Hello,
Ok, try instead
library(reshape2)
tmp <- dcast(data = dat2, ID ~ Type, value.var = "Type")
tmp[-1] <- lapply(tmp[-1], function(x){
y <- integer(length(x))
s <- as.character(x[!is.na(x)])[1]
idx <- which(as.character(dat2[["Type"]]) == s)
y[!is.na(x)] <- dat2[["Days"]][idx]
y})
result <- merge(dat1, tmp)
result
Rui Barradas
Em 30-08-2013 10:27, Mat escreveu:
Thanks first.
that doesn't look bad. But if have a equal ID in dat2, the days are no
longer correct.
the correct data.frame has to look like this one:
ID Name Management Training
1 1 Jack 1 3
2 2 John 1 0
3 3 Jill 0 4
not this one:
ID Name Management Training
1 1 Jack 1 1
2 2 John 3 0
3 3 Jill 0 1
dat1 <- read.table(text = "
+ ID Name
+ 1 Jack
+ 2 John
+ 3 Jill
+ ", header = TRUE, stringsAsFactors = FALSE)
dat2 <- read.table(text = "
+ ID Days Type
+ 1 1 Management
+ 1 3 Training
+ 2 1 Management
+ 3 4 Training
+ ", header = TRUE, stringsAsFactors = FALSE)
library(reshape2)
tmp <- dcast(data = dat2, ID ~ Type, value.var = "Type")
tmp[-1] <- lapply(tmp[-1], function(x){
+ y <- integer(length(x))
+ y[!is.na(x)] <- dat2[["Days"]][!is.na(x)]
+ y})
result <- merge(dat1, tmp)
result
ID Name Management Training
1 1 Jack 1 1
2 2 John 3 0
3 3 Jill 0 1
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