Here is my data:
structure(list(date = structure(c(19662, 19663, 19664, 19665,
19666), class = "Date"), tmax = c(12, 13, 12, 11, 15)), class = "data.frame", row.names = c(NA,
-5L))
date tmax
2023-11-01 12
2023-11-02 13
2023-11-03 12
2023-11-04 11
2023-11-05 15
What is want to achieve is the following:
date tmax tmax_climate
2023-11-01 12 NA
2023-11-01 12 NA
2023-11-01 12 12
2023-11-01 12 13
2023-11-01 12 12
2023-11-02 13 NA
2023-11-02 13 12
2023-11-02 13 13
2023-11-02 13 12
2023-11-02 13 11
2023-11-03 12 12
2023-11-03 12 13
2023-11-03 12 12
2023-11-03 12 11
2023-11-03 12 15
2023-11-04 11 13
2023-11-04 11 12
2023-11-04 11 11
2023-11-04 11 15
2023-11-04 11 NA
2023-11-05 15 12
2023-11-05 15 11
2023-11-05 15 15
2023-11-05 15 NA
2023-11-05 15 NA
Basically what I want is to get tmax from two previous days and tmax for two next days. I've tried rollapply(), lead() and lag() but with no luck so far. Preferably I would like to stick to dplyr. Order doesn't matter in tmax_climate (no need to be tmax-1, tmax, tmax+1 as in desired output)
library(dplyr)
df |>
reframe(ref_date = seq.Date(date-2, date+2, "day"), .by = c(date, tmax)) |>
left_join(df |> rename(climate = tmax), join_by(ref_date == date))
Result
date tmax ref_date climate
1 2023-11-01 12 2023-10-30 NA
2 2023-11-01 12 2023-10-31 NA
3 2023-11-01 12 2023-11-01 12
4 2023-11-01 12 2023-11-02 13
5 2023-11-01 12 2023-11-03 12
6 2023-11-02 13 2023-10-31 NA
7 2023-11-02 13 2023-11-01 12
8 2023-11-02 13 2023-11-02 13
9 2023-11-02 13 2023-11-03 12
10 2023-11-02 13 2023-11-04 11
11 2023-11-03 12 2023-11-01 12
12 2023-11-03 12 2023-11-02 13
13 2023-11-03 12 2023-11-03 12
14 2023-11-03 12 2023-11-04 11
15 2023-11-03 12 2023-11-05 15
16 2023-11-04 11 2023-11-02 13
17 2023-11-04 11 2023-11-03 12
18 2023-11-04 11 2023-11-04 11
19 2023-11-04 11 2023-11-05 15
20 2023-11-04 11 2023-11-06 NA
21 2023-11-05 15 2023-11-03 12
22 2023-11-05 15 2023-11-04 11
23 2023-11-05 15 2023-11-05 15
24 2023-11-05 15 2023-11-06 NA
25 2023-11-05 15 2023-11-07 NA