Run function through all combinations of rows in R - r

Question

For a sample dataframe:
df <- structure(list(area = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 4L,
4L, 4L, 4L), .Label = c("a1", "a2", "a3", "a4"), class = "factor"),
result = c(0L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 0L,
1L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 1L),
weight = c(0.5, 0.8, 1, 3, 3.4, 1.6, 4, 1.6, 2.3, 2.1, 2,
1, 0.1, 6, 2.3, 1.6, 1.4, 1.2, 1.5, 2, 0.6, 0.4, 0.3, 0.6,
1.6, 1.8)), .Names = c("area", "result", "weight"), class = "data.frame", row.names = c(NA,
-26L))
I wish to calculate the risk difference between all combinations of areas (i.e. a1 and a2, a1 and a3, a2 and a3). Preferably this would be in a matrix form.
Up till now, I have just looked at comparing the risk difference (RD) between the regions with the highest and lowest results:
#Include only regions with highest or lowest percentage
df.summary <- data.table(df.summary)
incl <- df.summary[c(which.min(result), which.max(result)),area]
df.new <- df[df$area %in% incl,]
df.new$area <- factor(df.new$area)
#Run relative difference
df.xtabs <- xtabs(weight ~ result + area, data=df.new)
df.xtabs
#Produce xtabs table
RD.result <- prop.test(x=df.xtabs[,2], n=rowSums(df.xtabs), correct = FALSE)
RD <- round(- diff(RD.result$estimate), 3)
... But how would I change this to ensure the code runs through all combinations of areas without having to specify each one in turn? (I may have up to 19 areas).

Answer 1

You can do it using combn function. For example,
uniqueCombinations <- combn(unique(as.character(df$area)), 2)
resultDF <- data.frame(matrix(NA, nrow=dim(uniqueCombinations)[2], ncol=2+1))#2 col for unique combination and 1 for RD value
names(resultDF) <- c(paste0("area_", 1:2), "RD")
for(i in 1:dim(uniqueCombinations)[2]){
#iterate over a unique combination
incl <- uniqueCombinations[,i]
print(incl)
#Your code
df.new <- df[df$area %in% incl,]
df.new$area <- factor(df.new$area)
#Run relative difference
df.xtabs <- xtabs(weight ~ result + area, data=df.new)
df.xtabs
df.xtabs1 <- data.frame(df.xtabs)
#Produce xtabs table
RD.result <- prop.test(x=df.xtabs[,2], n=rowSums(df.xtabs), correct = FALSE)
RD <- round(- diff(RD.result$estimate), 3)
resultDF[i, 1:2] <- incl
resultDF[i, 3] <- RD
}
resultDF
UPDATE : code update to create a resultDF, which will have result from loop.