Hi,
this works aswell:
for(i in 1:ncol(data)) data[is.na(data[,i]),i] <- 0
i am sure there is way doing it with a member of the apply family, maybe
someone else has an idea.
Johannes
On Fri, Jan 15, 2010 at 9:51 PM, Jim Lemon <j...@bitwrit.com.au> wrote:
> On 01/15/2010 07:10 PM, Uli Kleinwechter wrote:
>
>> Dear all,
>>
>> I'm looking for a way to replace NA's with 0 for a number of variables
>> which share the same ending and which constitute a subset of a data frame.
>>
>> Say, for example, there is
>>
>> data<- data.frame(ax=c(1,2,3,NA,0) , bx=c(3,5,NA,5,1) ,
>>>
>> ay=c(5,NA,2,NA,0) , by=c(4,2,NA,2,1))
>>
>>> data
>>>
>> ax bx ay by
>> 1 1 3 5 4
>> 2 2 5 NA 2
>> 3 3 NA 2 NA
>> 4 NA 5 NA 2
>> 5 0 1 0 1
>>
>> I wish to apply something like //
>> //
>> /> data[is.na(data)]<- 0/
>> //
>> but not to the entire data frame, rather only to the variables ending
>> with x.
>>
>> Hi Uli,
> How about:
>
> data[,grep("x",names(data))][is.na(data[,grep("x",names(data))])]<-0
>
> Jim
>
>
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