On 26/05/2017 7:46 AM, A M Lavezzi wrote:
Dear R-Users
I have data on bilateral trade flows among countries in the following form:
head(dataTrade)
iso_o iso_d year FLOW
1 ABW AFG 1985 NA
2 ABW AFG 1986 NA
3 ABW AFG 1987 NA
4 ABW AFG 1988 NA
5 ABW AFG 1989 NA
6 ABW AFG 1990 NA
where:
iso_o: code of country of origin
iso_d: code of country of destination
year: 1985:2015
FLOW: amount of trade (values are "NA", 0s, or positive numbers)
I have 215 countries. I would like to create a 215x215 matrix , say M, in
which element M(i,j) is the total trade between countries i and j between
1985 and 2015 (i.e. the sum of annual amounts of trade).
After collecting the country codes in a variable named "my_iso", I can
obtain M in a straightforward way using a loop such as:
for (i in my_iso){
for(j in my_iso)
if(i!=j){
M[seq(1:length(my_iso))[my_iso==i],seq(1:length(my_iso))[my_iso==j]]
<-
sum(dataTrade[dataTrade$iso_o==i &
dataTrade$iso_d==j,"FLOW"],na.rm=TRUE)
}
}
However, it takes ages.
Is there a way to avoid these loops?
Assuming that you have unique entries for each of the first 3 columns,
you could so something like this:
# Put all the data into an array, indexed by origin, destination, year:
dataMatrix <- as.matrix(dataTrade) # Converts everything to character
dataArray <- array(0, c(215, 215, 31))
dimnames(dataArray) <- list(unique(dataMatrix[,1]),
unique(dataMatrix[,2]), unique(dataMatrix[,3]))
dataArray[dataMatrix[,1:3]] <- dataTrade$FLOW
# Sum across years
apply(dataArray, 3, sum)
I haven't tried this (you didn't give a reproducible example...), so you
may need to tweak it a bit.
Duncan Murdoch
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