similar to: Unexpected alteration of data frame column names

Hi Herve, Inline. On Thu, May 16, 2019 at 4:45 PM Pages, Herve <hpages at fredhutch.org> wrote: > Hi Gabe, > > ncol(data.frame(aa=c("a", "b", "c"), AA=c("A", "B", "C"))) > # [1] 2 > > ncol(data.frame(aa="a", AA="A")) > # [1] 2 > > ncol(data.frame(aa=character(0),

Hi, I was stumped by this. The two S4 objects below looked exactly the same: > a1 An object of class "A" Slot "aa": integer(0) > a2 An object of class "A" Slot "aa": integer(0) > str(a1) Formal class 'A' [package ".GlobalEnv"] with 1 slots ..@ aa: int(0) > str(a2) Formal class

Hi, Here is another problem with data frame subsetting: > df <- data.frame(aa=1:3) > value <- data.frame(aa=11:12, row.names=c("A", "B")) > `[<-`(df, 4:5, , value=value) aa 1 1 2 2 3 3 A 11 B 12 > `[<-`(df, 5:4, , value=value) aa 1 1 2 2 3 3 B 12 A 11 For this last result, the rownames of the

Hi, In the man page for is.unsorted(): Value: A length-one logical value. All objects of length 0 or 1 are sorted: the result will be ?NA? for objects of length 2 or more except for atomic vectors and objects with a class (where the ?>=? or ?>? method is used to compare ?x[i]? with ?x[i-1]? for ?i? in ?2:length(x)?). This contains many incorrect

Hi, It doesn't seem that the dispatching algo is finding my coerce method under some circumstances. Let's say I have 2 classes, A and AA and that AA is just a direct extension of A with no additional slots: setClass("A", representation(ii="integer")) setClass("AA", contains="A") I can define a method for coercing my objects to an integer

Hi, When called with complete=TRUE, validObject() is supposed to work in a recursive manner. But here is a situation where it doesn't seem to be the case. Let's define a class with a validity method: setClass("PosInts", representation(ii="integer")) setValidity("PosInts", function(object) { if (!all(object at ii > 0))

Hi, I am confused by results from: > ddply(aa, names(aa), colwise(sum)) I thought ddply was just calling colwise(sum)() with each column. However ddply() returns a 13 x 5 result !! The general result I expected is similar to that of apply() , or using colwise(sum)() alone. Shouldn't ddply() produce the same ? Thanks in advance for your help, - Stuart Andrews >

Hi, > dd <- data.frame(A=c("b","c","a"), B=3:1) > dd A B 1 b 3 2 c 2 3 a 1 > unlist(dd) A1 A2 A3 B1 B2 B3 2 3 1 3 2 1 Someone else might get something different. It all depends on the values of its 'stringsAsFactors' option: > dd2 <- data.frame(A=c("b","c","a"), B=3:1, stringsAsFactors=FALSE) > dd2

Dear R users, I am currently working in subsetting a zooreg() object using either window or subset. I have a solution but it may be a bit cumbersome when I start working with actual data. Your inputs would be greatly appreciated. Example: I have a zooreg() object that starts in 1997 and ends in 2001. This object contains daily data for the 4 years

Hi, When playing interactively with the S4 system, I've tried to define the following class: > setClass("A", representation("integer")) [1] "A" > showClass("A") Slots: Name: .Data Class: integer Extends: Class "integer", from data part Class "vector", by

On Mon, Sep 21, 2015 at 2:48 PM, Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > On 21/09/2015 4:50 PM, Herv? Pag?s wrote: >> Hi, >> >> Note that one significant change to read.dcf() that happened since R >> 3.0.2 is the addition of support for arbitrary long lines (commit >> 63281), which never worked: >> >> dcf <- paste(c("aa:

(I am reposting this question after a few months without a solution...) Hi all, I am trying to read a .txt file, with Hebrew column names, but without success. I uploaded an example file to: http://www.talgalili.com/files/aa.txt And tried the command: read.table("http://www.talgalili.com/files/aa.txt", header = T, sep = "\t") This returns me with: X.....ª X...ª......

Hi, The trick used by duplicated.data.frame() is to transform the supplied data.frame into a character vector by pasting together the columns using "\r" as separator. But no precautions are taken to deal with "\r" in the supplied data.frame. As a consequence it's easy to imagine situations where duplicated.data.frame() returns an incorrect answer: > df <-

Dear folks-- The function below is a snippet of a larger function that is not doing what it is supposed to do, and I do not understand its behavior. The larger function is supposed to produce an array containing the results of a user-specified function applied to groups of data defined by the intersection of one or more factors, and return them in an array with a dimension for each factor and a

Hi, Today I downloaded and compiled the last R-devel snapshot. The SVN-REVISION in the tarball contains the following: Revision: 36792 Last Changed Date: 2005-12-18 But after compiling on Unix (I compiled out of tree), I ended up with an SVN-REVSION file containing: Revision: unknown Last Changed Date: Today in the build tree. Then when I start R, I get: R : Copyright Today, The

Hi all, Apologies if this has been asked before (a quick google didn't find it for me),and I know this is a case of behaving as documented but its so unintuitive (to me at least) that I figured I'd bring it up here anyway. I figure its probably going to not be changed, but I'm happy to submit a patch if this is something R-core feels can/should change. So I recently got bitten by

Hi, Starting with ordinary vectors, so we know what to expect: > mapply(function(x, y) {x * y}, 101:106, rep(1:3, 2)) [1] 101 204 309 104 210 318 > mapply(function(x, y) {x * y}, 101:106, 1:3) [1] 101 204 309 104 210 318 Now with an S4 object: setClass("A", representation(aa="integer")) a <- new("A", aa=101:106) > length(a)

http://bugs.freedesktop.org/show_bug.cgi?id=16815 Summary: losing fonts in gnome-terminal and other font weirdnesses Product: xorg Version: git Platform: Other OS/Version: All Status: NEW Severity: normal Priority: medium Component: Driver/nouveau AssignedTo: nouveau at

Hi, table1D() below can be up to 60x faster than base::table() for the 1D case. Here are the detailed speedups compared to base::table(). o With a logical vector of length 5M: 11x faster (or more if 'useNA="always"') o With factor/integer/numeric/character of length 1M and 9 levels (or 9 distinct values for non-factors):

OK, what is the trick to extracting the overall p value from an lm object? It shows up in the summary(lm(model)) output but I can't seem to extract it: > test2 = apply(aa, 1, function(x) summary(lm(x[,1] ~ 0 + x[,3] + x[,6]))) > test2[[1]] Call: lm(formula = x[, 1] ~ 0 + x[, 3] + x[, 6]) [omitted summary output] F-statistic: 40.94 on 2 and 7 DF, p-value: 0.0001371 It does not seem