Question

I have data arranged like this in R:

indv    time    mass
1         10    7
2          5    3
1          5    1
2          4    4
2         14    14
1         15    15

where indv is individual in a population. I want to add columns for initial mass (mass_i) and final mass (mass_f). I learned yesterday that I can add a column for initial mass using ddply in plyr:

sorted <- ddply(test, .(indv, time), sort)
sorted2 <- ddply(sorted, .(indv), transform, mass_i = mass[1])

which gives a table like:

   indv mass time mass_i
1    1    1    5      1
2    1    7   10      1
3    1   10   15      1
4    2    4    4      4
5    2    3    5      4
6    2    8   14      4
7    2    9   20      4

However, this same method will not work for finding the final mass (mass_f), as I have a different number of observations for each individual. Can anyone suggest a method for finding the final mass, when the number of observations may vary?

Answer 1

You can simply use length(mass) as the index of the last element:

sorted2 <- ddply(sorted, .(indv), transform,
                 mass_i = mass[1], mass_f = mass[length(mass)])

As suggested by mb3041023 and discussed in the comments below, you can achieve similar results without sorting your data frame:

ddply(test, .(indv), transform,
      mass_i = mass[which.min(time)], mass_f = mass[which.max(time)])

Except for the order of rows, this is the same as sorted2.