extract_country_data() should also include country and prov population data

[mcuadera]

extract_country_data() contains prov population data. However, it would also be handy to attach the country and district population data as well. This ensures consistency when doing the desk reviews, especially with accessing the data (i.e., once subsetting raw.data, they can just focus on doing their analysis using the dataset from extract_country_data())

On the desk reviews, we currently subset the data like so:

cpop.ctry <- raw.data$ctry.pop |> 
  select(ADM0_NAME, adm0guid, u15pop, year, datasource) |>
  rename("ctry" = "ADM0_NAME") |>
  filter(ctry == str_trim(str_to_upper(country)),
         between(year, year(date_first), year(date_last))
  )

ppop.ctry <- raw.data$prov.pop |> 
  select(ADM0_NAME, ADM0_GUID, ADM1_NAME, adm1guid, u15pop.prov, year, 
         datasource) |>
  rename("adm0guid" = "ADM0_GUID",
         "ctry" = "ADM0_NAME",
         "prov" = "ADM1_NAME",
         "u15pop" = "u15pop.prov") |>
  filter(ctry == str_trim(str_to_upper(country)),
         between(year, year(date_first), year(date_last))
  )

dpop.ctry <- raw.data$dist.pop |> 
  select(ADM0_NAME, ADM0_GUID, ADM1_NAME, adm1guid, ADM2_NAME, adm2guid, 
         u15pop, year, datasource) |>
  rename("adm0guid" = "ADM0_GUID",
         "ctry" = "ADM0_NAME",
         "prov" = "ADM1_NAME",
         "dist" = "ADM2_NAME") |>
  filter(ctry == str_trim(str_to_upper(country)),
         between(year, year(date_first), year(date_last))
  )