如何在R中的特定列上按行计数？

Question

I have a dataframe like the following, where each row is a person and each column is an answer coded 0,1:

data<-as.data.frame(cbind('answer1' = c(0,0,1,0,0,0), 
'answer2' = c(1,1,1,1,1,0),
'answer3' = c(1,1,1,0,1,1), 
'answer4' = c(1,0,0,0,0,0)))

What I would like to do is count, for each person, the number of "1"s in only certain columns and to reference those columns by column name, not number. In this case, "count the number of times 1 appears in "answer1" and "answer3" only." So I want to end up with something that looks like:

data<-as.data.frame(cbind('answer1' = c(0,0,1,0,0,0), 
'answer2' = c(1,1,1,1,1,0), 
'answer3' = c(1,1,1,0,1,1), 
'answer4' = c(1,0,0,0,0,0), 
'sum' = c(1,1,2,0,1,1)))

I've searched and have found a number of related questions but none addressing the specific issue of counting only certain columns and referencing those columns by name. I've tried rowSums and can use it to sum across all columns, but can't seem to get it to select only certain ones. I'm sure there's a very easy answer to this but it's eluding me... Thank you!

edit: I need to actually count the number of instances of "1" rather than simply summing across the two columns, because some rows in the actual dataframe will contain values other than 1 or 0, which will interfere with using a simple summation. So, the example dataframe should have looked like this instead:

data<-as.data.frame(cbind('answer1' = c(0,0,1,0,2,0), 
'answer2' = c(1,1,1,1,1,0), 
'answer3' = c(1,1,1,0,1,1), 
'answer4' = c(1,0,0,0,0,0)))

Answer 1

Update

Based on your edit, try:

> rowSums(data[c("answer1", "answer3")] == 1)
[1] 1 1 2 0 1 1

Original answer

Yes, rowSums is what you want:

> data$sum <- rowSums(data[c("answer1", "answer3")])
> data
  answer1 answer2 answer3 answer4 sum
1       0       1       1       1   1
2       0       1       1       0   1
3       1       1       1       0   2
4       0       1       0       0   0
5       0       1       1       0   1
6       0       0       1       0   1

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There are, however, many other approaches. within (or transform ) is sometimes nice for these types of problems:

within(data, {
  sum <- answer1 + answer3
})