[R] matching vectors against vectors
Piet van Remortel
piet.vanremortel at gmail.com
Tue Mar 29 22:47:02 CEST 2005
Hi all.
I have a re-occuring typical problem that I don't know how to solve
efficiently.
The situation is the following: I have a number of data-sets
(A,B,C,...) , consisting of an identifier (e.g. 11,12,13,...,20) and a
measurement (e.g. in the range 100-120). I want to compile a large
table, with all availabe identifiers in all data-sets in the rows, and
a column for every dataset.
Now, not all datasets have a measurement for every identifier, so I
want NA if the set does not contain the identifier.
an example for a single dataset:
#all identifiers
> rep <- c(10:20)
#Identifiers in my dataset (a subset of rep)
> rep1 <- c(12,13,15,16,17,18)
#measurements in this dataset
> rep1.r <- c(112,113,115,116,117,118)
#a vector which should become a column in the final table, now
containing all NAs
> res <- rep(NA,10)
#the IDs and values of my dataset together
> data <- cbind(rep1, rep1.r)
data looks like this:
rep1 rep1.r
[1,] 12 112
[2,] 13 113
[3,] 15 115
[4,] 16 116
[5,] 17 117
[6,] 18 118
Now, I want to put the values 112, 113, 115,... in the correct rows of
the final table, using the identifiers as an indicator of which row to
put it in, so that I finally obtain:
rep res
10 NA
11 NA
12 112
13 113
14 NA
15 115
16 116
17 117
18 118
19 NA
20 NA
I try to avoid repeating 'which' a lot and filling in every
identifier's observation etc, since I will be doing this for thousands
of rows at once. There must be an efficient way using factors,
tapply etc, but I have trouble finding it. Ideal would be if this
could be done in one go, instead of looping.
Any suggestions ?
Thanks,
Piet
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