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regioncode: Convert Region Names and Division Codes of China Over Years |
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14 July 2021 |
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paper.bib |
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The Chinese government gives unique geocodes for each county, city (prefecture), and provincial-level administrative unit. The so-called “administrative division codes” were consistently adjusted to matched national and regional plans of development. Geocode adjustments disturb researchers when they merge data with different versions of geocodes or region names. Especially, when researchers render statistical data on a Chinese map, different geocodes between map data and statistical data may cause mess-up data output or visualization.
The package is developed to conquer such difficulties to match regional data across years more conveniently and correctly. Inspired by Vincent Arel-Bundock’s well-known countrycode [@Arel-Bundock2018], we created regioncode to achieve similar functions specifically for China studies. regioncode enables seamlessly converting formal names, common-used names, and division codes of Chinese prefecture regions between each other and across thirty-four years from 1986 to 2019.
In the current version, we provide three basic functions 2code, 2name, and 2sname to convert formal names, common-used names, and division codes between each other. We also provide some useful features: incompleteName, which completes incomplete parameters; 2area, which converts region codes and names of the region into the municipal area that they belong to; topinyin, which convert the names or areas into the form of pinyin; and todialect, which offers a function to convert the name of prefecture from any year to language(local dialect) zone.
regioncode function accept numeric and character vectors as the input division codes and region names respectively. To achieve an accurate conversion, users have to specify the year of the source data correctly in the argument year_from. Then they can set the year they want the output is. That’s it. See the following example to convert the 2019-version codes to the 1999 version:
# load toy data and package
library(regioncode)
library(dplyr)
corruption <- sample_n(na.exclude(corruption), 10)
# original geocodes. It's 2019 version
corruption$prefecture_id
[1] 430100 371700 530100 640300 431100 621100 330400 360400 441500 421000
# after conversion. It's 1999 version
regioncode(data_input = corruption$prefecture_id,
year_from = 2019,
year_to = 1999)
[1] 430100 372900 530100 640300 431100 622400 330400 360400 441500 421000In some cases, the original data may only have division codes or region names, but users need the other form or both formats of data. In such cases, regioncode offers a function to convert division codes from any year to region names in any year. Users only need to alter the converting method, for example, to “2name” in order to convert division codes to region names.
regioncode(data_input = corruption$prefecture_id,
year_from = 2019,
year_to = 1999,
method = "2name")
[1] "长沙市" "菏泽地区" "昆明市" "吴忠市" "永州市" "定西地区"
[7] "嘉兴市" "九江市" "汕尾市" "荆州市"Similarly, one can get the code from names, or in a less-often case get the names in a different year from the names from a given year. Users need to change the method argument to “2code” or “2name” to achieve these conversions.
corruption$prefecture
[1] "长沙市" "菏泽市" "昆明市" "吴忠市" "永州市" "定西市" "嘉兴市" "九江市"
[9] "汕尾市" "荆州市"
regioncode(data_input = corruption$prefecture,
year_from = 2019,
year_to = 1999,
method = "2code")
[1] 430100 372900 530100 640300 431100 622400 330400 360400 441500 421000
regioncode(data_input = corruption$prefecture,
year_from = 2019,
year_to = 1999,
method = "2name")
[1] "长沙市" "菏泽地区" "昆明市" "吴忠市" "永州市" "定西地区"
[7] "嘉兴市" "九江市" "汕尾市" "荆州市"regioncode provides two advanced functions to achieve more complicated conversions. One of the occasions occurs when the data source includes only common-used short names of the cities instead of the full, official ones. regioncode can still accomplish the conversion in this case when the users specify the incompleteName to from. (regioncode can also produce short names from inputs of full or short names and division code. See the details of the help file for more information.)
# Full, official names
corruption$prefecture
[1] "长沙市" "菏泽市" "昆明市" "吴忠市" "永州市" "定西市" "嘉兴市" "九江市"
[9] "汕尾市" "荆州市"
# Incomplete names
corruption$prefecture_sname <- gsub('.{1}$', '', corruption$prefecture)
corruption$prefecture_sname
[1] "长沙" "菏泽" "昆明" "吴忠" "永州" "定西" "嘉兴" "九江" "汕尾" "荆州"
# Converting
regioncode(data_input = corruption$prefecture_sname,
year_from = 2019,
year_to = 1999,
method = "2code",
incompleteName = "from")
[1] 430100 372900 530100 640300 431100 622400 330400 360400 441500 421000Another advanced application involves the case when the municipalities directly under the central government (“zhixiashi” in Chinese Pinyin). This is common for national survey data. regioncode can fit this case with no problem as long as the user sets the argument zhixiashi as TRUE.
# In the sample data, the division code of municipalities were coded as NA. Filling the codes of municipalities with their provinces' codes.
code_zhixiashi <- c("110000", "120000", "310000", "400000")
corruption <- corruption %>%
mutate(prefecture_id = ifelse(province_id %in% code_zhixiashi, province_id, prefecture_id))
## Converting
regioncode(data_input = corruption$prefecture_id,
year_from = 2019,
year_to = 1999,
zhixiashi = TRUE)
[1] 430100 372900 530100 640300 431100 622400 330400 360400 441500 421000regioncode also offers a method "2area" to convert codes and names of the region into the municipal area that they belong to.
regioncode(data_input = corruption$prefecture,
year_from = 2019,
year_to = 1999,
province = F,
method="2area")
[1] "华中" "华东" "西南" "西北" "华中" "西北" "华东" "华东" "华南" "华中"regioncode offers a parameter "topinyin" to convert the names or areas into the form of pinyin. The default of topinyin is set as FALSE, and only when the output form is character that the converting process will begin.
regioncode(data_input = corruption$prefecture,
year_from = 2019,
year_to = 1999,
province = F,
method="2area",
topinyin=FALSE
)
[1] 华中 华东 西南 西北 华中 西北
"hua_zhong" "hua_dong" "xi_nan" "xi_bei" "hua_zhong" "xi_bei"
华东 华东 华南 华中
[7]"hua_dong" "hua_dong" "hua_nan" "hua_zhong"regioncode also offers a function to convert name of prefecture from any year to language zone.
Users need to change the todialect argument to "dia_group" or "dia_sub_group" to achieve these transformations.
Similarly, one can get the language zone from the province name.
As long as the user sets the argument province as TRUE and changes the todialect argument to "dia_super".
regioncode(data_input = corruption$prefecture,
year_from = 2019,
year_to = 1999,
province = F,
todialect = "dia_group")
[1] "湘语" "中原官话" "西南官话" "兰银官话" "西南官话" "中原官话"
[7] "吴语" "赣语" "闽南区" "西南官话"We acknowledge contributions from Meng Zhu, Yuyang Shi, Yujia Xu, and Yuxin Pan, Haiting Tian, Weihang Shao, and Yuanqian Chen.