Hello, Xianming,
I have changed your (particular) data structure: use matrices because you
have only numeric scores and effects, use NA instead of -1 as missing
value (as usual), don't use columns for ids or row/column names (except
for the easy of reading the data structures), increase your score values
in dat1 by 1 to obtain valid column indices for dat2. Finally, loop (!)
rowwise through your matrix dat1 and construct an index-matrix (!) to
index dat2 (and sum up the indexed elements). Hope this does what you
want. (See below.)
The same remark regarding elegancy/efficiency applies as in Petr's
solution (but w/o an additional package ;-)).
dat1 <- cbind( c(2, 2, 1, NA, 0),
c(1, 0, 1, NA, 1),
c(0, 1, 1, NA, 0))
# dimnames( dat1) <- list( paste0( 'C', 1:5), paste0( "m", 1:3))
dat2 <- cbind( c(-19.5482, -.512, -.492),
c(.007, 3.241, -2.256),
c(1.223, -4.490, 1.779))
# rownames( dat2) <- paste0 ('m', 1:3)
apply( dat1 + 1, 1,
function( idx, d2)
sum( d2[ cbind( seq( nrow( d2)), idx)]),
d2 = dat2
)
Hth -- Gerrit
On Tue, 11 Aug 2015, Xianming Wei wrote:
[I might have sent the following request to a wrong email address -
'r-help-requ...@r-project.org']
Hi,
I have two data frame dat1 and dat2.
dat1 <- data.frame(pid = paste('C', 1:5, sep = ''),
m1 = c(2, 2, 1, -1, 0),
m2 = c(1, 0, 1, -1, 1),
m3 = c(0, 1, 1, -1, 0))
dat2 <- data.frame(mid = paste('m', 1:3, sep = ''),
'0' = c(-19.5482, -.512, -.492),
'1' = c(.007, 3.241, -2.256),
'2' =c(1.223, -4.490, 1.779)) names(dat2)[-1]
<- c('0', '1', '2')
dat1 contains individuals with scores of three measurements (-1 represents
missing) and dat2 with the effect of the different levels of the three
measurements. What I'd like to do is to summise the effects of three
measurements based on the level effects. So C1 I want to get the values of dat2
for m1 at level 2 = 1.223, m2 at level 1 = 3.241 and m3 at level 0 = -0.4920
and sum them up as 3.972.
I can only think of a loop to do that at the moment. Because of much higher
dimensions of actual two datasets, I need help to come up with an efficient /
elegant approach.
Any help is much appreciated.
Regards,
Xianming
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