Hello,
The obvious way would be to preallocate the resulting data.frame, to
expand an empty one on each iteration being a time expensive operation.
n <- nrow(expand.grid(1:nrow(D1), 1:nrow(D2)))
D4 <- data.frame(distance=integer(n),difference=integer(n))
k <- 0
for (i in 1:nrow(D1)){
for (j in 1:nrow(D2)) {
k <- k + 1
D4[k, ] <-
c(distance=sqrt(sum((D1[i,1:2]-D2[j,1:2])^2)),difference=(D1[i,3]-D2[j,3])^2)
}
}
identical(D3, D4)
Hope this helps,
Rui Barradas
Em 23-06-2017 16:19, Rathore, Saubhagya Singh escreveu:
For certain reason, the content was not visible in the last mail, so posting it
again.
Dear Members,
I have two different dataframes with a different number of rows. I need to
apply a set of functions to each possible combination of rows with one row
coming from 1st dataframe and other from 2nd dataframe. Though I am able to
perform this task using for loops, I feel that there must be a more efficient
way to do it. An example case is given below. D1 and D2 are two dataframes. I
need to evaluate D3 with one column as the Euclidean distance in the x-y plane
and second column as squared difference of z values, of each row pair from D1
and D2.
D1<-data.frame(x=1:5,y=6:10,z=rnorm(5))
D2<-data.frame(x=19:30,y=41:52,z=rnorm(12))
D3<-data.frame(distance=integer(0),difference=integer(0))
for (i in 1:nrow(D1)){
for (j in 1:nrow(D2)) {
temp<-data.frame(distance=sqrt(sum((D1[i,1:2]-D2[j,1:2])^2)),difference=(D1[i,3]-D2[j,3])^2)
D3<-rbind(D3,temp)
}
}
Thank you
-----Original Message-----
From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of
r-help-ow...@r-project.org
Sent: Friday, June 23, 2017 10:47 AM
To: Rathore, Saubhagya Singh <saubha...@gatech.edu>
Subject: R version 3.3.2, Windows 10: Applying a function to each possible pair
of rows from two different data-frames
The message's content type was not explicitly allowed
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