Thanks a lot for both replies.
If I setup the option as proposed everything works as I wanted it to. I guess as.character would work as well. Only then I guess I would need to loop through the data frame. Lutz On 24/05/11 22:42, Ista Zahn wrote: > This is a FAQ: > > http://cran.r-project.org/doc/FAQ/R-FAQ.html#How-do-I-convert-factors-to-numeric_003f > > Please try there before posting a question to the list. > > Best, > Ista > On Tue, May 24, 2011 at 5:33 PM, David Scott <d.sc...@auckland.ac.nz> wrote: >> On 25/05/2011 9:20 a.m., Lutz Fischer wrote: >>> Hi, >>> >>> I have a bit of a problem with as.numeric or as.double. >>> >>> I read in an excel-file (either xlsx::read.xlsx2 or gdata::read.xls). >>> Select a subset and then try to make it numeric: >>> >>> >>> # read in the excel-file >>> alldata<-read.xlsx2("input.xls",1) >>> # select the subset >>> s<-subset(alldata, select=c("cI","cII","cIII","cIV","cV")) >>> # unluckily we have "n/a" for missing values in the file - so we turn it >>> into "proper" missing values >>> s[s == "n/a"]<-NA >>> >>> n<-data.matrix(s); >>> >>> >>> >>> >>> The problem I have is that it does not convert the date the way I would >>> expect. >>> >>> just as an example: >>> > s[1,2] >>> [1] 30.94346629 >>> 3136 Levels: 0.026307482 0.028239812 0.02849896 0.029054564 0.029540352 >>> 0.030248034 0.030841352 0.032966308 ... n/a >>> >>> turned into: >>> > n[1,2] >>> [1] 3020 >>> >>> And I would like to have there 30.94346629 as well. I assume that has to >>> do with the "Levels" attribute - but not sure what to make of these in >>> the first place. >>> >>> I also tried to convert each value on its own: >>> >>> #make some space that holds the actual numeric data >>> n <- array(dim=c(length(s[,1]),length(s))) >>> # now turn everything into doubles >>> for (c in 1:length(s)) { >>> for (r in 1:length(s[,1])) { >>> n[r,c]<-as.double(s[r,c]) >>> } >>> } >>> >>> but that gave the same result - just a lot slower. >>> >>> >>> >>> Thanks >>> Lutz >>> >>> >> Your problem is the conversion to factors when the data is read. Use >> >> options(stringsAsFactors = FALSE) >> >> before you read the data, then the mixed columns of numeric and missing will >> be read as character data and the conversion to numeric will go as you >> expect. (But I haven't tested this.) >> >> David Scott >> -- >> _________________________________________________________________ >> David Scott Department of Statistics >> The University of Auckland, PB 92019 >> Auckland 1142, NEW ZEALAND >> Phone: +64 9 923 5055, or +64 9 373 7599 ext 85055 >> Email: d.sc...@auckland.ac.nz, Fax: +64 9 373 7018 >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
