I have a variable called "exposed" and I know already the sum of exposed people over time: have a look to understand
i | exposed |
---|---|
1 | y |
2 | y |
3 | y |
4 | n |
5 | n |
So I have 3 exposed individuals and 2 are not.
t <- 5
#I know that each i in t :
sum(exposed[i]) <- c(3,4,1,4,5)
I created this line of code to capture the change in data:
evol <- list()
for(i in 1:t){evol[[i]]<- df}
for (i in 2:t) {
# condition
}
My question is: what is the condition that I have to write to have in:
evol[[1]]
a data that looks like this:
i | exposed |
---|---|
1 | y |
2 | y |
3 | y |
4 | n |
5 | n |
evol[[2]]
the data looks like this:
i | exposed |
---|---|
1 | y |
2 | y |
3 | y |
4 | y |
5 | n |
evol[[3]]
a data that looks like this:
i | exposed |
---|---|
1 | y |
2 | n |
3 | n |
4 | n |
5 | n |
I hope I made it clear;
Any ideas please;
kind regards.
If I'm understanding you correctly, you want a list of dataframes based on the exposed sums.
Using lapply you can do
exposed <- c(3,4,1,4,5)
evol <- lapply(exposed, \(x) data.frame(i = seq_along(exposed), exposed = c(rep("y", x), rep("n", length(exposed) - x ))) )
evol[[1]]
i exposed
1 1 y
2 2 y
3 3 y
4 4 n
5 5 n