Here are two ways:
dat0 = subset(dat,time==0)
one = as.data.frame(as.table(by(dat0,dat0$id,
function(x)as.character(x$mode)[which.max(x$y)])))
names(one) = c('id','type')
merge(dat,one)
two = sapply(split(dat0,dat0$id),
function(x)as.character(x$mode)[which.max(x$y)])
merge(dat,data.frame(id=names(two),type=two))
- Phil Spector
Statistical Computing Facility
Department of Statistics
UC Berkeley
spec...@stat.berkeley.edu
On Fri, 1 Oct 2010, array chip wrote:
Hi, I am wondering if anyone can propose a simple/best way to do the following:
Let's say I have a data frame
dat <-
cbind(expand.grid(mode=c('right','left'),time=0:3,id=c('p1','p2','p3')),y=c(3,5,rep(4,6),6,2,rep(3,6),4,4,rep(2,6)))
dat
mode time id y
1 right 0 p1 3
2 left 0 p1 5
3 right 1 p1 4
4 left 1 p1 4
5 right 2 p1 4
6 left 2 p1 4
7 right 0 p2 6
8 left 0 p2 2
9 right 1 p2 3
10 left 1 p2 3
11 right 2 p2 3
12 left 2 p2 3
13 right 0 p3 4
14 left 0 p3 4
15 right 1 p3 2
16 left 1 p3 2
17 right 2 p3 2
18 left 2 p3 2
Now I want to add a new column "type" to this data frame with values of either
"left" or "right" for each "id" based on the following logic:
For each "id", the value of "type" column is the value of "mode" for which the
value of "y" is the maximum of "y" based on time=0. For example for id=p1, the
value of "type" is "left" because for the 2 "y" values (3 & 5) based on time=0,
mode=left has the bigger "y" value (5). But if the 2 "y" values are the same for
"mode", then let type=right.
In the end the new data frame is:
mode time id y type
1 right 0 p1 3 left
2 left 0 p1 5 left
3 right 1 p1 4 left
4 left 1 p1 4 left
5 right 2 p1 4 left
6 left 2 p1 4 left
7 right 0 p2 6 right
8 left 0 p2 2 right
9 right 1 p2 3 right
10 left 1 p2 3 right
11 right 2 p2 3 right
12 left 2 p2 3 right
13 right 0 p3 4 right
14 left 0 p3 4 right
15 right 1 p3 2 right
16 left 1 p3 2 right
17 right 2 p3 2 right
18 left 2 p3 2 right
Any suggestions would be appreciated.
John
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