[R] R as.numeric()

[Lutz Fischer]

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.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
>>
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>>
>


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