| Type: | Package | 
| Title: | Utilities for Fude Polygon | 
| Version: | 0.3.7 | 
| Description: | Provides utilities to facilitate handling of Fude Polygon data downloadable from the Ministry of Agriculture, Forestry and Fisheries website https://open.fude.maff.go.jp. | 
| License: | MIT + file LICENSE | 
| URL: | https://github.com/takeshinishimura/fude, https://takeshinishimura.github.io/fude/ | 
| BugReports: | https://github.com/takeshinishimura/fude/issues | 
| Encoding: | UTF-8 | 
| LazyData: | true | 
| Depends: | R (≥ 3.5) | 
| Imports: | dplyr, DT, forcats, glue, leaflet, magrittr, purrr, rlang, sf, shiny, tidyr, units | 
| Suggests: | testthat (≥ 3.0.0) | 
| RoxygenNote: | 7.3.2 | 
| Config/testthat/edition: | 3 | 
| NeedsCompilation: | no | 
| Packaged: | 2024-12-22 05:10:53 UTC; takeshinishimura | 
| Author: | Takeshi Nishimura | 
| Maintainer: | Takeshi Nishimura <takenishi@gmail.com> | 
| Repository: | CRAN | 
| Date/Publication: | 2024-12-22 05:20:02 UTC | 
Bind multiple Fude Polygon data
Description
bind_fude() binds a list of polygon data. It also binds a list of data
combined by combine_fude().
Usage
bind_fude(...)
Arguments
| ... | Database lists to be combined. They should all have the same named elements. | 
Value
A list of sf::sf() object(s).
See Also
Examples
path <- system.file("extdata", "castle.zip", package = "fude")
d1 <- read_fude(path, stringsAsFactors = FALSE, quiet = TRUE)
d2 <- read_fude(path, stringsAsFactors = FALSE, quiet = TRUE)
bind_fude(d1, d2)
Generate Citation Text for Fude Polygon Data
Description
Generates citation text in Japanese and English for Fude Polygon Data.
Usage
cite_fude(data)
Arguments
| data | A list or data frame containing Fude Polygon data. | 
Value
A list with two elements: ja for Japanese citation text and en
for English citation text.
Examples
data <- list(fude = data.frame(issue_year = c(2021, 2020), boundary_edit_year = c(2019, 2020)))
cite_fude(data)
Combine the Fude Polygon data with the agricultural community boundary data
Description
combine_fude() uses the agricultural community boundary data to reduce the
Fude Polygon data to the community units.
Usage
combine_fude(data, boundary, city, kcity = "", community = "", year = NULL)
Arguments
| data | List of  | 
| boundary | List of one or more agricultural community boundary data provided by the MAFF. | 
| city | A local government name in Japanese to be extracted. In the case of overlapping local government names, this must contain the prefecture name in Japanese and the prefecture code in romaji (e.g., "Fuchu-shi, 13", "fuchu 13", "34 fuchu-shi", "34, FUCHU-CHO"). Alternatively, it could be a 6-digit local government code. | 
| kcity | String by regular expression. One or more former village name in Japanese to be extracted. | 
| community | String by regular expression. One or more agricultural community name in Japanese to be extracted. | 
| year | Year in the column name of the  | 
Value
A list of sf::sf() objects.
See Also
Examples
path <- system.file("extdata", "castle.zip", package = "fude")
d <- read_fude(path, stringsAsFactors = FALSE)
b <- get_boundary(d)
db <- combine_fude(d, b, "\u677e\u5c71\u5e02", "\u57ce\u6771", year = 2022)
Community code/name correspondence table
Description
A dataset containing codes/names of communities in Japan.
Usage
community_code_table
Format
A data frame with 149,511 rows and 13 variables:
- KEY
- Unique community codes 
- PREF_NAME
- Prefecture names in Kanji 
- PREF_KANA
- Prefecture names in Hiragana 
- PREF_ROMAJI
- Prefecture names in Romaji 
- CITY_NAME
- City names in Kanji 
- CITY_KANA
- City names in Hiragana 
- CITY_ROMAJI
- City names in Romaji 
- KCITY_NAME
- Former village names in Kanji 
- RCOM_NAME
- Community names in Kanji 
- RCOM_KANA
- Community names in Hiragana 
- RCOM_ROMAJI
- Community names in Romaji 
- local_government_cd
- Local government codes 
- census_year
- The year of the census from which the data is derived 
Extract specified agricultural community boundary data
Description
extract_boundary() extracts the specified data from the list returned by
get_boundary().
Usage
extract_boundary(boundary, city = "", kcity = "", community = "", all = FALSE)
Arguments
| boundary | List of one or more agricultural community boundary data provided by the MAFF. | 
| city | A local government name in Japanese to be extracted. In the case of overlapping local government names, this must contain the prefecture name in Japanese and the prefecture code in romaji (e.g., "Fuchu-shi, 13", "fuchu 13", "34 fuchu-shi", "34, FUCHU-CHO"). Alternatively, it could be a 6-digit local government code. | 
| kcity | String by regular expression. One or more former village name in Japanese to be extracted. | 
| community | String by regular expression. One or more agricultural community name in Japanese to be extracted. | 
| all | logical. | 
Value
A list of sf::sf() object(s).
See Also
Extract specified Fude Polygon data
Description
extract_fude() extracts the specified data from the list returned by
read_fude().
Usage
extract_fude(
  data,
  year = NULL,
  city = NULL,
  kcity = "",
  community = "",
  list = TRUE
)
Arguments
| data | List of  | 
| year | Years to be extracted. | 
| city | Local government names or codes to be extracted. | 
| kcity | String by regular expression. One or more former village name in Japanese to be extracted. | 
| community | String by regular expression. One or more agricultural community name in Japanese to be extracted. | 
| list | logical. If  | 
Value
A list of sf::sf() object(s).
See Also
Get the agricultural community boundary data
Description
get_boundary() downloads and reads one or more agricultural community
boundary data provided by the MAFF.
Usage
get_boundary(
  data,
  year = 2020,
  census_year = 2020,
  path = NULL,
  to_wgs84 = TRUE,
  quiet = FALSE
)
Arguments
| data | List of  | 
| year | The year when the agricultural community boundary data was created. | 
| census_year | The year of the Agricultural and Forestry Census. | 
| path | Path to the ZIP file containing the agricultural community boundary data; use a local ZIP file instead of going looking for a ZIP file. Specify a directory containing one or more ZIP files, not the ZIP file itself. | 
| to_wgs84 | logical. Convert JGD2000 to WGS 84. | 
| quiet | logical. Suppress information about the data to be read. | 
Value
A list of sf::sf() objects.
Examples
path <- system.file("extdata", "castle.zip", package = "fude")
d <- read_fude(path)
b <- get_boundary(d)
Local government code/name correspondence table
Description
A dataset containing codes/names of local governments in Japan.
Usage
lg_code_table
Format
A data frame with 1,992 rows and 6 variables:
- lg_code
- Local government codes 
- pref_kanji
- Prefecture names in Kanji 
- city_kanji
- Local government names in Kanji 
- pref_kana
- Prefecture names in Katakana 
- city_kana
- Local government names in Katakana 
- romaji
- Local government names in Romaji 
Itemize the structure of Fude Polygon data
Description
ls_fude() lists the year and the local government names (or codes) in
order to understand what is included in the list returned by read_fude().
Usage
ls_fude(data)
Arguments
| data | List of  | 
Value
A data.frame.
See Also
Prefecture code/name correspondence table
Description
A dataset containing codes/names of prefectures in Japan.
Usage
pref_code_table
Format
A data frame with 47 rows and 2 variables:
- pref_code
- Prefecture codes 
- pref_kanji
- Prefecture names in Kanji 
Read a Fude Polygon ZIP file
Description
read_fude() reads Fude Polygon data as a list. The data can be downloaded
from the MAFF website as a ZIP file, which contains one or more spatial data
files, such as GeoJSON files (.json or .geojson) and FlatGeobuf
files (.fgb). The function also works with ZIP files you created, as long
as you do not change the filenames of the original files.
Usage
read_fude(
  path = NULL,
  pref = NULL,
  year = 2024,
  census_year = 2020,
  stringsAsFactors = TRUE,
  to_wgs84 = TRUE,
  quiet = FALSE,
  supplementary = FALSE
)
Arguments
| path | Path to the ZIP file containing one or more supported spatial data files.
Supported formats include  | 
| pref | The year when the Fude Polygon data was created. | 
| year | The year when the Fude Polygon data was created. | 
| census_year | The year of the Agricultural and Forestry Census. | 
| stringsAsFactors | logical. Should character vectors be converted to factors? | 
| to_wgs84 | logical. Convert JGD2000 to WGS 84. | 
| quiet | logical. Suppress information about the data to be read. | 
| supplementary | logical. If TRUE, add supplementary information for each polygon. | 
Value
A list of sf::sf() objects.
Examples
path <- system.file("extdata", "castle.zip", package = "fude")
d <- read_fude(path, stringsAsFactors = FALSE)
Rename the Fude Polygon data
Description
rename_fude() renames the 6-digit local government code of the list
returned by read_fude() to the corresponding Japanese name in order to
make the data human-friendly.
Usage
rename_fude(data, suffix = TRUE, romaji = NULL, quiet = TRUE)
Arguments
| data | List of  | 
| suffix | logical. If  | 
| romaji | If not  
 | 
| quiet | logical. Suppress information about the data to be read. | 
Value
A list of sf::sf() objects.
See Also
Examples
path <- system.file("extdata", "castle.zip", package = "fude")
d <- read_fude(path, stringsAsFactors = FALSE, quiet = FALSE)
d2 <- rename_fude(d)
d2 <- rename_fude(d, suffix = FALSE)
d2 <- d |> rename_fude(romaji = "upper")
Prepare Leaflet Map for Fude Polygon Data
Description
Prepares a Leaflet map for Fude Polygon data.
Usage
shiny_fude(data, community = FALSE)
Arguments
| data | A list or data frame containing Fude Polygon data. | 
| community | A logical value indicating whether to overlay community data on the map. | 
Value
A Leaflet map object with Fude Polygon data with an HTML table.