similar to: 'aggregate' should preserve level ordering of factors (PR#9666)

On Tue, 8 May 2007, prechelt at inf.fu-berlin.de wrote: > Full_Name: Lutz Prechelt > Version: 2.4.1 > OS: Windows XP > Submission from: (NULL) (160.45.111.67) > > > aggregate (from package stats) should preserve the > ordering of levels of factors it works on and also their > 'ordered' attribute if present. > But it does not. In fact it treats all grouping

This is not a bug, nor is the subject line true: both do accept factors but what they do with factors is undocumented. From the help (not 'man') page Performs *set* union, intersection, (asymmetric!) difference, equality and membership on two vectors. ^^^^^^^ so it is not said to work on factors. I disagree that what intersect() for

Full_Name: Lutz Prechelt Version: 2.4.1 OS: Windows XP Submission from: (NULL) (160.45.111.67) I stack a number of data.frames using rbind. Each of these dataframes has a column 'authorname', which is a factor and a column author = unclass(authorname) as piecewise pseudonyms. When using rbind to stack these dataframes, R warns about invalid factor levels and inserts all NAs in the author

Hello all, trying to prepare my first package for submission to CRAN I am stumbling over the "checking examples" step of R CMD check. I have some examples that produce more than one plot. I currently separate those plot calls by readline("Press <Return> for a plot including a density plot") or some such to have R wait before producing the next plot. This works OK

(was: AW: [Rd] R CMD check: checking examples: how to (not) pause execution) Paul, Brian, > > I think the more usual way to solve this is to have the user set > > par(ask=TRUE) is they want to be prompted. thank you. Looking back, 'par' would have been a likely candidate for looking. One reason I did NOT look there is that I need the functionality for print.trellis in

Full_Name: Lutz Prechelt Version: 2.2.1 OS: WinXP SP2 Submission from: (NULL) (130.133.8.114) This command plot(0, 0, xlim=c(3, 5), ylim=c(0, 10, 17)) should complain about 'ylim' (because it has three elements). However, it does in fact (in my german error message at least) complain about 'xlim' instead: Fehler in plot.window(xlim, ylim, log, asp, ...) : ung?ltiger

Hello everybody, I am just trying to put together my first own CRAN-able package. I have completed the programming and my code works OK. But now when I perform R CMD check agsemisc_1.0-2.tar.gz and R gets to the step * checking examples ... I receive the following error message: > print(bwplot(Species~Sepal.Length, data=iris, panel=panel.bwstrip)) Error in rep(T, length(x)) : T used

Hello everybody, I have a bunch of strings like this: "IBM POWER4+ 1.9GHz" "IBM RS64-III 500MHz" "IBM RS64-IV 600 MHz" "IBM RS64 IV 750MHz" "Intel Itanium 2 Processor 6M 1.5GHz" "Intel Itanium2 1 Ghz" "Intel Itanium2 1.5GHz" "Intel

Dear Lattice bit-meddlers, while within a panel function for xyplot, how can I find out the values of (effectively) xlim and ylim -- no matter whether they have been set explicitly or chosen by Lattice itself? I have just tried for an hour to find out, with no success whatsoever. I looked in Grid for something that would return such data, but got lost. I looked at tracebacks of panel calls,

Brian Ripley wrote (to somebody asking about "effect sizes"): > ... > Given that, I wonder if you are used to standard terminology. Good point. But I think for many of us there is more behind that. I personally belong to an (apparently fairly large) group of R users who may be enthusiastic, but are statistical laymen due to a lack of formal education in the area. The

I am looking for a function like my.blockwisesum(vector, n) that computes sums of disjoint subsequences of length n from vector and can work with vector lengths that are not a multiple of n. It should give me for instance my.blockwisesum(1:10, 3) == c(6, 15, 24, 10) Is there a builtin function that can do this? One could do it by coercing the vector into a matrix of width n, and then use

In your data frames, 'y' is a category and the following comment in the code makes clear this is deliberate. if( !is.null(levels(xj)) ) { all.levs[[j]] <- levels(xj) facCol[j] <- TRUE # turn categories into factors } else facCol[j] <- is.factor(xj) The behaviour is compatible with S apart from the comment in the R help

I have a large computation that performs various bootstrap resampling loops over pairs of samples using lapply(). After a few seconds it stops like this > do.summarize.effects(compute.power=T) ... Error: Unimplemented feature in rep > .Traceback [[1]] [1] "rep(no, length = length(ans))" [[2]] [1] "ifelse(t.howto == \"n\", boot.result, l.meanboot.test(onew.x,

Hi all, This is my first post to the developers list. As I understand it, aggregate() currently repeats a function across cells in a dataframe but is only able to handle functions with single value returns. Aggregate() also lacks the ability to retain the names given to the returned value. I've created an agg() function (pasted below) that is apparently backwards compatible (i.e.

Hi, I am using aggregate() to add up groups of data according to year and month. It seems that the function aggregate() automatically sorts the levels of factors of the grouping elements, even if the order of the levels of factors is supplied. I am wondering if this is a bug, or if I missed something important. Below is an example that shows what I mean. Does anyone know if this is just the way

I'm having a problem with aggregate.formula when I call it in a function and the function is converted from a string in the funtion I think my problem may also only occur when the left hand side of the formula is cbind(...) Here is example code that generates a dataset and then the error. The first function "agg2" fails > agg2(FALSE) do agg 2 Error in m[[2L]][[2L]] : object

On 6 nov. 07, at 06:17, Chris Lattner wrote: >> But then, why refuse aggregates as input or output of a call? What is >> the rationale? > > Because LLVM has no notion of aggregates as "values" that can be > passed around as atomic units. This is a very important design point, > and has many useful values. I see. You explained one of them in a message on the XL

Hi, I''m having a dataframe ''Subset1'' with a number of factor variables and 160 numerical variables Now I want to make sums for all rows that have the same values for the different factor variables, except for the factor variables: VAR1,VAR2,VAR3 who may have the same values. With the formula given below this works great, but in a situation with 15000 rows and 13

Hi, I have a financial (zoo) time series with prices and volumes (although I can get the coredata as a matrix). Due to the data-source some indices have multiple observations. I want to aggregate these according to a weighted average. 11:00:01 34 1000 11:00:01 35 500 11:00:01 35 1000 11:00:02 34 500 11:00:02 35 500 should become 11:00:01 34.6 2500 11:00:02 34.5 1000 I currently do this

Dear R-devels, I am looking for a package (or some other infrastructure) for the following situation: I am doing a larger data evaluation. I have several dozen data files and do not want to keep the persistent data in the R workspace (for robustness reasons). I have several dozen R files, some for reading and preprocessing data files, others for doing plots or analyses. I will make frequent