I gather data from 4 df's and would like to merge them by rownames. I am looking for an efficient way to do this. This is a simplified version of the data I have.
df1 <- data.frame(N= sample(seq(9, 27, 0.5), 40, replace= T),
P= sample(seq(0.3, 4, 0.1), 40, replace= T),
C= sample(seq(400, 500, 1), 40, replace= T))
df2 <- data.frame(origin= sample(c("A", "B", "C", "D", "E"), 40,
replace= T),
foo1= sample(c(T, F), 40, replace= T),
X= sample(seq(145600, 148300, 100), 40, replace= T),
Y= sample(seq(349800, 398600, 100), 40, replace= T))
df3 <- matrix(sample(seq(0, 1, 0.01), 40), 40, 100)
df4 <- matrix(sample(seq(0, 1, 0.01), 40), 40, 100)
rownames(df1) <- paste("P", sprintf("%02d", c(1:40)), sep= "")
rownames(df2) <- rownames(df1)
rownames(df3) <- rownames(df1)
rownames(df4) <- rownames(df1)
This is what I would normally do:
# merge df1 and df2
dat <- merge(df1, df2, by= "row.names", all.x= F, all.y= F) #merge
rownames(dat) <- dat$Row.names #reset rownames
dat$Row.names <- NULL #remove added rownames col
# merge dat and df3
dat <- merge(dat, df3, by= "row.names", all.x= F, all.y= F) #merge
rownames(dat) <- dat$Row.names #reset rownames
dat$Row.names <- NULL #remove added rownames col
# merge dat and df4
dat <- merge(dat, df4, by= "row.names", all.x= F, all.y= F) #merge
rownames(dat) <- dat$Row.names #reset rownames
dat$Row.names <- NULL #remove added rownames col
As you can see, this requires a lot of code. My question is if the same result can be achieved with more simple means. I've tried (without success): UPDATE: this works now!
MyMerge <- function(x, y){
df <- merge(x, y, by= "row.names", all.x= F, all.y= F)
rownames(df) <- df$Row.names
df$Row.names <- NULL
return(df)
}
dat <- Reduce(MyMerge, list(df1, df2, df3, df4))
Three lines of code will give you the exact same result:
dat2 <- cbind(df1, df2, df3, df4)
colnames(dat2)[-(1:7)] <- paste(paste('V', rep(1:100, 2),sep = ''),
rep(c('x', 'y'), each = 100), sep = c('.'))
all.equal(dat,dat2)
Ah I see, now I understand why you are getting into so much pain. Using the old for loop surely does the trick. Maybe there are even more clever solutions
rn <- rownames(df1)
l <- list(df1, df2, df3, df4)
dat <- l[[1]]
for(i in 2:length(l)) {
dat <- merge(dat, l[[i]], by= "row.names", all.x= F, all.y= F) [,-1]
rownames(dat) <- rn
}