[R] R as.numeric()

[David Winsemius]

On May 25, 2011, at 7:25 AM, Lutz Fischer wrote:

>
>
> 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.

as.character is vectorized. You should not need loops.

-- 
David.
>
> 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.scott at 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.scott at auckland.ac.nz,  Fax: +64 9 373 7018
>>>
>>> ______________________________________________
>>> R-help at 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.
>>>
>>
>
>
> -- 
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>
> ______________________________________________
> R-help at r-project.org mailing list
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David Winsemius, MD
West Hartford, CT