[R] joining "one-to-many"

ONKELINX, Thierry Thierry.ONKELINX at inbo.be
Tue Feb 17 16:23:28 CET 2009

Hi Monica,

merge(t1, t2) works on your example. So why don't you use merge?



ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
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tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be 

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say what the experiment died of.
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-----Oorspronkelijk bericht-----
Van: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
Namens Monica Pisica
Verzonden: dinsdag 17 februari 2009 15:33
Aan: R help project
Onderwerp: [R] joining "one-to-many"

Hello list,

I am wondering if a joining "one-to-many" can be done a little bit
easier. I tried merge function but I was not able to do it, so I end up
using for and if.

Suppose you have a table with locations, each location repeated several
times, and some attributes at that location. The second table has the
same locations, but only once with a different set of attributes. I
would like to add the second set of attributes to the first table.


set.seed <- 123
loc <- c(rep("L1", 3), rep("L2", 5), rep("L3", 2))
val1 <- round(rnorm(10),2)
val2 <- c("a", "b", "c", "a", "b", "d", "f", "e", "b", "e")
t1 <- data.frame(loc, val1, val2)
t2 <- data.frame(loc=c("L1","L2","L3"), val3 = c("m", "n", "p"), val4 =
c(25, 67, 48))

# join one-to-many

n <- nrow(t1)
m <- nrow(t2)
t1$val3 <- rep(1, n)
t1$val4 <- rep(1, n)

for (i in 1:n) {
    for (j in 1:m){
    if (t1$loc[i]==t2$loc[j]) {
        t1$val3[i] <- as.character(t2$val3[j])
        t1$val4[i] <- t2$val4[j]

Desired result:

   loc  val1 val2 val3 val4
1   L1 -0.41    a    m   25
2   L1 -0.69    b    m   25
3   L1  0.36    c    m   25
4   L2  1.11    a    n   67
5   L2  0.15    b    n   67
6   L2 -0.80    d    n   67
7   L2 -0.08    f    n   67
8   L2 -1.01    e    n   67
9   L3 -1.01    b    p   48
10  L3 -2.50    e    p   48

This code works OK but it is slow if the data frames are actually bigger
than my little example. I hope somebody knows of a better way of doing
these type of things.



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