search for: noradrenalin

Sometimes the absence of a name is maked by an NA: x <- 1:2 names(x)[[1]] <- "a" names(x) # [1] "a" NA Whereas other times its y <- c(a = 1, 2) names(y) # [1] "a" "" Is this deliberate? The help for names() is a bit murky, but an example shows the NA behaviour. Hadley -- http://had.co.nz/

...behaviour. I think it is (a) impossible to change (b) at least somewhat coherent The situation is partially due to the fact that character-NA is a relative latecomer to the language. In the beginning, there was no real distinction between NA and "NA", causing issues when abbreviating Noradrenaline, North America, Nelson Anderson, etc. At some point, it was decided to fix things up, as far as possible in a backawards compatible way. Some common idioms were retained but others were changed to comply with the rules for other vector types. We have the empty string convention on (AFAICT) all co...

Example: xxx <- data.frame(x=1:26,y=letters) xxx$x[c(2,4,6,8)] <- NA xxx$y[c(1,3,5,7)] <- NA yyy <- edit(yyy) The missing values in xxx$y appear as blanks in the spreadsheet window that appears, whereas the missing values in the numeric column "x" appear as "NA" (as I would expect). Is this a bug or a feature? cheers, Rolf Turner P.S. >

Hi, R people. In ?factor, in the "Examples:" section, we see: ## suppose you want "NA" as a level, and to allowing missing values. (x <- factor(c(1, 2, "NA"), exclude = "")) is.na(x)[2] <- TRUE x # [1] 1 <NA> NA, <NA> used because NA is a level. is.na(x) # [1] FALSE TRUE FALSE I'm a bit confused by this example, as I

Dear R-Helpers, Why does R show character missing values in vectors as NA and when stored in a data frame as <NA>? I've searched but did not find an explanation. Thanks, Bob > gender <- c("f","f","f",NA,"m","m","m","m") > gender [1] "f" "f" "f" NA "m" "m"

Hello, R-devel! I posted to R-help, and (inappropriately) to R-bugs, this R/S-Plus difference: > LETTERS[c(NA,2)] in S is c("","B"), but in R is c("NA","B") Kurt Hornik <Kurt.Hornik@ci.tuwien.ac.at> wrote: > I think we do not want to change this. ... > R> is.na(LETTERS[c(NA,2)]) [1] TRUE FALSE > so we really have NA but it is

Can someone point me to the proper place in the documentation or on the Wiki where I can learn how to get R to stop interpreting the string "NA" as something special? I have a table in a database which contains (among other things) country codes and continent codes. The standard set of two-letter codes includes "NA" to denote "North America". I learned of the