similar to: factor issue

Dear All, I have a query : what is the command to count number of repeated words in a column. for ex: a = oranges oranges apples apples grape oranges apple pine the result should be oranges 3 apples 3 grape 1 pine 1 is there an easy way for this. Thanks, Nataraju GM R & D Bangalore -- "No relationship is Static .. You either Step up or Step down" [[alternative HTML

Hi, I have a comma seperated data file which has blanks in it. I am trinying to import it to R using data1<-read.csv("oa_2006.csv", header = TRUE, sep = ",", quote="\"", dec=".") I want the missing values to be "NA". instead R reads them as "U". Any idea why this happens ? Thanks in advance. Regards, Nataraju GM

Hi, I have a query regarding barplot I have a following data AIS LEvel 1 2 3 body region A 10 15 20 B 15 25 15 Now I want to plot a barplot and in each bar (corresponding a body region), I need a percentage of AIS level 1 displayed in the plot. Is there an

Dear All, Assume I have a data.frame that contains also factors and I would like to get another data.frame containing the factors as numeric vectors, to apply functions like sapply(..., median) on them. I read the warning concerning as.numeric or unclass, but in my case this makes sense, because the factor levels are properly ordered. I can do it, if I write for each single column

How do I completely remove the first column? (x <- matrix(c(1, 44, 124, 80, 254, 70, 190, 0, 2, 35, 110, 70, 240, 73, 216, 0, 3, 41, 114, 80, 279, 68, 178, 0, 4, 31, 100, 80, 284, 68, 149, 0, 5, 61, 190, 110, 315, 68, 182, 1, 6, 61, 130, 88, 250, 70, 185, 0, 7, 44, 130, 94, 298, 68, 161, 0, 8, 58, 110, 74, 384, 67, 175, 0, 9, 52, 120, 80, 310, 66, 144, 0, 10, 52, 120, 80, 337, 67, 130, 0, 11,

Hi All, I'm perplexed by the way the unclass function displays a factor whose labels have been swapped with the relevel function. I realize it won't affect any results and that the relevel did nothing useful in this particular case. I'm just doing it to learn ways to manipulate factors. The display of unclass leaves me feeling that the relevel had failed. I've checked three books

I apologize if this is not appropriate for this mailing list. In R, there is already functionality to drop unused factor levels. However, I am proposing the code below that I wrote. In some occasions, it was faster than applying function 'factor'. In any case, there is no restriction for anyone to use the code below. droplevels2 <- function(x) { if (is.null(levels(x))) stop("no

Full_Name: Andrew Stryker Version: 1.8.1 OS: Linux/Win XP Submission from: (NULL) (65.124.252.58) >From ?factor: See Also: '[.factor' for subsetting of factors. 'gl' for construction of "balanced" factors and 'C' for factors with specified contrasts. 'levels' and 'nlevels' for accessing the levels, and

Hello, I have a script in R language that makes sorting using the order() method of R language. What I need is to reimplement this method in any other language (PHP, Perl, Python, Java maybe). First I tried to reimplement it in php, here is some numbers that i need to sort: 1,2,3,4,5,6,7,8,9,10,300,231,11,12,0,1 R language: n = c(1,2,3,4,5,6,7,8,9,10,300,231,11,12,0,1) n [1] 1 2 3 4 5

I used read.dta() to read in a Stata 9 dataset to R. The "Sex01" variable takes on two values in Stata: 0 and 1, and it is labeled "M" and "F" respectively, analogous to an R factor. Thus, read.dta reads it in as a factor. Now, I wanted to see what this variable *really* is, in R. For instance, sometimes R converts a 0/1 variable into a 1/2 variable when it considers

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

Dear all, I am attempting to explain patterns of arthropod family richness (count data) using a regression model. It seems to be able to do a pretty good job as an explanatory model (i.e. demonstrating relationships between dependent and independent variables), but it has systematic problems as a predictive model: It is biased high at low observed values of family richness and biased low at

This is day one on R for me, I am trying to figure out how to do simple computations. For example I have a data set with 200 observations. I am trying to compute the mean and variance in r for 1:25 (first 25 observations); 1:50 (first 50 obs) ; 1:100th observation etc. Here is the dataset: Id value 1 2.2338 2 3.13597 3 1.98685 4 4.35593 5 2.43963 6 4.20262 7 3.12131 8 4.79583 9 3.13937 10

Perhaps someone can enlighten me here: R> x <- factor(LETTERS[1:3]) R> x [1] A B C R> mode(x) [1] "factor" R> class(x) [1] "factor" R> mode(unclass(x)) [1] "factor" S-PLUS has > x <- factor(LETTERS[1:3]) > mode(x) [1] "numeric" > class(x) [1] "factor" > mode(unclass(x)) [1] "numeric" ???

So i have a simple question that doesnt require sample code, not sure if that violates posting rules or not. Is this: [1] "111" "112" "113" "114" "115" "116" "118" "119" "120" "123" "125" "126" [13] "127" "128" "132" "137"

Full_Name: Bo Zhou Version: 2.6.1 (2007-11-26) OS: Windows XP Submission from: (NULL) (207.237.54.242) Hi, I found an arithmetic problem when I'm doing something with POSIXct The code to reproduce it is as follows (This is the recommended way of finding out time zone difference on R News 2004-1 Page 32 URL http://cran.r-project.org/doc/Rnews/Rnews_2004-1.pdf) a=Sys.time()

In a real example I was trying to remove the class from the result of table, just because it was to be used as a building block for other things and a simple integer vector seemed likely to be most efficient. I'm puzzled as to why unclass doesn't work. > zed <- table(1:5) > class(zed) [1] "table" > class(unclass(zed)) [1] "array" >

In a real example I was trying to remove the class from the result of table, just because it was to be used as a building block for other things and a simple integer vector seemed likely to be most efficient. I'm puzzled as to why unclass doesn't work. > zed <- table(1:5) > class(zed) [1] "table" > class(unclass(zed)) [1] "array" >

Hi all, I would like to multithread that script, to detect structure from multilocus genetic data : >library(Geneland) > >geno = read.table("cot966gen_test.txt") #the file is show after >MCMC(geno.dip.codom = geno, varnpop=T, npopmax=20, spatial = F, nit=100000, thinnin=100, path.mcmc="./") >PostProcessChain(path.mcmc="./", nxdom=100, nydom=100,

I compiled R 2.1.0 under Windows XP SP2 as a preliminary to rebuilding a custom package for use with R 2.1.0. The compile completed successfully, and I was able to run demo(graphics) successfully. But make check and make check-recommended fail. > version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 2 minor 1.0 year 2005