CODEWITHSUNDEEP
rreplacena
Matthias Prommer
Matthias Prommer

Reputation: 11

Replacing values in a dataframe - why doesn't it work?

for(i in 1:nrow(survey)){
    for(j in 1:ncol(survey)){
        if(survey[i,j] < 1 | survey[i,j] >10){
            survey[i,j] <- "NA"
        }
    }
}

I have this data set:

survey <- data.frame("q1" = c(5, 3, 2, 7, 11, 5),
                     "q2" = c(4, 2, 2, 5, 5, 2),
                     "q3" = c(2, 1, 4, 2, 9, 10),
                     "q4" = c(2, 5, 2, 5, 4, 2),
                     "q5" = c(1, 4, -20, 2, 11, 2))

I would like to replace all the numbers smaller than 1 and larger than 10, so I wrote the r code above. And I got this when running the code:

q1 q2 q3 q4 q5
1  5  4  2  2  1
2  3  2  1  5  4
3  2  2  4  2 NA
4  7  5  2  5 NA
5 NA  5  9  4 NA
6 NA  2 10  2 NA

Why it does not work? What do I miss in the code? Could anyone advise me, please?

Upvotes: 0

Views: 353

Answers (2)

akrun
akrun

Reputation: 886938

Another way would be to use the set function of is.na i.e. is.na<-

is.na(survey) <- survey > 10|survey < 1
survey
  q1 q2 q3 q4 q5
1  5  4  2  2  1
2  3  2  1  5  4
3  2  2  4  2 NA
4  7  5  2  5  2
5 NA  5  9  4 NA
6  5  2 10  2  2

The main issue as mentioned in the comments is "NA" is character string. If we do an assignment to an element in a column that is already a numeric one with character, the whole column is converted to character. Instead, use NA

for(i in 1:nrow(survey)){
     for(j in 1:ncol(survey)){
         if(survey[i,j] < 1 | survey[i,j] >10){
             survey[i,j] <- NA
         }
     }
 }
 
survey
  q1 q2 q3 q4 q5
1  5  4  2  2  1
2  3  2  1  5  4
3  2  2  4  2 NA
4  7  5  2  5  2
5 NA  5  9  4 NA
6  5  2 10  2  2

The comparison operators works differently for character values i.e.

> "10" > "1"
[1] TRUE
> "10" > "5"
[1] FALSE

Upvotes: 1

s__
s__

Reputation: 9485

It could be much easier, try something like this:

survey[survey > 10 | survey < 1] <- NA

survey
  q1 q2 q3 q4 q5
1  5  4  2  2  1
2  3  2  1  5  4
3  2  2  4  2 NA
4  7  5  2  5  2
5 NA  5  9  4 NA
6  5  2 10  2  2

Upvotes: 1

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