R: Update with value of previous row (subject to condition)

Question

I would like to update the value in a table with values of the previous row, within groups, (and probably stop the updates on a given condition)

Here is an example:<

Answer 1

something like this ?

ddply(field, 'player', function(x) {
  baseline <- x[x$time == 1, 'energy']
  x$energy <- baseline
  ind <- which(x$prospects < 0.27)
  if (length(ind)) {
    x[min(ind):nrow(x), 'energy'] <- 0
  }
  x
})

Answer 2

Probably there are better ways, but this is what came to my mind. This makes use of roll=TRUE argument. The idea is to first set energy=0.0 where prospects < 0.27:

field[prospects < 0.27, energy := 0.0]

Then, if we remove the NA values from field, we can use roll=TRUE by doing a join with all combinations as follows:

field[!is.na(energy)][CJ(c("a", "b"), 1:3), roll=TRUE][, prospects := field$prospects][]
#    player time prospects energy
# 1:      a    1      0.81   0.63
# 2:      a    2      0.25   0.00
# 3:      a    3      2.05   0.00
# 4:      b    1      1.63  -0.28
# 5:      b    2      2.20  -0.28
# 6:      b    3      0.49  -0.28

We've to reset prospects because the roll changes it too. You could do it better, but you get the idea.

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A variation, so that the roll is performed only on energy column:

field[!is.na(energy)][CJ(c("a", "b"), 1:3), list(energy), 
           roll=TRUE][, prospects := field$prospects][]

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Or it may be simpler to use na.locf from package zoo :

field[time == 1, energy := round(rnorm(2),2)]
field[prospects < 0.27, energy := 0.0]
require(zoo)
field[, energy := na.locf(energy, na.rm=FALSE)]

which works if the first row of each group is guaranteed to be non-NA, which it is here by construction. But if not, you can run na.locf by group, too :

field[, energy := na.locf(energy, na.rm=FALSE), by=player]