[R] assign NA to rows by test on multiple columns of a data frame

[Rui Barradas]

Hello,

Try the following.


icol <- which(grepl("flag", names(mydf)))
mydf[icol] <- lapply(mydf[icol], function(x){
         is.na(x) <- x == 0
         x
     })

mydf
#   A A_flag B B_flag
#1  8     10 5     12
#2  7     NA 6      9
#3 10      1 2     NA
#4  1     NA 1      5
#5  5      2 0     NA


Hope this helps,

Rui Barradas

On 11/22/2017 10:34 AM, Massimo Bressan wrote:
> 
> 
> Given this data frame (a simplified, essential reproducible example)
> 
> 
> 
> 
> A<-c(8,7,10,1,5)
> 
> A_flag<-c(10,0,1,0,2)
> 
> B<-c(5,6,2,1,0)
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> B_flag<-c(12,9,0,5,0)
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> 
> 
> 
> mydf<-data.frame(A, A_flag, B, B_flag)
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> 
> 
> 
> # this is my initial df
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> mydf
> 
> 
> 
> 
> I want to get to this final situation
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> 
> 
> i<-which(mydf$A_flag==0)
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> mydf$A[i]<-NA
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> 
> 
> 
> ii<-which(mydf$B_flag==0)
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> mydf$B[ii]<-NA
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> 
> 
> 
> # this is my final df
> 
> mydf
> 
> 
> 
> 
> By considering that I have to perform this task in a data frame with many columns I’m wondering if there is a compact and effective way to get the final result with just one ‘sweep’ of the dataframe?
> 
> 
> 
> 
> I was thinking to the function apply or lapply but I can not properly conceive how to…
> 
> 
> 
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> any hint for that?
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> 
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