这是使用plyr做到这一点的一种方法:

Here is a way to do it with plyr :

R> ddply(IN, .(DATE,TRAP), transform, RESULT=ifelse(length(ID)>1,"y","n"))
  ID       DATE TRAP RESULT
1  1 2013-01-01    1      y
2  2 2013-01-01    1      y
3  3 2013-01-01    1      y
4  2 2013-01-01    2      n
5  1 2013-01-02    3      y
6  3 2013-01-02    3      y
7  2 2013-01-03    1      n
8  1 2013-01-03    2      n
9  3 2013-01-03    3      n

请注意，行已重新排序.

Note that the rows have been reordered.

使用data.table的另一种解决方案:

Another solution with data.table :

R> DT <- data.table(IN)
R> DT[,RESULT:=ifelse(.N>1,"y","n"), by=list(DATE,TRAP)]
R> DT
   ID       DATE TRAP RESULT
1:  1 2013-01-01    1      y
2:  2 2013-01-01    1      y
3:  3 2013-01-01    1      y
4:  1 2013-01-02    3      y
5:  2 2013-01-01    2      n
6:  3 2013-01-02    3      y
7:  1 2013-01-03    2      n
8:  2 2013-01-03    1      n
9:  3 2013-01-03    3      n

这里没有重新排序.

或使用基础ave:

IN <- within(IN, { RESULT <- ave(TRAP, list(DATE, TRAP), 
               FUN= function(x) ifelse(length(x) > 1, "y", "n"))})
#   ID       DATE TRAP RESULT
# 1  1 2013-01-01    1      y
# 2  2 2013-01-01    1      y
# 3  3 2013-01-01    1      y
# 4  1 2013-01-02    3      y
# 5  2 2013-01-01    2      n
# 6  3 2013-01-02    3      y
# 7  1 2013-01-03    2      n
# 8  2 2013-01-03    1      n
# 9  3 2013-01-03    3      n