Expand / impute time series in R - r

Question

I have a time series that I require on a weekly basis, however I currently have the data on a quarterly basis. For example:
R> test
Quarter week totA totB totC totD
1 1 2015-12-28 1745 1720 11 1714
2 2 2016-03-28 1736 1718 7 1710
3 3 2016-06-27 1777 1768 5 1750
4 4 2016-09-26 1833 1815 13 1795
5 1 2016-12-26 1708 1697 6 1677
R>
What I want is to have the information on a weekly basis, each of the totals (totA to totD) needs to be divided by the number of weeks until the next quarter (i.e. 13, as there are 13 weeks in the quarter in 2016 - but very occasionally it might be 14 if there is a year with 53 weeks such as 2015) such that the quarterly total is the same. So, from the example above, the first 26 weeks become:
1 1 2015-12-28 134.9 132.3 0.8462 131.8
2 2 2016-01-04 134.9 132.3 0.8462 131.8
3 3 2016-01-11 134.9 132.3 0.8462 131.8
4 4 2016-01-18 134.9 132.3 0.8462 131.8
5 5 2016-01-25 134.9 132.3 0.8462 131.8
6 6 2016-02-01 134.9 132.3 0.8462 131.8
7 7 2016-02-08 134.9 132.3 0.8462 131.8
8 8 2016-02-15 134.9 132.3 0.8462 131.8
9 9 2016-02-22 134.9 132.3 0.8462 131.8
10 10 2016-02-29 134.9 132.3 0.8462 131.8
11 11 2016-03-07 134.9 132.3 0.8462 131.8
12 12 2016-03-14 134.9 132.3 0.8462 131.8
13 13 2016-03-21 134.9 132.3 0.8462 131.8
14 14 2016-03-28 133.5 132.2 0.5385 131.5
15 15 2016-04-04 133.5 132.2 0.5385 131.5
16 16 2016-04-11 133.5 132.2 0.5385 131.5
17 17 2016-04-18 133.5 132.2 0.5385 131.5
18 18 2016-04-25 133.5 132.2 0.5385 131.5
19 19 2016-05-02 133.5 132.2 0.5385 131.5
20 20 2016-05-09 133.5 132.2 0.5385 131.5
21 21 2016-05-16 133.5 132.2 0.5385 131.5
22 22 2016-05-23 133.5 132.2 0.5385 131.5
23 23 2016-05-30 133.5 132.2 0.5385 131.5
24 24 2016-06-06 133.5 132.2 0.5385 131.5
25 25 2016-06-13 133.5 132.2 0.5385 131.5
26 26 2016-06-20 133.5 132.2 0.5385 131.5
R>
That was obtained using:
rbind(
data.frame(Week_number=c(1:13),
Week_commencing=seq(as.Date("2015-12-28"), by=7, len=13),
totA=rep(1754/13,13),
totB=rep(1720/13,13),
totC=rep(11/13,13),
totD=rep(1714/13,13)
),
data.frame(Week_number=c(14:26),
Week_commencing=seq(as.Date("2016-03-28"), by=7, len=13),
totA=rep(1736/13,13),
totB=rep(1718/13,13),
totC=rep(7/13,13),
totD=rep(1710/13,13)
)
)
But there's clearly a better way of doing it rather than manually... The data set is, of course, much larger!
I've tried a few things, but other than creating a sequence of weeks and then filling it in manually as above, I'm going around in circles. I'm sure there's a way to do it in the tidyverse, but I can't figure out how (most of my R is self-taught, and from before when tidyverse was available). Any help would be appreciated!

Answer 1

As all information used in this solution comes from the data, the number of days (or weeks) in the final quarter is assumed to be the same as in the quarter preceding it. So you might want to check up on that ...
library(dplyr)
library(lubridate)
library(purrr)
library(tidyr)
test %>%
mutate(week = ymd(week),
weekCount = if_else(week != max(week),
as.double(abs(week - lead(week)))/7,
as.double(abs(week - lag(week)))/7),
weekInQuarter = map(weekCount, ~ seq_len(.)),
across(totA:totD, ~ ./weekCount)) %>%
unnest(weekInQuarter) %>%
mutate(week = week + weeks(weekInQuarter - 1)) %>%
select(- weekCount)
# Quarter week totA totB totC totD weekInQuarter
# <dbl> <date> <dbl> <dbl> <dbl> <dbl> <int>
# 1 1 2015-12-28 134. 132. 0.846 132. 1
# 2 1 2016-01-04 134. 132. 0.846 132. 2
# 3 1 2016-01-11 134. 132. 0.846 132. 3
# 4 1 2016-01-18 134. 132. 0.846 132. 4
# 5 1 2016-01-25 134. 132. 0.846 132. 5
# 6 1 2016-02-01 134. 132. 0.846 132. 6
# 7 1 2016-02-08 134. 132. 0.846 132. 7
# 8 1 2016-02-15 134. 132. 0.846 132. 8
# 9 1 2016-02-22 134. 132. 0.846 132. 9
# 10 1 2016-02-29 134. 132. 0.846 132. 10