Inspired by Vincent Arel-Bundock’s amazing countrycode package, we created regioncode, a package to achieve similar functions but specifically within China. regioncode aims to enable seamlessly converting regions’ formal names, common-used names, and administrative division codes between each other in modern China (1986–2019).
regioncode?The Chinese government gives unique geocodes for each county, city (prefecture), and provincial-level administrative unit. These “administrative division codes” are consistently adjusted and updated to matched national and regional plans of development. The adjustments however may disturb researchers when they conduct studies over time or merge geo-based data from different years. Especially, when researchers render statistical data on a Chinese map, different geocodes between map data and statistical data can cause mess-up outputs.
This package aims to conquer such difficulties by a one-step solution. In the current version, regioncode enables seamlessly converting formal names, common-used names, language zone, and division codes of Chinese provinces and prefectures between each other and across thirty-four years from 1986 to 2019.
To install:
install.packages("regioncode").remotes::install_github("sammo3182/regioncode").We uses a randomly drawn sample of Yuhua Wang’s China’s Corruption Investigations Dataset to illustrate how the package works. In the data, the division codes were recorded with the 2019 version, and we added prefectural abbreviations for the sake of illustration.
In regioncode package, we named administrative division codes as code, regions’ formal names as name, and their commonly used abbreviation as sname. The current version enables mutual conversion between any pair of them. To do so, users just need to pass a character vector of names or a numeric vector of geocodes into the function. In the current version, the function can produce three types of output at both the prefectural and provincial levels: codes (code), names (name) and area (area, such as 华北, 东北, 华南, etc.). One just needs to specify which type of the output they want in the argument convert_to and corresponding years of the input and output. For example, the following codes convert the 2019 geocodes in the corruption data to their 1989 version:
library(regioncode)
data("corruption")
# Original 2019 version
corruption$prefecture_id## [1] 370100 321200 310117 420500 451300 431200 350300 511500 469021 420600# 1999 version
regioncode(data_input = corruption$prefecture_id,
convert_to = "code", # default set
year_from = 2019,
year_to = 1989)## [1] 370100 329001 310227 420500 422700 452200 433000 350300 512500 460025
## [11] 420600Note that if a region was initially geocoded in e.g., 1989 and included in a new region, in 2019, the new region geocode will be used hereafter. If a big place was broken into several regions, the later-year codes will be aligned with the first region according to the ascendant order of the regions’ numeric geocodes.
By altering the output format to name, one can easily convert codes or region names of a given year to region names in another year. regioncode automatically detects the input format, so users need to specify the output format only (together with the input and output years) to gain what they want. In the following example, we convert the geocode variable in the corruption dataset to region names and the name variable to codes and names in another year.
# The original name
corruption$prefecture## [1] "<U+6D4E><U+5357><U+5E02>" "<U+6CF0><U+5DDE><U+5E02>" "<U+677E><U+6C5F><U+533A>" "<U+5B9C><U+660C><U+5E02>" "<U+6765><U+5BBE><U+5E02>" "<U+6000><U+5316><U+5E02>" "<U+8386><U+7530><U+5E02>" "<U+5B9C><U+5BBE><U+5E02>"
## [9] "<U+5B9A><U+5B89><U+53BF>" "<U+8944><U+9633><U+5E02>"# Codes to name
regioncode(data_input = corruption$prefecture_id,
convert_to = "name",
year_from = 2019,
year_to = 1989)## [1] "<U+6D4E><U+5357><U+5E02>" "<U+6CF0><U+5DDE><U+5E02>" "<U+677E><U+6C5F><U+53BF>" "<U+5B9C><U+660C><U+5E02>" "<U+5B9C><U+660C><U+5730><U+533A>" "<U+67F3><U+5DDE><U+5730><U+533A>"
## [7] "<U+6000><U+5316><U+5730><U+533A>" "<U+8386><U+7530><U+5E02>" "<U+5B9C><U+5BBE><U+5730><U+533A>" "<U+5B9A><U+5B89><U+53BF>" "<U+8944><U+6A0A><U+5E02>"# Name to codes of the same year
regioncode(data_input = corruption$prefecture,
convert_to = "code",
year_from = 2019,
year_to = 2019)## [1] 370100 321200 310117 420500 451300 431200 350300 511500 469021 420600# Name to name of a different year
regioncode(data_input = corruption$prefecture,
convert_to = "name",
year_from = 2019,
year_to = 1989)## [1] "<U+6D4E><U+5357><U+5E02>" "<U+6CF0><U+5DDE><U+5E02>" "<U+677E><U+6C5F><U+53BF>" "<U+5B9C><U+660C><U+5E02>" "<U+5B9C><U+660C><U+5730><U+533A>" "<U+67F3><U+5DDE><U+5730><U+533A>"
## [7] "<U+6000><U+5316><U+5730><U+533A>" "<U+8386><U+7530><U+5E02>" "<U+5B9C><U+5BBE><U+5730><U+533A>" "<U+5B9A><U+5B89><U+53BF>" "<U+8944><U+6A0A><U+5E02>"To further help uses with “messier” data and diverse demands, regioncode provides five special conversions: conversion from data with incomplete data, specification of municipalities, conversion sociopolitical areas and linguistic areas, and pinyin output. The current version also allows conversions at the provincial level.
More than often, data codes may omit the administrative level when recording geo-information, e.g., using “北京” instead of “北京市.” To accomplish conversions of such data, one needs to specify the incomplete_name argument. If the input data is incomplete, users should set the argument as “from”; if they want the output name (when convert_to = "name") to be without “city” or “prefecture,” they can set the argument to “to” (see the example below); and if users want to gain incomplete names for both input and output names, incomplete_name = "both". All the above conversions can be over years.
# Full, official names
corruption$prefecture## [1] "<U+6D4E><U+5357><U+5E02>" "<U+6CF0><U+5DDE><U+5E02>" "<U+677E><U+6C5F><U+533A>" "<U+5B9C><U+660C><U+5E02>" "<U+6765><U+5BBE><U+5E02>" "<U+6000><U+5316><U+5E02>" "<U+8386><U+7530><U+5E02>" "<U+5B9C><U+5BBE><U+5E02>"
## [9] "<U+5B9A><U+5B89><U+53BF>" "<U+8944><U+9633><U+5E02>"regioncode(data_input = corruption$prefecture,
convert_to = "name",
year_from = 2019,
year_to = 1989,
incomplete_name = "to")## [1] "<U+6D4E><U+5357>" "<U+6CF0><U+5DDE>" "<U+677E><U+6C5F>" "<U+5B9C><U+660C>" "<U+67F3><U+5DDE>" "<U+6765><U+5BBE>" "<U+6000><U+5316>" "<U+8386><U+7530>" "<U+5B9C><U+5BBE>" "<U+5B9A><U+5B89>"
## [11] "<U+8944><U+6A0A>" "<U+8944><U+9633>"Municipalities (“直辖市”) are geographically cities but administratively provincial. The districts within these municipalities are thus prefectural. Different analyses treat these districts differently: some parallel the districts aligned with other prefectures, while the others treat the entire municipality as one prefecture. To deal with the latter situation, regioncode sets an argument zhixiashi. When the argument is set TRUE, the municipalities are treated as whole prefectures, and their provincial codes are used as the geocodes.
Due to social, political, and martial reasons, Chinese regions are divided into seven regions:
| region | provincial-level administrative unit |
|---|---|
| 华北 | 北京市, 天津市, 山西省, 河北省, 内蒙古自治区 |
| 东北 | 黑龙江省, 吉林省, 辽宁省 |
| 华东 | 上海市, 江苏省, 浙江省, 安徽省, 福建省, 台湾省, 江西省, 山东省 |
| 华中 | 河南省, 湖北省, 湖南省 |
| 华南 | 广东省, 海南省, 广西壮族自治区, 香港特别行政区, 澳门特别行政区 |
| 西南 | 重庆市, 四川省, 贵州省, 云南省, 西藏自治区 |
| 西北 | 陕西省, 甘肃省, 青海省, 宁夏回族自治区, 新疆维吾尔自治区 |
regioncode also offers a method “area” to convert codes and names of the region into such areas.
regioncode(data_input = corruption$prefecture,
year_from = 2019,
year_to = 1989,
convert_to="area")## [1] "<U+534E><U+4E1C>" "<U+534E><U+4E1C>" "<U+534E><U+4E1C>" "<U+534E><U+4E2D>" "<U+534E><U+5357>" "<U+534E><U+4E2D>" "<U+534E><U+4E1C>" "<U+897F><U+5357>" "<U+534E><U+5357>" "<U+534E><U+4E2D>"China is a multilingual country with a variety of dialects. These dialects may be used by several prefectures in a province or province. Prefectures from different provinces may also share the same dialect.
regioncode allows users to gain linguistic zones the prefectures belong as an output. Users can gain two levels of linguistic zones, dialect groups and dialect sub-groups by setting the argument to_pinyin to dia_group or dia_sub_group. Note that, the linguistic distribution in China is too complex for precisely gauging at the prefectural level. The linguistic zone output from regioncode is thus at most for reference rather than rigorous linguistic research.
regioncode(data_input = corruption$prefecture,
year_from = 2019,
year_to = 1989,
to_dialect = "dia_group")## [1] "<U+5180><U+9C81><U+5B98><U+8BDD>" "<U+6C5F><U+6DEE><U+5B98><U+8BDD>" "<U+5434><U+8BED>" "<U+897F><U+5357><U+5B98><U+8BDD>" "<U+897F><U+5357><U+5B98><U+8BDD>" "<U+6E58><U+8BED>"
## [7] "<U+8386><U+4ED9><U+533A>" "<U+897F><U+5357><U+5B98><U+8BDD>" "<U+743C><U+6587><U+533A>" "<U+897F><U+5357><U+5B98><U+8BDD>"regioncode(data_input = corruption$prefecture,
year_from = 2019,
year_to = 1989,
to_dialect = "dia_sub_group")## [1] "<U+6CA7><U+60E0><U+7247>-1" "<U+77F3><U+6D4E><U+7247>-8" "<U+6CF0><U+5982><U+7247>-1" "<U+592A><U+6E56><U+7247>-1" "<U+6210><U+6E1D><U+7247>-3" "<U+6210><U+6E1D><U+7247>-9"
## [7] "<U+6842><U+67F3><U+7247>-10" "<U+5C91><U+6C5F><U+7247>-2" "<U+5409><U+6E86><U+7247>-3" "<U+5A04><U+90B5><U+7247>-1" "<U+9ED4><U+5317><U+7247>-3" "<U+957F><U+76CA><U+7247>-3"
## [13] "<U+8386><U+4ED9><U+533A>-4" "<U+704C><U+8D64><U+7247>-10" "<U+5E9C><U+57CE><U+7247>-1" "<U+9102><U+5317><U+7247>-10"Pinyin is a Chinese phonetic romanization. Some data stores the region names with pinyin instead of Chinese characters. The default name output of regioncode uses Chinese characters, but one can gain pinyin output by setting the argument to_pinyin = TRUE. The effect can be applied to either official name, incomplete name, or sociopolitical area outputs.
regioncode(data_input = corruption$prefecture,
year_from = 2019,
year_to = 1989,
convert_to="name",
to_pinyin=TRUE
)## <U+6D4E><U+5357><U+5E02> <U+6CF0><U+5DDE><U+5E02> <U+677E><U+6C5F><U+53BF> <U+5B9C><U+660C><U+5E02>
## "ji_nan_shi" "tai_zhou_shi" "song_jiang_xian" "yi_chang_shi"
## <U+5B9C><U+660C><U+5730><U+533A> <U+67F3><U+5DDE><U+5730><U+533A> <U+6000><U+5316><U+5730><U+533A> <U+8386><U+7530><U+5E02>
## "yi_chang_di_qu" "liu_zhou_di_qu" "huai_hua_di_qu" "pu_tian_shi"
## <U+5B9C><U+5BBE><U+5730><U+533A> <U+5B9A><U+5B89><U+53BF> <U+8944><U+6A0A><U+5E02>
## "yi_bin_di_qu" "ding_an_xian" "xiang_fan_shi"regioncode(data_input = corruption$prefecture,
year_from = 2019,
year_to = 1989,
convert_to="name",
incomplete_name = "to",
to_pinyin=TRUE
)## <U+6D4E><U+5357> <U+6CF0><U+5DDE> <U+677E><U+6C5F> <U+5B9C><U+660C> <U+67F3><U+5DDE> <U+6765><U+5BBE>
## "ji_nan" "tai_zhou" "song_jiang" "yi_chang" "liu_zhou" "lai_bin"
## <U+6000><U+5316> <U+8386><U+7530> <U+5B9C><U+5BBE> <U+5B9A><U+5B89> <U+8944><U+6A0A> <U+8944><U+9633>
## "huai_hua" "pu_tian" "yi_bin" "ding_an" "xiang_fan" "xiang_yang"regioncode(data_input = corruption$prefecture,
year_from = 2019,
year_to = 1989,
convert_to="area",
to_pinyin=TRUE
)## <U+534E><U+4E1C> <U+534E><U+4E1C> <U+534E><U+4E1C> <U+534E><U+4E2D> <U+534E><U+5357> <U+534E><U+4E2D>
## "hua_dong" "hua_dong" "hua_dong" "hua_zhong" "hua_nan" "hua_zhong"
## <U+534E><U+4E1C> <U+897F><U+5357> <U+534E><U+5357> <U+534E><U+4E2D>
## "hua_dong" "xi_nan" "hua_nan" "hua_zhong"regioncode allows conversions at not only the prefectural but provincial level. By setting the argument province = TRUE, users can accomplish all the code, name, and area conversions at the provincial level. (Note that, at the provincial level, the linguistic conversion can be only to dialect group.) Moreover, since provinces have fixed abbreviations, regioncode allows names not only being, e.g., “宁夏” instead of “宁夏回族自治区” but also “宁”. When the inputs are abbreviations, users can set the convert_to argument to abbreTocode, abbreToname, or abbreToarea. When they want provincial abbreviation outputs, just set convert_to = "abbre".
regioncode(data_input = corruption$province_id,
convert_to = "codeToabbre",
year_from = 2019,
year_to = 1989,
province = TRUE)## [1] "<U+9C81>" "<U+82CF>" "<U+6CAA>" "<U+9102>" "<U+6842>" "<U+6E58>" "<U+95FD>" "<U+8700>" "<U+743C>" "<U+9102>"regioncode provides a convenient way to convert Chinese administrative division codes, official names, sociopolitical and linguistic areas, abbreviations, and so on between each other. This vignette offers a quick view of package features and a short tutorial for users.
The development of the package is ongoing. Future versions aim to add more administrative level choices, from province level to county level. Data are also enriching. Welcome to join us if you are also interested (see the affiliations below). Please contact us with any questions or comments. Bug reports can be conducted by Github Issues.
Also thanks ZHU Meng and LIU Xueyan for helping writing the ‘Advanced Application’ section of this vignette.
Dr. Yue Hu
Department of Political Science,
Tsinghua University,
Email: yuehu@tsinghua.edu.cn
Website: https://sammo3182.github.io
Wenquan Wu
Department of Political Science,
Tsinghua University,
Email: wuwq20@mails.tsinghua.edu.cn