Missing data is not missing

[raffaem]

Consider the following code.

nuts tell us that HR03 is missing but it isn't

mydf <- data.frame(nuts_code=c("HR03", "HR04", "HR05"))
mydf_nuts <- nuts_classify(mydf, nuts_code="nuts_code")
> mydf_nuts$missing_data
# A tibble: 3 × 4
  from_code from_version from_level country
  <chr>     <chr>             <dbl> <chr>  
1 HR02      2021                  2 Croatia
2 HR03      2016                  2 Croatia # <- this is not missing
3 HR06      2021                  2 Croatia

[AAoritz]

Interesting... Since HR03 is classified as version 2024 it is 'missing' from version 2016 in the information on missing data. We should change that...

library(nuts)
library(tidyverse)

data(all_nuts_codes) 

all_nuts_codes %>% 
  filter(country == "Croatia" & nchar(code) == 4 & version >= 2016) %>%
  arrange(version)
#> # A tibble: 10 × 3
#>    code  version country
#>    <chr> <chr>   <chr>  
#>  1 HR03  2016    Croatia
#>  2 HR04  2016    Croatia
#>  3 HR02  2021    Croatia
#>  4 HR03  2021    Croatia
#>  5 HR05  2021    Croatia
#>  6 HR06  2021    Croatia
#>  7 HR02  2024    Croatia
#>  8 HR03  2024    Croatia
#>  9 HR05  2024    Croatia
#> 10 HR06  2024    Croatia

mydf <- data.frame(nuts_code = c("HR03", "HR04", "HR05"))
nuts_classify(mydf, nuts_code = "nuts_code")
#> 
#> ── Classifying version of NUTS codes ───────────────────────────────────────────
#> Within groups defined by country:
#> ✔ All NUTS codes can be identified and classified.
#> ✖ Multiple NUTS versions classified. See the tibble 'versions_data' in the
#>   output.
#> ✖ Missing NUTS codes detected. See the tibble 'missing_data' in the output.
#> $data
#> # A tibble: 3 × 4
#>   from_code from_version from_level country
#>   <chr>     <chr>             <dbl> <chr>  
#> 1 HR03      2024                  2 Croatia
#> 2 HR04      2016                  2 Croatia
#> 3 HR05      2024                  2 Croatia
#> 
#> $versions_data
#> # A tibble: 6 × 3
#>   from_version country overlap_perc
#>   <chr>        <chr>          <dbl>
#> 1 2024         Croatia         66.7
#> 2 2021         Croatia         66.7
#> 3 2016         Croatia         66.7
#> 4 2013         Croatia         66.7
#> 5 2010         Croatia         66.7
#> 6 2006         Croatia         33.3
#> 
#> $missing_data
#> # A tibble: 3 × 4
#>   from_code from_version from_level country
#>   <chr>     <chr>             <dbl> <chr>  
#> 1 HR02      2024                  2 Croatia
#> 2 HR03      2016                  2 Croatia
#> 3 HR06      2024                  2 Croatia
#> 
#> attr(,"groups")
#> [1] "country"
#> attr(,"class")
#> [1] "nuts.classified" "list"

^{Created on 2025-11-28 with reprex v2.1.1}