Fill values in between values in rows in R based on condition - r

Question

I have data that look like this:
id <- c(rep(1,5), rep(2,5), rep(3,4), rep(4,2), rep(5, 1))
year <- c(1990,1991,1992,1993,1994,1990,1991,1992,1993,1994,1990,1991,1992,1994,1990,1994, 1994)
gender <- c(rep("female", 5), rep("male", 5), rep("male", 4), rep("female", 2), rep("male", 1))
dat <- data.frame(id,year,gender)
As you can see, id 1 and 2 have observations for every year between 1990 and 1994, while there are missing observations in between 1990 and 1994 for ids 3 and 4, and, finally, only one observation for id 5.
What I want to do is to copy column id and gender and insert the missing observations for id 3 and 4 so that there are observations from 1990 too 1994, while I want to do nothing with id 1, 2 or 5. Is there are way to create a sequence with numbers from the oldest to the newest observation based on the condition that there is a gap between two numbers grouped by a variable, such as id?
The final result should look like this:
id year gender
<dbl> <dbl> <chr>
1 1 1990 female
2 1 1991 female
3 1 1992 female
4 1 1993 female
5 1 1994 female
6 2 1990 male
7 2 1991 male
8 2 1992 male
9 2 1993 male
10 2 1994 male
11 3 1990 male
12 3 1991 male
13 3 1992 male
14 3 1993 male
15 3 1994 male
16 4 1990 female
17 4 1991 female
18 4 1992 female
19 4 1993 female
20 4 1994 female
21 5 1994 male

Answer 1

Filter the dataset for id 3 and 4, complete their observations and bind the data to other id's where id is not 3 and 4.
library(dplyr)
library(tidyr)
complete_id <- c(3, 4)
dat %>%
filter(id %in% complete_id) %>%
complete(id, year = 1990:1994) %>%
fill(gender) %>%
bind_rows(dat %>% filter(!id %in% complete_id)) %>%
arrange(id)
# id year gender
#1 1 1990 female
#2 1 1991 female
#3 1 1992 female
#4 1 1993 female
#5 1 1994 female
#6 2 1990 male
#7 2 1991 male
#8 2 1992 male
#9 2 1993 male
#10 2 1994 male
#11 3 1990 male
#12 3 1991 male
#13 3 1992 male
#14 3 1993 male
#15 3 1994 male
#16 4 1990 female
#17 4 1991 female
#18 4 1992 female
#19 4 1993 female
#20 4 1994 female
#21 5 1994 male