similar to: missing values are not allowed in subscripted assignments of data frames

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Hello everybody! I have the following problem: I'd like to select a sample from a subsample in a dataset. Actually, I don't want to select it, but to create a new variable sampleNo that indicates to which sample (one or two) a case belongs to. Lets suppose I have a dataset containing 40 cases: data <- data.frame(var1=seq(1:40), var2=seq(40,1)) The first sample (n=10) I drew like

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For personal aesthetic reasons, I changed the name "data" to "dat". Your code, with a slight modification: set.seed (1357) ## for reproducibility dat <- data.frame(var1=seq(1:40), var2=seq(40,1)) dat$sampleNo <- 0 idx <- sample(seq(1,nrow(dat)), size=10, replace=F) dat[idx,"sampleNo"] <-1 ## yielding > dat var1 var2 sampleNo 1 1 40

Hi David, I was about to post a reply when Bert responded. His answer is good and his comment to use the name 'dat' rather than 'data' is instructive. I am providing my suggestion as well because I think it may address what was causing you some confusion (mainly to use "which", but also the missing !) idx2 <- sample( which( (!data$var1%%2) & data$sampleNo==0 ),

From: Nate Studer <nate.studer@dornerworks.com> Add a utility function to update the rest of the timeslice accounting fields when updating the timeslice of the credit scheduler, so that capped CPUs behave correctly. Before this patch changing the timeslice to a value higher than the default would result in a domain not utilizing its full capacity and changing the timeslice to a value lower

I stand corrected. The part "If set to 'NULL', it implies 'useNA="always"'." is even in the documentation in R 2.8.0. It was my fault not to check carefully. I wonder, why "always" was chosen for 'useNA' for exclude = NULL. Why exclude = NULL is so special? What about another 'exclude' of length zero, like character(0) (not c(),

Good morning, Is there a way to get table() to default to including NAs - as in... table(..., useNA='ifany') or table(..., useNA='always') or table(..., exclude=NULL) ? I can't see a way under table() or options() or searching the archives (probably using the wrong keyword?). > t1 <- c(1,2,3,3,3,2,NA,NA,NA,NA) > table(t1) t1 1 2 3 1 2 3 I keep forgetting to

This is an example from https://stat.ethz.ch/pipermail/r-help/2007-May/132573.html . With R 2.7.2: > a <- c(1, 1, 2, 2, NA, 3); b <- c(2, 1, 1, 1, 1, 1) > table(a, b, exclude = NULL) b a 1 2 1 1 1 2 2 0 3 1 0 <NA> 1 0 With R 3.3.1: > a <- c(1, 1, 2, 2, NA, 3); b <- c(2, 1, 1, 1, 1, 1) > table(a, b, exclude = NULL) b a 1 2

The quirk as in table(1:3, exclude = 1, useNA = "ifany") is actually somewhat documented, and still in R devel r71104. In R help on 'table', in "Details" section: It is best to supply factors rather than rely on coercion. In particular, ?exclude? will be used in coercion to a factor, and so values (not levels) which appear in ?exclude? before coercion will be mapped to

>>>>> Martin Maechler <maechler at stat.math.ethz.ch> >>>>> on Mon, 15 Aug 2016 11:07:43 +0200 writes: >>>>> Suharto Anggono Suharto Anggono <suharto_anggono at yahoo.com> >>>>> on Sun, 14 Aug 2016 03:42:08 +0000 writes: >> useNA <- if (missing(useNA) && !missing(exclude) && !(NA %in%

useNA <- if (missing(useNA) && !missing(exclude) && !(NA %in% exclude)) "ifany" An example where it change 'table' result for non-factor input, from https://stat.ethz.ch/pipermail/r-help/2005-April/069053.html : x <- c(1,2,3,3,NA) table(as.integer(x), exclude=NaN) I bring the example up, in case that the change in result is not intended.

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):

Hello to everyone. I'm trying to use the %in% to match to vectors in ff format. a<-as.ff(data[,1]) %in% fire$fecha > aff (open) logical length=3653 (3653) [1] [2] [3] [4] [5] [6] [7] [8] [3646] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE : FALSE [3647] [3648] [3649] [3650] [3651] [3652] [3653] FALSE FALSE FALSE FALSE FALSE FALSE