[R] indexing into a data.frame using another data.frame that also contains values for replacement

[Alice Wines]

Hello all,

     I have a quandry I have been scratching my head about for a
while. I've searched the manual and the web and have not been able to
find an acceptable result, so I am hoping for some help.

     I have two data frames and I want to index into the first using
the second, and replace the specific values I have indexed with more
values from the second data.frame. I can do this using a loop, but I
wanted a quicker solution with no loops involved.

Although my data set is much larger than this, a small example of what
I am trying to do is as follows:

df1 <- data.frame(rows=c("A","B","C", "B", "C", "A"),
columns=c("21_2", "22_2", "23_2", "21_2", "22_2", "23_2"),
values=c(3.3, 2.5, 67.2, 44.3, 53, 66))
df2 <- data.frame(matrix(rep(NA, length(df1$values)),nrow=3, ncol=3))
names(df2) <- c("21_2", "22_2", "23_2")
row.names(df2) <- c("A", "B", "C")

> df1
  rows columns values
1    A    21_2    3.3
2    B    22_2    2.5
3    C    23_2   67.2
4    B    21_2   44.3
5    C    22_2   53.0
6    A    23_2   66.0



> df2
  21_2 22_2 23_2
A   NA   NA   NA
B   NA   NA   NA
C   NA   NA   NA


     Note that none of the same locations in df2 are specified twice
in df2, so I'm not worried about over-writing it.

    I have tried 'mapply' and 'replace', but apparently either they do
not work well for this or I don't understand how to use them properly
for this purpose. My understanding is that 'replace' needs a vector
input and that one cannot create a vector of vectors, so I couldn't
pass my indices to 'replace'.

     When I tried mapply, the code I used was something like what follows:

df3 <- mapply('[<-' , df2, paste(as.character(df1$rows),
as.character(df1$columns), sep=', '), df1$values)

but it yields the following strange result

> df3
        21_2 22_2 23_2 <NA> <NA> <NA>
          NA   NA   NA   NA   NA   NA
          NA   NA   NA   NA   NA   NA
          NA   NA   NA   NA   NA   NA
A, 21_2  3.3  2.5 67.2 44.3   53   66


What I want to see is the following:

>df3
    21_2   22_2  23_2
A   3.3    NA    66.0
B   44.3  2.5    NA
C   NA   53.0   67.2


     I will greatly appreciate any help that can be given as I am
completely bamboozled by this problem and although I found many useful
things in my search for an answer, I did not find out how to do this.

Thanks,

Alice