csdata provides structural reference data for Norway:
location hierarchies, population counts, and the conventions used across
the csverse format.
See https://niphr.github.io/csdata/reference/index.html for an overview of all available datasets and functions.
What csdata is for
csdata holds the reference tables that Norwegian
surveillance work needs again and again:
- which places exist, and how they nest inside each other;
- how place boundaries were redistricted from 2006 to 2024;
- how many people live in each place, by age and sex.
Every table ships inside the package, so no function call downloads data. Each analysis then stops carrying its own copy of the same lookups.
csdata exports thirteen objects. These five do most of the work.
| Function | Use it when you need |
|---|---|
nor_locations_names() |
The list of places, and which level each place sits at. |
nor_locations_hierarchy_from_to(from, to) |
To map one level onto another, such as every municipality to its county. |
nor_locations_redistricting() |
Weights to move data recorded under older borders onto the 2024 borders. |
nor_population_by_age_cats(cats) |
Denominators: population in the age bands you choose. |
nor_population_by_sex_age_cats(cats) |
The same denominators, split by sex. |
All five take a border argument. 2024 is
the only value they accept. Any other value stops with an error.
Two current limitations
BA-regions are missing from the hierarchy table.
nor_locations_names() lists 159 BA-regions, and
nor_locations_hierarchy_from_to() accepts
"baregion". But the bundled hierarchy table carries no
BA-region codes at all. Every from/to pair
that names "baregion" therefore returns an empty table
instead of an error.
nrow(csdata::nor_locations_hierarchy_from_to(from = "municip", to = "baregion"))
#> [1] 0
nrow(csdata::nor_locations_names()[granularity_geo == "baregion"])
#> [1] 159One location code is used twice. Two different
laboratories share the code lab_nor084467.
loc <- csdata::nor_locations_names()
loc[location_code == "lab_nor084467", .(location_code, location_name)]
#> location_code location_name
#> <char> <char>
#> 1: lab_nor084467 VV-HF Drammen Sykehus
#> 2: lab_nor084467 Laboratoriet Bærum sykehusThis matters when you pass nor_locations_names() as
location_reference, because the lookup is a join on
location_code. The duplicated code matches twice, so you
get more values back than you put in.
csdata::location_code_to_granularity_geo(
c("nation_nor", "county_nor03", "lab_nor084467"),
location_reference = loc
)
#> [1] "nation" "county" "lab" "lab"add_granularity_geo_to_data_set() then fails, because it
tries to write those four values into a three-row table.
x <- data.table(location_code = c("nation_nor", "county_nor03", "lab_nor084467"))
csdata::add_granularity_geo_to_data_set(x, location_reference = loc)
#> Error in `[.data.table`:
#> ! Supplied 4 items to be assigned to 3 items of column 'granularity_geo'. If you wish to 'recycle' the RHS please use rep() to make this intent clear to readers of your code.Leave location_reference unset to avoid both problems.
The granularity then comes from the code prefix, one value per
input.
Where csdata sits, and what to read next
csdata depends on no other cs package, so you can
install it on its own. cstidy imports it.
csmaps uses the same location_code values for
the 2024 borders, so its map polygons join straight onto csdata
tables.
Two vignettes go deeper:
-
vignette("locations_norway", package = "csdata")lists every location code with its name. -
vignette("population_norway", package = "csdata")shows population counts by location and calendar year.
The rest of this page gives the csverse coding rules for locations, ages and sex.
Location
csdata::nor_locations_names() lists the valid locations
and location types. The table below strikes through entries with
uncommon or internal use.
| Valid locations and location types in the csverse format | ||||||
| Geo (Granularity) | N |
Examples
|
||||
|---|---|---|---|---|---|---|
| location_code1 | location_name2 | location_name_description_nb3 | location_name_file_nb_utf4 | location_name_file_nb_ascii5 | ||
| nation | 1 | nation_nor | Norge-Noreg-Norway | Norge-Noreg-Norway | Norge_Noreg_Norway | norge_noreg_norway |
| georegion6 | 5 | georegion_nor1 | Nord-Norge-Davvi-Norggas | Nord-Norge-Davvi-Norggas (landsdel) | Nord_Norge_Davvi_Norggas_landsdel | nord_norge_davvi_norggas_landsdel |
| county | 15 | county_nor42 | Agder | Agder (fylke) | Agder_fylke | agder_fylke |
| notmainlandcounty | 2 | notmainlandcounty_nor22 | Utenfor fastlands-Norge (Jan Mayen) | Utenfor fastlands-Norge (Jan Mayen) (fylke) | Utenfor_fastlands_Norge_Jan_Mayen_fylke | utenfor_fastlands_norge_jan_mayen_fylke |
| missingcounty | 1 | missingcounty_nor99 | Ukjent fylke | Ukjent fylke (fylke) | Ukjent_fylke | ukjent_fylke |
| municip | 357 | municip_nor1820 | Alstahaug | Alstahaug (kommune i Nordland-Nordlándda) | Alstahaug_kommune_i_Nordland_Nordlándda | alstahaug_kommune_i_nordland_nordlandda |
| notmainlandmunicip | 2 | notmainlandmunicip_nor2200 | Jan Mayen | Jan Mayen (kommune i Utenfor fastlands-Norge (Jan Mayen)) | Jan_Mayen_kommune_i_Utenfor_fastlands_Norge_Jan_Mayen | jan_mayen_kommune_i_utenfor_fastlands_norge_jan_mayen |
| missingmunicip | 1 | missingmunicip_nor9999 | Ukjent kommune | Ukjent kommune (kommune i Ukjent fylke) | Ukjent_kommune_i_Ukjent_fylke | ukjent_kommune_i_ukjent_fylke |
| wardoslo | 15 | wardoslo_nor030112 | Alna | Alna (bydel i Oslo-Oslove) | Alna_bydel_i_Oslo_Oslove | alna_bydel_i_oslo_oslove |
| wardbergen | 8 | wardbergen_nor460101 | Arna | Arna (bydel i Bergen) | Arna_bydel_i_Bergen | arna_bydel_i_bergen |
| wardstavanger | 9 | wardstavanger_nor110303 | Eiganes og Våland | Eiganes og Våland (bydel i Stavanger) | Eiganes_og_Våland_bydel_i_Stavanger | eiganes_og_valand_bydel_i_stavanger |
| wardtrondheim | 4 | wardtrondheim_nor500104 | Heimdal | Heimdal (bydel i Trondheim) | Heimdal_bydel_i_Trondheim | heimdal_bydel_i_trondheim |
| extrawardoslo | 2 | extrawardoslo_nor030117 | Marka | Marka (bydel i Oslo-Oslove) | Marka_bydel_i_Oslo_Oslove | marka_bydel_i_oslo_oslove |
| missingwardbergen | 1 | missingwardbergen_nor460199 | Ukjent bydel i Bergen | Ukjent bydel i Bergen (bydel i Bergen) | Ukjent_bydel_i_Bergen | ukjent_bydel_i_bergen |
| missingwardoslo | 1 | missingwardoslo_nor030199 | Ukjent bydel i Oslo | Ukjent bydel i Oslo (bydel i Oslo-Oslove) | Ukjent_bydel_i_Oslo_Oslove | ukjent_bydel_i_oslo_oslove |
| missingwardstavanger | 1 | missingwardstavanger_nor110399 | Ukjent bydel i Stavanger | Ukjent bydel i Stavanger (bydel i Stavanger) | Ukjent_bydel_i_Stavanger | ukjent_bydel_i_stavanger |
| missingwardtrondheim | 1 | missingwardtrondheim_nor500199 | Ukjent bydel i Trondheim | Ukjent bydel i Trondheim (bydel i Trondheim) | Ukjent_bydel_i_Trondheim | ukjent_bydel_i_trondheim |
| baregion7 | 159 | baregion_nor111 | Alstahaug | Alstahaug (BA-region) | Alstahaug_BA_region | alstahaug_ba_region |
| mtregion8 | 5 | mtregion_nor4 | Midt-Norge | Midt-Norge (Mattilsynet-region) | Midt_Norge_Mattilsynet_region | midt_norge_mattilsynet_region |
| lab | 26 | lab_nor000030 | Akershus Universitetssykehus | Akershus Universitetssykehus (lab) | Akershus_Universitetssykehus_lab | akershus_universitetssykehus_lab |
| 1 location_code: Used a) inside datasets and b) in data file names for transfer of data/results between analytic systems. All values are unique. | ||||||
| 2 location_name: Used (rarely) inside results (figures, tables, documents). Can be confusing as some names are duplicated. Its rare usage is demarcated by a line through the text. | ||||||
| 3 location_name_description_nb: Used (frequently) inside results (figures, tables, documents). All values are unique. | ||||||
| 4 location_name_file_nb_utf: Used (frequently) in the file names for results (figures, tables, documents). All values are unique. | ||||||
| 5 location_name_file_nb_ascii: Used (rarely) in the file names for results (figures, tables, documents). Used if file systems have problems with the Norwegian letters æøå. All values are unique. | ||||||
| 6 Landsdeler/riskdeler. Geographical regions. | ||||||
| 7 Bo- og arbeidsmarkedsregioner. Housing and labor market regions. | ||||||
| 8 Mattilsynet-regioner. Food authority regions. | ||||||
Ages
An age MUST be coded as a character. An age MUST contain three
digits. For an age range, join the two ages with an underscore
(e.g. 005_010).
Use 085p rather than >=085 or
85+. This keeps the conversion from long to wide format
straightforward.
| Valid ages in the csverse format | ||
| Value | class | Definition |
|---|---|---|
| "000" | character | One year age group (0 year olds) |
| "079" | character | One year age group(79 year olds) |
| "000_004" | character | Age span of 0-4 year olds |
| "065p" | character | Age span of >=65 year olds |
| "missing" | character | Missing/unknown |
| "total" | character | Everyone |
This format keeps data sorted correctly. It also produces valid variable names in wide format.
A missing age SHOULD be coded as "missing".