Here is an example:
set.seed(123)
data<-data.frame(X=rep(letters[1:3], each=4),Y=sample(1:12,12),Z=sample(1:100, 12))
data[data==3]<-NA
There is a data.table
way
library(data.table)
set.seed(123)
data<-data.frame(X=rep(letters[1:3], each=4),Y=sample(1:12,12),Z=sample(1:100, 12))
data[data==3]<-NA
data <- data.table(data)
data[data[,.I[which.min(Y)], by = "X"][,V1]]
This does not select the rows using an index but returns the values you want...
ddply(data, .(X), summarise, min=min(Y, na.rm=T))
X min
1 a 5
2 b 1
3 c 4
EDIT AFTER COMMENT: To select the whole rows you may:
ddply(data, .(X), function(x) arrange(x, Y)[1, ])
X Y Z
1 a 4 68
2 b 1 4
3 c 2 64
Or
data$index <- 1L:nrow(data)
i <- by(data, data$X, function(x) x$index[which.min(x$Y)] )
data[i, ]
X Y Z index
1 a 4 68 1
6 b 1 4 6
10 c 2 64 10
Using subset to for each letter may be this can help
data<-data.frame(X=rep(letters[1:3], each=4),Y=sample(1:12,12))
dataA <- subset(data, data$X=="a")
min(dataA$Y, na.rm=TRUE)
Using the data.table
package, this is trivial:
library(data.table)
d <- data.table(data)
d[, min(Y, na.rm=TRUE), by=X]
You can also use plyr
and its ddply
function:
library(plyr)
ddply(data, .(X), summarise, min(Y, na.rm=TRUE))
Or using base R:
aggregate(X ~ ., data=data, FUN=min)
Based on the edits, I would use data.table
for sure:
d[, .SD[which.min(Y)], by=X]
However, there are solutions using base R or other packages.