The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

jpcity

R-CMD-check CRAN status Codecov test coverage

README in Japanese is here.

jpcity is an R package for reading and converting Japanese municipality codes. This package provides the following features,

Installation

install.packages("jpcity")

You can install the development version of jpcity from GitHub with:

# install.packages("devtools")
devtools::install_github("UchidaMizuki/jpcity")

Examples

library(jpcity)
library(tidyverse)

Read city codes

city <- parse_city(c("13101", "27101", "23101"))
#> Guessing the interval to be 1970-04-01 JST--1989-02-12 JST.
#> ℹ You can override using `when` argument.

# Override the interval using `when` argument
city <- parse_city(c("13101", "27101", "23101"),
                   when = "1989-02-12")
city
#> <city[3]> Interval: 1970-04-01--1989-02-12
#> [1] 13101 27101 23101
#> 
#> Cities:
#>   city_code pref_name city_desig_name city_desig_name_kana city_name
#> 1     13101    東京都            <NA>                 <NA>  千代田区
#> 2     27101    大阪府          大阪市           おおさかし      北区
#> 3     23101    愛知県        名古屋市             なごやし    千種区
#>   city_name_kana
#> 1       ちよだく
#> 2         きたく
#> 3       ちくさく

tibble(city = city,
       pref_name = pref_name(city),
       city_name = city_name(city),
       city_name_kana = city_name(city,
                                  kana = TRUE))
#> # A tibble: 3 × 4
#>   city                         pref_name city_name      city_name_kana  
#>   <city>                       <chr>     <chr>          <chr>           
#> 1 13101 [東京都千代田区]       東京都    千代田区       ちよだく        
#> 2 27101 [大阪府大阪市北区]     大阪府    大阪市北区     おおさかしきたく
#> 3 23101 [愛知県名古屋市千種区] 愛知県    名古屋市千種区 なごやしちくさく

Convert to city codes at a different point in time

city <- parse_city(c("13101", "27101", "23101"),
                   when = "1980-01-01")
tibble(city_from = city,
       city_to = city_convert(city,
                              from = "1980-01-01",
                              to = "2020-01-01")) |> 
  unnest(city_to)
#> # A tibble: 3 × 2
#>   city_from                    city_to                     
#>   <city>                       <city>                      
#> 1 13101 [東京都千代田区]       13101 [東京都千代田区]      
#> 2 27101 [大阪府大阪市北区]     27127 [大阪府大阪市北区]    
#> 3 23101 [愛知県名古屋市千種区] 23101 [愛知県名古屋市千種区]

city <- parse_city("15100",
                   when = "2020-01-01")
tibble(city_from = city,
       city_to = city_convert(city,
                              from = "2020-01-01",
                              to = "1970-04-01")) |> 
  unnest(city_to)
#> # A tibble: 15 × 2
#>    city_from            city_to               
#>    <city>               <city>                
#>  1 15100 [新潟県新潟市] 15201 [新潟県新潟市]  
#>  2 15100 [新潟県新潟市] 15207 [新潟県新津市]  
#>  3 15100 [新潟県新潟市] 15220 [新潟県白根市]  
#>  4 15100 [新潟県新潟市] 15305 [新潟県豊栄町]  
#>  5 15100 [新潟県新潟市] 15321 [新潟県小須戸町]
#>  6 15100 [新潟県新潟市] 15323 [新潟県横越村]  
#>  7 15100 [新潟県新潟市] 15324 [新潟県亀田町]  
#>  8 15100 [新潟県新潟市] 15341 [新潟県岩室村]  
#>  9 15100 [新潟県新潟市] 15345 [新潟県巻町]    
#> 10 15100 [新潟県新潟市] 15346 [新潟県西川町]  
#> 11 15100 [新潟県新潟市] 15347 [新潟県黒埼村]  
#> 12 15100 [新潟県新潟市] 15348 [新潟県味方村]  
#> 13 15100 [新潟県新潟市] 15349 [新潟県潟東村]  
#> 14 15100 [新潟県新潟市] 15350 [新潟県月潟村]  
#> 15 15100 [新潟県新潟市] 15351 [新潟県中之口村]

Combine wards of designated cities or divide them into wards

city <- parse_city(c("13101", "27101", "23101"),
                   when = "1980-01-01")
tibble(city = city,
       city_desig = city_desig_merge(city),
       city_desig_merge_tokyo = city_desig_merge(city,
                                                 merge_tokyo = TRUE))
#> # A tibble: 3 × 3
#>   city                         city_desig             city_desig_merge_tokyo
#>   <city>                       <city>                 <city>                
#> 1 13101 [東京都千代田区]       13101 [東京都千代田区] 13100 [東京都特別区部]
#> 2 27101 [大阪府大阪市北区]     27100 [大阪府大阪市]   27100 [大阪府大阪市]  
#> 3 23101 [愛知県名古屋市千種区] 23100 [愛知県名古屋市] 23100 [愛知県名古屋市]

Get city codes at a specific point in time

tibble(city = get_city("2020-01-01"))
#> # A tibble: 1,923 × 1
#>    city                      
#>    <city>                    
#>  1 01100 [北海道札幌市]      
#>  2 01101 [北海道札幌市中央区]
#>  3 01102 [北海道札幌市北区]  
#>  4 01103 [北海道札幌市東区]  
#>  5 01104 [北海道札幌市白石区]
#>  6 01105 [北海道札幌市豊平区]
#>  7 01106 [北海道札幌市南区]  
#>  8 01107 [北海道札幌市西区]  
#>  9 01108 [北海道札幌市厚別区]
#> 10 01109 [北海道札幌市手稲区]
#> # ℹ 1,913 more rows

tibble(city = get_city("1970-04-01"))
#> # A tibble: 3,376 × 1
#>    city                  
#>    <city>                
#>  1 01201 [北海道札幌市]  
#>  2 01202 [北海道函館市]  
#>  3 01203 [北海道小樽市]  
#>  4 01204 [北海道旭川市]  
#>  5 01205 [北海道室蘭市]  
#>  6 01206 [北海道釧路市]  
#>  7 01207 [北海道帯広市]  
#>  8 01208 [北海道北見市]  
#>  9 01209 [北海道夕張市]  
#> 10 01210 [北海道岩見沢市]
#> # ℹ 3,366 more rows

Find city codes using the name of the prefecture or city

find_city(c("東京都", "新宿区"))
#> <city[1]> Interval: 1970-04-01--Inf
#> [1] 13104
#> 
#> Cities:
#>   city_code pref_name city_desig_name city_desig_name_kana city_name
#> 1     13104    東京都            <NA>                 <NA>    新宿区
#>   city_name_kana
#> 1   しんじゅくく

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.