Title: Easy Access for South Korea Census Data and Boundaries
Version: 0.2.3
Description: Census and administrative data in South Korea are a basic source of quantitative and mixed-methods research for social and urban scientists. This package provides a 'sf' (Pebesma et al., 2024 <doi:10.32614/CRAN.package.sf>) based standardized workflow based on direct open API access to the major census and administrative data sources and pre-generated files in South Korea.
License: MIT + file LICENSE
LazyData: true
Depends: R (≥ 4.2.0)
RoxygenNote: 7.3.3
Imports: sf, dplyr, tidyr, kosis, utils, rlang
Suggests: knitr, withr, purrr, rmarkdown, ggplot2, biscale, cowplot, tmap, geodata, testthat (≥ 3.0.0), ggspatial, spdep
Config/testthat/edition: 3
Encoding: UTF-8
VignetteBuilder: knitr
URL: https://github.com/sigmafelix/tidycensuskr, https://sigmafelix.github.io/tidycensuskr/, https://sigmafelix.r-universe.dev/tidycensuskr/
BugReports: https://github.com/sigmafelix/tidycensuskr/issues
NeedsCompilation: no
Packaged: 2025-11-04 11:40:35 UTC; isong
Author: Insang Song ORCID iD [aut, cre], Sohyun Park ORCID iD [aut, ctb], Hyesop Shin ORCID iD [aut, ctb]
Maintainer: Insang Song <geoissong@snu.ac.kr>
Repository: CRAN
Date/Publication: 2025-11-10 09:00:02 UTC

South Korea Census Boundary in 2020

Description

District level boundary data in South Korea in 2020. adm2_code column can be used to join with an anycensus() output.

Usage

adm2_sf_2020

Format

A sf object with 250 rows and 3 variables:

Details

Source

Query Korean census data by admin code (province or municipality) and year

Description

The function queries a long format census data frame (censuskor) for specific administrative codes (if provided)

Usage

anycensus(
  year = 2020,
  codes = NULL,
  type = c("population", "housing", "tax", "mortality", "economy", "medicine",
    "migration", "environment"),
  level = c("adm2", "adm1"),
  aggregator = sum,
  ...
)

Arguments

year

integer(1). One of 2010, 2015, or 2020.

codes

integer vector of admin codes (e.g. c(11, 26)) or character administrative area names (e.g. c("Seoul", "Daejeon")).

type

character(1). "population", "housing", "tax", "economy", "medicine", "migration", "environment" or "mortality" Defaults to "population".

level

character(1). "adm1" for province-level or "adm2" for municipal-level. Defaults to "adm2".

aggregator

function to aggregate values when level = "adm1".

...

additional arguments passed to the aggregator function. (e.g., na.rm = TRUE).

Value

A data.frame object containing census data for the specified codes and year.

Note

Using characters in codes has a side effect of returning all rows in the dataset that match year and type. The 'wide' table is returned with separate columns for each class1 and class2 and unit (abbreviated whereof) combination.

Examples

# Query mortality data for adm2_code 21 (Busan)
anycensus(codes = 21, type = "mortality")

# Query population data for adm1 "Seoul" or "Daejeon"
anycensus(codes = c("Seoul", "Daejeon"), type = "housing", year = 2015)

# Aggregate to adm1 level tax (province-level) using sum
anycensus(
  codes = c(11, 23, 31),
  type = "tax",
  year = 2020,
  level = "adm1",
  aggregator = sum,
  na.rm = TRUE
)

South Korea Census Data

Description

District level data including tax, population, business entities, housing, economy, medicine and mortality in South Korea in 2010, 2015, and/or 2020. The availble years and variables depend on the type of data.

Usage

censuskor

Format

A data.frame with 54218 rows and 10 variables:

Details

Note

NA values in the value field indicate that the data was omitted or suppressed. We kept these NA values as-is to reflect the original data from the source. For temporal comparison, province names in adm1 field are standardized to the common names with no suffix in metropolitan cities and "-do" suffix in provinces. For example, "Seoul" instead of "Seoul Metropolitan City", and "Jeollabuk-do" instead of "Jeonbuk State". "KRW" in the unit field stands for South Korean Won. Values are as-is unless otherwise noted in the unit field (e.g., "per 100k population" or "million KRW").

Source

geofacet Grid for South Korea Administrative Districts (SGIS Standard, 2020)

Description

A geofacet grid for South Korea administrative districts (Si-Gun-Gu) based on the Statistical Geographic Information Service (SGIS) standard in 2020. Non-autonomous districts in cities are retained as separate entities. This grid can be used with the geofacet package to create faceted visualizations based on geographic layout.

Usage

kr_grid_adm2_sgis_2020

Format

A data.frame with 250 rows and 6 variables

Details

Source

Load district boundaries for a specific year

Description

Load district boundaries for a specific year

Usage

load_districts(year = 2020)

Arguments

year

The year for which to load district boundaries (2010, 2015, or 2020)

Value

An sf object containing district boundaries for the specified year

Note

This function requires the tidycensussfkr package to be installed. No explicit dependency is defind; but users should install the package following the instructions at vignette('v01_intro') or more succinctly: install.packages('tidycensussfkr', repos = 'https://sigmafelix.r-universe.dev')

Set KOSIS API Key from a File

Description

This function reads a KOSIS API key from a specified file and sets it for use in KOSIS API calls.

Usage

set_kosis_key(file)

Arguments

file

A character string specifying the path to the file containing the KOSIS API key.

Details

The file should contain the API key as a single line of text. If the file does not exist, an error will be raised.

Value

No return value. A message will be printed to confirm that the key has been set.