R: replacing values in the randomly selected fractions of observations - r

Question

I am relatively new to R and probably the solution to this problem is rather simple.
Let's imagine that i have nest dataset of bird two species (a and b) like this:
df
year nestid sp egg chick
2013 a1 a 2 1
2013 a2 a NA 1
2013 a3 a NA 0
2013 a4 a NA 1
2013 a5 a NA 0
2013 b1 b 2 0
2013 b2 b NA 1
2013 b3 b NA 2
2013 b4 b NA 1
2014 a1 a NA 1
2014 a2 a NA 1
2014 a3 a 1 1
2014 a4 a NA 1
2014 a5 a NA 1
2014 b1 b NA 1
2014 b2 b NA 2
2014 b3 b NA 2
2014 b4 b NA 1
I want to infer number of eggs for those 'NAs' from number of chicks. It makes sense to replace "NA" by 2 if there were "2" chicks as they lay 2 eggs max.
But i want to replace NAs by "2" for randomly selected 80% of nests with 1 chick and replace by "1" for remaining 20% of the nests with 1 chick for species "a" in year 2013. But this ratio would be 40% and 60% for clutch sizes of 2 and 1 respectively for species "a" in 2014.
I tried like this but could not work out how to code properly.
df%>% mutate(egg=ifelse(egg==0 & chick==2, 2, egg))
df%>%
mutate(egg=ifelse(egg==0 & chick==1 & year==2013, sample_frac(.8)==2, egg))
Any help would be greatly appreciated!
Many thanks

Answer 1

One of the approach could be
set.seed(123)
#missing egg & chick = 2
df$egg <- with(df,ifelse(is.na(egg) & chick == 2, 2, egg))
#2013 data having species = 'a', missing egg & chick = 1
x <- with(df, which(is.na(egg) & chick == 1 & sp == 'a' & year == 2013))
x_sample <- sample(x, round(0.8 * length(x)))
df$egg[x_sample] <- 2
df$egg[setdiff(x, x_sample)] <- 1
#2014 data having species = 'a', missing egg & chick = 1
x <- with(df, which(is.na(egg) & chick == 1 & sp == 'a' & year == 2014))
x_sample <- sample(x, round(0.4 * length(x)))
df$egg[x_sample] <- 2
df$egg[setdiff(x, x_sample)] <- 1
which gives
> df
year nestid sp egg chick
1 2013 a1 a 2 1
2 2013 a2 a 2 1
3 2013 a3 a NA 0
4 2013 a4 a 2 1
5 2013 a5 a NA 0
6 2013 b1 b 2 0
7 2013 b2 b NA 1
8 2013 b3 b 2 2
9 2013 b4 b NA 1
10 2014 a1 a 1 1
11 2014 a2 a 2 1
12 2014 a3 a 1 1
13 2014 a4 a 2 1
14 2014 a5 a 1 1
15 2014 b1 b NA 1
16 2014 b2 b 2 2
17 2014 b3 b 2 2
18 2014 b4 b NA 1
Sample data:
df <- structure(list(year = c(2013L, 2013L, 2013L, 2013L, 2013L, 2013L,
2013L, 2013L, 2013L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L,
2014L, 2014L, 2014L), nestid = c("a1", "a2", "a3", "a4", "a5",
"b1", "b2", "b3", "b4", "a1", "a2", "a3", "a4", "a5", "b1", "b2",
"b3", "b4"), sp = c("a", "a", "a", "a", "a", "b", "b", "b", "b",
"a", "a", "a", "a", "a", "b", "b", "b", "b"), egg = c(2L, NA,
NA, NA, NA, 2L, NA, NA, NA, NA, NA, 1L, NA, NA, NA, NA, NA, NA
), chick = c(1L, 1L, 0L, 1L, 0L, 0L, 1L, 2L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 1L)), .Names = c("year", "nestid", "sp",
"egg", "chick"), class = "data.frame", row.names = c(NA, -18L
))