search for: ifani

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

Hi All, my script tries to do the following on factors: > ## Check for case 3: Umsatz = 0 & Kunde = 1 > for (year in 2011:2015) { + Umsatz <- paste0("Umsatz_", year) + Kunde <- paste0("Kunde01_", year) + Check <- paste0("Check_U_0__Kd_1_", year) + + cat('Creating', Check, 'from', Umsatz, "and", Kunde,

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.

>>>>> 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%

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(),

Hi Your script is not reproducible. Creating Check_U_0__Kd_1_2011 from Umsatz_2011 and Kunde01_2011 Error in ifelse(Kunden01[[Umsatz]] == 0 & Kunden01[[Kunde]] == 1, 1, 0) : object 'Kunden01' not found > This is interesting x <- c(NA, FALSE, TRUE) names(x) <- as.character(x) outer(x, x, "&") ## AND table <NA> FALSE TRUE <NA> NA FALSE

>>>>> Suharto Anggono Suharto Anggono via R-devel <r-devel at r-project.org> >>>>> on Sun, 7 Aug 2016 15:32:19 +0000 writes: > 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 >

>>>>> Suharto Anggono Suharto Anggono via R-devel <r-devel at r-project.org> >>>>> on Thu, 11 Aug 2016 16:19:49 +0000 writes: > 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,

R version 2.14.0, started with --vanilla > table(c(1,2,3,4,NA), exclude=2, useNA='ifany') 1 3 4 <NA> 1 1 1 2 This came from a local user who wanted to remove one particular response from some tables, but also wants to have NA always reported for data checking purposes. I don't think the above is what anyone would want. PS. This is on a

Hi guys, I hope you can help me with this. Here is the problem: I have some data (myData) that looks similar to this: [,1] [,2] [,3] [,4] [1,] "A" "A" "B" "B" [2,] "B" "B" "B" "B" [3,] "C" "C" "C" "C" When I build a contingency table for the first and second

Hi your initial ds > str(ds) 'data.frame': 2 obs. of 3 variables: $ var1: num 1 1 $ var2: logi TRUE FALSE $ var3: logi NA NA first result > str(ds) 'data.frame': 2 obs. of 6 variables: $ var1 : num 1 1 $ var2 : logi TRUE FALSE $ var3 : logi NA NA $ value_and_logical: logi TRUE TRUE $ logical_and_na : logi TRUE NA

Looking at the code of function 'table' in R devel r71227, I see that the part "remove NA level if it was added only for excluded in factor(a, exclude=.)" is not quite right. In is.na(a) <- match(a0, c(exclude,NA), nomatch=0L) , I think that what is intended is a[a0 %in% c(exclude,NA)] <- NA . So, it should be is.na(a) <- match(a0, c(exclude,NA),

Hi I've recently started using Emacs as my text editor for writing R script. I am looking for a feature which I have seen on the standard R text editor for Mac OS. In the Mac OS editor when you start typing a function, the possible arguments for that function appear at the bottom of the window. E.g. if you type "table( " before you finish typing you can see at the bottom of the

Dear all I'm creating two way tables based on weighted survey data using svytable and want to include NAs as a level in the table. For unweighted data I use table(..., useNA="ifany"). Is there any equivalent for svytable? If not, is there a solution using a different function? Thanks Tim -- Tim Elwell-Sutton The University of Hong Kong Office: 3906 2053 Mob: 6084 5654

In R 2.7.2, if argument 'exclude' is not specified and input is already a factor, function 'table' uses the input as is. In R 2.15.2, in the same case, function 'table' always applies function 'factor' to the input. The time spent by 'factor' is not long, but is not negligible. I suggest to change 'table' so that 'factor' is not called for

Hello, might be rather easy for R pros, but I've been searching to the dead end to ... twsource.area <- table(twsource, area, useNA="ifany") gives me a nice cross tabulation of frequencies of two factors, but now I want to convert to pecentages of those absolute values. In addition I'd like an extra column and an extra row with absolute sums. I know, Excel or the

Hi, I have large data frame with many columns. A short example is given below: > dataH host ms01 ms31 ms33 ms34 1 cattle 4 20 9 6 2 sheep 4 3 4 5 3 cattle 4 3 4 5 4 cattle 4 3 4 5 5 sheep 4 3 5 5 6 goat 4 3 4 5 7 sheep 4 3 5 5 8 goat 4 3 4 5 9 goat 4 3 4 5 10 cattle

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):