Reputation: 3554
I have a data.frame with a block of columns that are logicals, e.g.
> tmp <- data.frame(a=c(13, 23, 52),
+ b=c(TRUE,FALSE,TRUE),
+ c=c(TRUE,TRUE,FALSE),
+ d=c(TRUE,TRUE,TRUE))
> tmp
a b c d
1 13 TRUE TRUE TRUE
2 23 FALSE TRUE TRUE
3 52 TRUE FALSE TRUE
I'd like to compute a summary column (say: e) that is a logical AND
over the whole range of logical columns. In other words, for a given row, if all b:d are TRUE
, then e would be TRUE
; if any b:d are FALSE
, then e would be FALSE
.
My expected result is:
> tmp
a b c d e
1 13 TRUE TRUE TRUE TRUE
2 23 FALSE TRUE TRUE FALSE
3 52 TRUE FALSE TRUE FALSE
I want to indicate the range of columns by indices, as I have a bunch of columns, and the names are cumbersome. The following code works, but i'd rather use a vectorized approach to improve performance.
> tmp$e <- NA
> for(i in 1:nrow(tmp)){
+ tmp[i,"e"] <- all(tmp[i,2:(ncol(tmp)-1)]==TRUE)
+ }
> tmp
a b c d e
1 13 TRUE TRUE TRUE TRUE
2 23 FALSE TRUE TRUE FALSE
3 52 TRUE FALSE TRUE FALSE
Any way to do this without using a for
loop to step through the rows of the data.frame?
Upvotes: 5
Views: 3975
Reputation: 141
By using rowSums in ifelse statement, in one go it can be acheived:
tmp$e <- ifelse(rowSums(tmp[,2:4] == T) == 3, T, F)
Upvotes: 1
Reputation: 176648
You can use rowSums
to loop over rows... and some fancy footwork to make it quasi-automated:
# identify the logical columns
boolCols <- sapply(tmp, is.logical)
# sum each row of the logical columns and
# compare to the total number of logical columns
tmp$e <- rowSums(tmp[,boolCols]) == sum(boolCols)
Upvotes: 7