for loops and if conditional applied to data frames - r

Question

If have two csv data frames data1 and data2 of dimension/size n1*n2 and m1*m2. I would like to create a new data frame consisting of differences: If (and only if)
data1[i,1] = data2[j,1] & data1[i,3] = data2[j,3]
then I want to consider
difference[i,z] <- abs(data1[i,x]-data2[i,y])
Is it possible to this in a simple manner, for instance using for/if?
difference <- matrix(nrow = max{n1,m1}, ncol = 3)
for (i in 1:n1) {
for (j in 1:m1) {
if(data1[i,1] == data2[j,1] & data1[i,3] == data2[j,3]){
difference[i,1] = data1[i,1]
difference[i,2] = data1[i,3]
difference[i,3] = data1[i,6]-data2[j,7]
}
}
This code is obviously far from being complete and I have several issues:
(1) I don't know if it is realizable using for loops/if conditional. If yes, being unfamiliar with R, I'm not sure if I need to put a 'print(something)' at the end of the loops.
(2) data1/2[i,1] is of type character. Hence I'm not sure if
data1[i,1] == data2[j,1] & data1[i,3] == data2[j,3]
is well-defined.
(3) The 'difference' matrix/frame should have as many rows as the number of i's and j's where
data1[i,1] = data2[j,1] & data1[i,3] = data2[j,3]
I do not know what this number is. Therefore I cannot really specify the size of 'difference'.
EDIT:
data1 = read.csv("path/to/data1.csv") ## Prices of 157 products each at
## 122 time points; (column1=Product, column3=date, column7=price)
data2 = read.csv("path/to/data2.csv") ## Prices of 118 products each at
## 122 time points; (column1=Product, column3=date, column6=price)
## the 122 time points are the same for both frames
## But: data1 contains some products data2 doesn't and vice versa
## I want to compare prices of the same products at the same time
So far, I've done it manually for product X1:
priceX1 = as.data.frame(data1[c(1,122),7])
priceX2 = as.data.frame(data2[c(5,126),6]) ## Product X2 starts at row 5
differenceX1 <- abs(priceX1 - priceX2)
The problem is I'd have to repeat this for all products contained in both data1 and data2.
RE-EDIT: dput(data1) returns
...), class = "factor"),
COMMENT = c(NA, ..., NA)), .Names = c("PRODUCT", "QUALIFIER_I",
"DATE", "QUALIFIER_II", "QUOTATION_DATE", "PROD_DATE", "PRICE",
"TYPE", "ID", "COMMENT"), row.names = c(NA, 14400L), class
= "data.frame")
"..." stands for me omitting a long list of products that couldn't fit here.
dput(data2) returns
..., NA, NA, NA)), .Names = c("PRODUCT", "QUALIFIER_II",
"DATE", "QUALIFIER_I", "Data2_source", "PRICE"), row.names = c(NA,
19161L), class = "data.frame")
"..." stand for me omitting a huge list of prices that couldn't fit in here.

Answer 1

You can find all pairs (i,j) which satisfy your condition by merging the two data.frames:
differences = merge(data1, data2, by=c('PRODUCT','DATE'))
This avoids for-loops entirely, and you can easily define the new column:
differences$Diff = abs(differences$PRICE.x - differences$PRICE.y)