如何根据R中的其他列将NA替换为先前的列值加上一个分组？

Question

I am currently trying to replace NA values in my dataframe with the previous value plus one. However, there is a condition in that the values must never exceed 52 due to that being the number of weeks within a calendar year. Here's an example of the the dataframe below:

Animal  Age   Week
Dog     13     5
Dog     14     6
Dog     15     7
Dog     16     NA
Dog     17     NA
Cat     12     46
Cat     13     47
Cat     14     48
Cat     15     49
Cat     16     50
Cat     17     NA
Rat     10     49
Rat     11     50
Rat     12     51
Rat     13     NA
Rat     14     NA
Rat     15     NA
Rat     16     NA
Rat     17     NA

What I would like the code to output is the following below:

Animal  Age   Week
Dog     13     5
Dog     14     6
Dog     15     7
Dog     16     8
Dog     17     9
Cat     12     46
Cat     13     47
Cat     14     48
Cat     15     49
Cat     16     50
Cat     17     51
Rat     10     49
Rat     11     50
Rat     12     51
Rat     13     52
Rat     14     1
Rat     15     2
Rat     16     3
Rat     17     4

The caveat is that the end age of each animal will always be 17. I tried using R's function "Complete" and "Fill", but I could not find a way to add plus one with the condition that it resets after week 52. Any help would be appreciated.

Answer 1

For each group ( Animal ), we add the first Week number to row number and get the remainder value. We finally replace the 0 value with 52.

library(dplyr)

df %>%
  group_by(Animal) %>%
  mutate(Week = (first(Week) + row_number() - 1) %% 52,
         Week = replace(Week, Week == 0, 52))


#  Animal   Age  Week
#   <fct>  <int> <dbl>
# 1 Dog       13     5
# 2 Dog       14     6
# 3 Dog       15     7
# 4 Dog       16     8
# 5 Dog       17     9
# 6 Cat       12    46
# 7 Cat       13    47
# 8 Cat       14    48
# 9 Cat       15    49
#10 Cat       16    50
#11 Cat       17    51
#12 Rat       10    49
#13 Rat       11    50
#14 Rat       12    51
#15 Rat       13    52
#16 Rat       14     1
#17 Rat       15     2
#18 Rat       16     3
#19 Rat       17     4

---

Similarly, in base R :

df <- transform(df, Week = ave(Week, Animal, FUN = function(x) 
                     seq_along(x) + x[1] - 1 %% 52))
transform(df, Week = replace(Week, Week == 0, 52))

Answer 2

We can use data.table

library(data.table)
setDT(df)[,  Week := (first(Week) + .N - 1) %% 52, Animal][Week == 0, Week := 52][]