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Maps of Norwegian counties with an insert for Oslo in data.table format

Source: R/data_norway_county.R
nor_county_map_bxxxx_insert_oslo_dt.Rd

We package the map datasets for Norwegian counties, taken from Geonorge, so that you can draw them in ggplot2 with no geolibrary. Every county keeps its default position. The layout adds a magnified copy of Oslo in the blank area east of the mainland outline. This data is licensed under Creative Commons BY 4.0 (CC BY 4.0).

Usage

nor_county_map_b2024_insert_oslo_dt

nor_county_map_b2020_insert_oslo_dt

nor_county_map_b2019_insert_oslo_dt

nor_county_map_b2017_insert_oslo_dt

nor_county_position_geolabels_b2024_insert_oslo_dt

nor_county_position_geolabels_b2020_insert_oslo_dt

nor_county_position_geolabels_b2019_insert_oslo_dt

nor_county_position_geolabels_b2017_insert_oslo_dt

Format

The four nor_county_map_*_insert_oslo_dt datasets are data.tables with one row per polygon vertex:

long

Longitude in decimal degrees (WGS84).

lat

Latitude in decimal degrees (WGS84).

order

Integer draw order carried over from the source polygon conversion. ggplot2::geom_polygon() follows row order, so you rarely need this column, and its values are not contiguous in every dataset.

group

Factor, one level per closed polygon ring; use as the group aesthetic in ggplot2. Several rings can share one location_code.

location_code

County code (e.g. "county_nor03").

The four nor_county_position_geolabels_*_insert_oslo_dt datasets are data.tables with one row per county:

location_code

County code (e.g. "county_nor03").

long

Longitude in decimal degrees (WGS84) of the label anchor.

lat

Latitude in decimal degrees (WGS84) of the label anchor.

repel

Logical layout flag. Draw the TRUE rows with ggrepel::geom_label_repel() and the FALSE rows with ggplot2::geom_label().

An object of class data.table (inherits from data.frame) with 4537 rows and 5 columns.

An object of class data.table (inherits from data.frame) with 4780 rows and 5 columns.

An object of class data.table (inherits from data.frame) with 4589 rows and 5 columns.

An object of class data.table (inherits from data.frame) with 15 rows and 4 columns.

An object of class data.table (inherits from data.frame) with 11 rows and 4 columns.

An object of class data.table (inherits from data.frame) with 18 rows and 4 columns.

An object of class data.table (inherits from data.frame) with 19 rows and 4 columns.

Source

Kartverket / Geonorge https://www.geonorge.no/. License: CC BY 4.0.

Details

Borders for 2024, 2020, 2019, and 2017 are provided. The number of counties differs by border year: 15 in 2024, 11 in 2020, 18 in 2019, and 19 in 2017.

Oslo therefore appears twice. Both copies keep location_code == "county_nor03". The magnified copy takes group levels that start with "x". It spans longitude 17.99 to 23.08 and latitude 60.39 to 63.96. Pair the dataset with nor_xxx_position_title_insert_oslo_bxxxx_insert_oslo_dt, which holds the coordinate for an "Oslo" caption above that copy.

Each border year has a polygon table (nor_county_map_*) and a label table (nor_county_position_geolabels_*). The two hold the same set of location_code values, but different columns.

See also

vignette("layout", package = "csmaps") draws nor_county_map_b2024_insert_oslo_dt and explains the layout. No vignette uses the 2020, 2019 or 2017 datasets, or any label dataset on this page.

Other county maps: nor_county_map_bxxxx_default_dt, nor_county_map_bxxxx_default_sf, nor_county_map_bxxxx_split_dt

Other insert-Oslo layout datasets: nor_municip_map_bxxxx_insert_oslo_dt, nor_xxx_position_title_insert_oslo_bxxxx_insert_oslo_dt

Examples

# 2024 borders
library(ggplot2)
q <- ggplot(mapping = aes(x = long, y = lat))
q <- q + geom_polygon(
  data = csmaps::nor_county_map_b2024_insert_oslo_dt,
  mapping = aes(group = group),
  color = "black",
  fill = "white",
  linewidth = 0.4
)
q <- q + annotate(
  "text",
  x = csmaps::nor_xxx_position_title_insert_oslo_b2024_insert_oslo_dt$long,
  y = csmaps::nor_xxx_position_title_insert_oslo_b2024_insert_oslo_dt$lat,
  label = "Oslo"
)
q <- q + theme_void()
q <- q + coord_quickmap()
q



# 2020 borders
library(ggplot2)
q <- ggplot(mapping = aes(x = long, y = lat))
q <- q + geom_polygon(
  data = csmaps::nor_county_map_b2020_insert_oslo_dt,
  mapping = aes(group = group),
  color = "black",
  fill = "white",
  linewidth = 0.4
)
q <- q + annotate(
  "text",
  x = csmaps::nor_xxx_position_title_insert_oslo_b2020_insert_oslo_dt$long,
  y = csmaps::nor_xxx_position_title_insert_oslo_b2020_insert_oslo_dt$lat,
  label = "Oslo"
)
q <- q + theme_void()
q <- q + coord_quickmap()
q


# 2019 borders
library(ggplot2)
q <- ggplot(mapping = aes(x = long, y = lat))
q <- q + geom_polygon(
  data = csmaps::nor_county_map_b2019_insert_oslo_dt,
  mapping = aes(group = group),
  color = "black",
  fill = "white",
  linewidth = 0.4
)
q <- q + annotate(
  "text",
  x = csmaps::nor_xxx_position_title_insert_oslo_b2019_insert_oslo_dt$long,
  y = csmaps::nor_xxx_position_title_insert_oslo_b2019_insert_oslo_dt$lat,
  label = "Oslo"
)
q <- q + theme_void()
q <- q + coord_quickmap()
q


# 2017 borders
library(ggplot2)
q <- ggplot(mapping = aes(x = long, y = lat))
q <- q + geom_polygon(
  data = csmaps::nor_county_map_b2017_insert_oslo_dt,
  mapping = aes(group = group),
  color = "black",
  fill = "white",
  linewidth = 0.4
)
q <- q + annotate(
  "text",
  x = csmaps::nor_xxx_position_title_insert_oslo_b2017_insert_oslo_dt$long,
  y = csmaps::nor_xxx_position_title_insert_oslo_b2017_insert_oslo_dt$lat,
  label = "Oslo"
)
q <- q + theme_void()
q <- q + coord_quickmap()
q