R pivot longer with both annual and monthly data - r

Question

I'm unsure how to structure my pivot longer command when I have both annual and monthly data. For example I have:
wide <- data.frame(region_name = character(), # Create empty data frame
total_population_2019 = numeric(),
total_population_2020 = numeric(),
mean_temperature_2019_1 = numeric(),
mean_temperature_2019_2 = numeric(),
mean_temperature_2020_1 = numeric(),
mean_temperature_2020_2 = numeric(),
stringsAsFactors = FALSE)
wide[1, ] <- list("funville", 50000, 51250, 26.3, 24.6, 25.7, 24.9)
region_name total_population_2019 total_population_2020 mean_temperature_2019_1 mean_temperature_2019_2 mean_temperature_2020_1 mean_temperature_2020_2
funville 50000 51250 26.3 24.6 25.7 24.9
I'm able to pivot on the monthly columns using spread:
long <- pivot_longer(wide, cols = 4:7, names_to = c("layer" ,"year", "month"),
names_pattern = "(.*)_(.*)_?_(.*)") %>%
group_by(layer) %>%
mutate(n = 1:n()) %>%
spread(layer, value) %>%
select(-n)
which gives
region_name total_population_2019 total_population_2020 year month mean_temperature
1 funville 50000 51250 2019 1 26.3
2 funville 50000 51250 2019 2 24.6
3 funville 50000 51250 2020 1 25.7
4 funville 50000 51250 2020 2 24.9
I'd like to now have a population column where the values are attributed for each row/month that falls in that year, ideally would look like:
desired.df <- data.frame(region_name = c("funville", "funville", "funville", "funville"),
year = c("2019", "2019", "2020", "2020"),
month = c("1", "2", "1", "2"),
population = c("50000", "50000", "51250", "51250"),
mean_temperature = c("26.3", "24.6", "25.7", "24.9"))
which gives
region_name year month population mean_temperature
1 funville 2019 1 50000 26.3
2 funville 2019 2 50000 24.6
3 funville 2020 1 51250 25.7
4 funville 2020 2 51250 24.9
Does anyone have a solution? Thanks in advance

Answer 1

One option would be to use the names_pattern argument and the special .value. To make this work I first add a helper month to your population columns. Additionally I use tidyr::fill to fill up the population column:
library(dplyr)
library(tidyr)
wide |>
rename_with(~ paste(.x, 1, sep = "_"), starts_with("total")) |>
pivot_longer(-region_name,
names_to = c(".value", "year", "month"),
names_pattern = "^(.*?)_(\\d+)_(\\d+)$") |>
group_by(year) |>
fill(total_population) |>
arrange(year)
#> # A tibble: 4 × 5
#> # Groups: year [2]
#> region_name year month total_population mean_temperature
#> <chr> <chr> <chr> <dbl> <dbl>
#> 1 funville 2019 1 50000 26.3
#> 2 funville 2019 2 50000 24.6
#> 3 funville 2020 1 51250 25.7
#> 4 funville 2020 2 51250 24.9