Remove duplicate observations based on set of rules

Question

I am trying to remove duplicate observations from a data set based on my variable, id. However, I want the removal of observations to be based on the following rules. The variables below are id, the sex of household head (1-male, 2-female) and the age of the household head. The rules are as follows. If a household has both male and female household heads, remove the female household head observation. If a household as either two male or two female heads, remove the observation with the younger household head. An example data set is below.

id = c(1,2,2,3,4,5,5,6,7,8,8,9,10)
sex = c(1,1,2,1,2,2,2,1,1,1,1,2,1)
age = c(32,34,54,23,32,56,67,45,51,43,35,80,45)
data = data.frame(cbind(id,sex,age))

Answer 1

You can do this by first ordering the data.frame so the desired entry for each id is first, and then remove the rows with duplicate ids.

d <- with(data, data[order(id, sex, -age),])
#    id sex age
# 1   1   1  32
# 2   2   1  34
# 3   2   2  54
# 4   3   1  23
# 5   4   2  32
# 7   5   2  67
# 6   5   2  56
# 8   6   1  45
# 9   7   1  51
# 10  8   1  43
# 11  8   1  35
# 12  9   2  80
# 13 10   1  45
d[!duplicated(d$id), ]
#    id sex age
# 1   1   1  32
# 2   2   1  34
# 4   3   1  23
# 5   4   2  32
# 7   5   2  67
# 8   6   1  45
# 9   7   1  51
# 10  8   1  43
# 12  9   2  80
# 13 10   1  45