Kou Kou - 3 months ago 22
R Question

How to use dplyr mutate to perform operation on a column when a lag variable and another column is involved

Suppose I have a data frame like this

> dat
a b c
1 1 0.3321008 0.3321008
2 2 -0.2946729 NA
3 3 -0.1447266 NA
4 4 -0.9415429 NA
5 5 -1.0165080 NA


here is the
dput


structure(list(a = 1:5, b = c(0.332100835317822, -0.294672931641969,
-0.144726592564241, -0.941542877670977, -1.0165079846083), c = c(0.332100835317822,
NA, NA, NA, NA)), .Names = c("a", "b", "c"), row.names = c(NA,
-5L), class = "data.frame")


I would like to perform an operation on the
c
column such that
c = lag(c)*b
(except for the first element in c

I can do this using a simple for loop as below

for(i in (1:4)){
dat$c[i+1] <- dat$c[i]*dat$b[i+1]
}


Output:

> dat
a b c
1 1 0.3321008 0.33210084
2 2 -0.2946729 -0.09786113
3 3 -0.1447266 0.01416311
4 4 -0.9415429 -0.01333517
5 5 -1.0165080 0.01355531


How do I do this using dplyr mutate ? or using apply functions?

Answer

By doing the math, we can avoid the iterative computation:

library(dplyr)
dat %>% mutate(c = cumprod(replace(b, 1, 1))*c[1])
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