() function with exactly same set of arguments named lapply1(), however with different internal codes. Therefore I want something like, if (some condition) then call lapply1() otherwise lapply() function. Ofcourse I can create a complete if()... else()... like of

Hi all, The coercion function defined for the ALTREP object will not be called by R when an assignment operation implicitly introduces coercion for a large ALTREP object. For example, If I create a vector of length 10, the ALTREP coercion function seems to work fine. ``` > x <- 1:10 > y <- wrap_altrep(x) > .Internal(inspect(y)) @0x000000001f9271c0 13 INTSXP g0c0 [REF(2)] I am

>>>>> Martin Maechler <maechler at stat.math.ethz.ch> >>>>> on Tue, 8 Dec 2015 15:25:21 +0100 writes: >>>>> John Chambers <jmc at r-project.org> >>>>> on Mon, 7 Dec 2015 16:05:59 -0800 writes: >> We do need an explicit method here, I think. >> The issue is that as() uses methods for the generic

>>>>> John Chambers <jmc at r-project.org> >>>>> on Fri, 11 Dec 2015 10:11:05 -0800 writes: > Somehow, the most obvious fixes are always back-incompatible these days. > The example intrigued me, so I looked into it a bit (should have been doing something else, but ....) > You're right that this is the proverbial

Peter et al, I had the same thought, in particular for any() and all(), which in as much as they should work on data.frames in the first place (which to be perfectly honest i do find quite debatable myself), should certainly work on "logical" data.frames if they are going to work on "numeric" ones. I can volunteer to prepare a patch if Martin (the reporter) did not want to

The old factor() wars...... {{maybe don't just report that factor()s are broken by design..}} If ff is a factor, e.g., ff <- as.factor(rep(1:2,3)) f2 <- ff; levels(f2) <- c("Lo","Hi") 1) we don't allow {in R as in S-plus 3.x} arithmetic on factors, i.e. 1 + ff gives an error, and I think most of us believe this is as desired. {{if one

A newbie here - please forgive me if this is a basic question. We have an in house package built in R 2.2.1 (yes we're a little behind the times at our firm)and would like to rebuild it using R 2.5.1. However, when I try and build the package from source, I keep getting this error: Error in as(slotVal, slotClass, strict = FALSE) : no method or default for coercing "POSIXt"

Hi Gabriel, here is a simple package for reproducing the problem. https://github.com/Jiefei-Wang/testPkg Best, Jiefei On Thu, Oct 8, 2020 at 5:04 AM Gabriel Becker <gabembecker at gmail.com> wrote: > Jiefei, > > Where does the code for your altrep class live? > > Thanks, > ~G > > On Wed, Oct 7, 2020 at 4:25 AM Jiefei Wang <szwjf08 at gmail.com> wrote: >

Using the Matrix package, how can I create a row-oriented sparse Matrix from scratch populated with some data? By default a column-oriented one is created and I'm aware of the note that the package is optimized for column-oriented ones, but I'm only interested in using it for holding my sparse row-oriented data and doing basic subsetting by rows (even using drop=FALSE). Here is what I

>>>>> Tomas Kalibera >>>>> on Tue, 25 Aug 2020 09:29:05 +0200 writes: > On 8/23/20 5:02 PM, Rory Winston wrote: >> Hi >> >> I noticed a small inconsistency when using sum() vs cumsum() >> >> I have a char-based series >> >> > tryjpy$long >> >> [1]

I need to convert a dataframe to a record-structure, to be able to encode it later in JSON. Suppose this is the data: mydata <- data.frame(foo=1:3, bar=c("M","M","F")); I would like to convert this to a unnamed list (json array) of key-value pairs. For example like this: apply(data.frame(foo=1:3, bar=c("M","M","F")),1,as.list)

all/any coerce their arguments to logical (if possible). I've added a warning in R-devel if coercion is from something other than integer. This arose because it is easy to make a slip and write all(X) > 0 rather than all(X > 0): thanks to Bill Dunlap for bringing that to my attention. However, it has been useful in detecting quite a few other things: - indices which had been made

I'm trying to produce a series of powers of a number as follows: |> 0.05^0:5 [1] 1 2 3 4 5 This is not the result I expected. I guess some kind of coercion happened, since, |> class(0.05^0:5) [1] "integer" Could anyone explain me what is happening here? Thanks, -Sergio.

As I tried to say on Dec. 11, there are two levels of "fix": 1. The fix to the complaint in the OP's subject heading is to conform to the default third argument, strict=TRUE: as(1L, "numeric") == 1.0 This generates some incompatibilities, as for classes that extend "numeric". But still leaves class(1.0) "numeric" and typeof(1.0) "double".

We do need an explicit method here, I think. The issue is that as() uses methods for the generic function coerce() but cannot use inheritance in the usual way (if it did, you would be immediately back with no change, since "integer" inherits from "numeric"). Copying in the general method for coercing to "numeric" as an explicit method for "integer" gives

Greetings, Amigos: I have been trying without success to convert a character string, > repeated.measures.columns [1] "3,6,10" into c(3,6,10) for subsequent use. as.numeric(repeated.measures.columns) doesn't work (likely because of the commas) [1] NA Warning message: NAs introduced by coercion I've tried many things including strsplit(repeated.measures.columns, split =