使用 hchinamap / highcharter 绘制交互式中国地图及中国各省地图

DataCharm

发布于 2021-02-22 15:20:47

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发布于 2021-02-22 15:20:47

文章被收录于专栏：数据学术商业新闻数据学术商业新闻

背景：我在 CRAN 上提交了几个 R 包，都是很简单的绘图包，后来觉得没什么意思便不再维护了。长期以来收到了不少使用者的反馈（issues），都是英语的，也懒得看。。。昨天给他们都回复了下（用中文回复的哈哈哈，让他们自己翻译吧哈哈）

hchinamap：快速绘制中国及各个省的地图

该包绘制的地图精度较低，如果你需要学习绘制高精度的中国地图，欢迎加入我的线上培训班获取：欢迎加入 RStata 线上培训班学习使用 R 语言和 Stata 进行数据处理和可视化

中国省级地图	中国市级地图

你可以从 CRAN 上安装这个包：https://cran.r-project.org/web/packages/hchinamap/

install.packages('hchinamap')

使用起来非常简单，首先加载我提供的示例数据：

dir <- tempdir()
download.file('https://mdniceczx.oss-cn-beijing.aliyuncs.com/chinadf.rda', file.path(dir, 'chinadf.rda'))
load(file.path(dir, 'chinadf.rda'), verbose = TRUE)
chinadf

#> # A tibble: 527 x 3
#>    region name   value
#>    <chr>  <chr>  <dbl>
#>  1 China  北京      44
#>  2 China  天津      28
#>  3 China  河北       3
#>  4 China  山西      65
#>  5 China  内蒙古    18
#>  6 China  辽宁      46
#>  7 China  吉林      67
#>  8 China  黑龙江    80
#>  9 China  上海       8
#> 10 China  江苏      50
#> # … with 517 more rows

绘制中国地图：

library(hchinamap)
china <- chinadf %>% 
  dplyr::filter(region == "China")
hchinamap(name = china$name, value = china$value,
          width = "100%", height = "400px",
          title = "中国地图", region = "China")

还可以绘制各个省级行政单位的：

anhui <- chinadf %>%
  dplyr::filter(region == "Anhui")
hchinamap(name = anhui$name, value = anhui$value,
          width = "100%", height = "500px",
          title = "安徽地图", region = "Anhui")

另外你还可以在 Shiny Apps 里面使用：

dir <- system.file("examples", "hchinamap", package = "hchinamap")
setwd(dir)
shiny::shinyAppDir(".")

使用这个 App 你可以探索各个参数的功能。

关于该包的更多使用方法可以参考：https://cran.r-project.org/web/packages/hchinamap/vignettes/hchinamap.html （原谅我百度翻译的英语文档。。。）

我虽然在 hchinamap 函数里面设置了超过 20 个参数，但是依然不能满足所有人的需要，所以我不再建议大家使用 hchinamap 绘制中国及各个省的地图了。highcharter 可以完成该包提供的所有的功能的！

使用 highcharter 绘制同样的中国及各个省的地图

虽然代码多了点，但是自定义的程度很高！

library(highcharter)
library(jsonlite)
library(tidyverse)
readLines("https://data.jianshukeji.com/jsonp?filename=geochina/china.json", warn = F) %>% 
  str_match(string = ., pattern = "\\((.*)\\)") -> text

load("https://mdniceczx.oss-cn-beijing.aliyuncs.com/chinadf.rda", verbose = TRUE)
china <- chinadf %>%
  dplyr::filter(region == "China") %>% 
  select(-region)

china

fromJSON(text[1, 2], simplifyVector = FALSE) -> cn

highchart(type = "map") %>% 
  hc_add_series_map(map = cn,
                    df = china, 
                    joinBy = "name", 
                    value = "value", 
                    name = "随机数据：",
                    borderWidth = 0.5,
                    borderColor = "gray",
                    states = list(hover = list(color = '#bada55')),
                    dataLabels = list(enabled = FALSE),
                    marginBottom = "200px") %>% 
  hc_title(text = "使用 highcharter 绘制中国地图") %>% 
  hc_subtitle(text = "数据来源：随机数据 | 绘制：<a src='https://tidyfriday.cn'>TidyFriday</a>",
              useHTML = TRUE) %>% 
  hc_tooltip(headerFormat = "",
             pointFormat = "<b>{point.name}</b><br>随机数据：{point.value}",
             borderRadius = 5) %>% 
  hc_colorAxis(dataClasses = JS('
      [{to: 1, color: "#ffffcc", name: "无"}, 
      {from: 1, to: 20, color: "#d9f0a3"}, 
      {from: 20, to: 40, color: "#addd8e"}, 
      {from: 40, to: 60, color: "#78c679"}, 
      {from: 60, to: 80, color: "#31a354"}, 
      {from: 80, color: "#006837"}]')) %>% 
  hc_legend(align = 'left',
            layout = 'vertical',
            valueDecimals = 0,
            floating = TRUE,
            symbolRadius = 0,
            x = 20, y = -20,
            symbolHeight = 14, 
            backgroundColor = JS("(Highcharts.theme && Highcharts.theme.legendBackgroundColor) || 'rgba(255, 255, 255, 0.85)'"),
            title = list(text = "随机数据")) %>% 
  hc_add_theme(hc_theme_google()) %>% 
  hc_exporting(enabled = TRUE) %>% 
  hc_credits(enabled = TRUE) %>% 
  hc_mapNavigation(enabled = TRUE)

绘制省份地图的方法类似，例如绘制广东省的：

chinadf %>%
  dplyr::filter(region == "Guangdong") %>% 
  select(-region) -> gd

gd

readLines("https://data.jianshukeji.com/jsonp?filename=geochina/guangdong.json", warn = F) %>% 
  str_match(string = ., pattern = "\\((.*)\\)") -> text
fromJSON(text[1, 2], simplifyVector = FALSE) -> gdmap

highchart(type = "map") %>% 
  hc_add_series_map(map = gdmap,
                    df = gd, 
                    joinBy = "name", 
                    value = "value", 
                    name = "随机数据：",
                    borderWidth = 0.5,
                    borderColor = "gray",
                    states = list(hover = list(color = '#bada55')),
                    dataLabels = list(enabled = FALSE),
                    marginBottom = "200px") %>% 
  hc_title(text = "使用 highcharter 绘制广东地图") %>% 
  hc_subtitle(text = "数据来源：随机数据 | 绘制：<a src='https://tidyfriday.cn'>TidyFriday</a>",
              useHTML = TRUE) %>% 
  hc_tooltip(headerFormat = "",
             pointFormat = "<b>{point.name}</b><br>随机数据：{point.value}",
             borderRadius = 5) %>% 
  hc_colorAxis(dataClasses = JS('
      [{to: 1, color: "#ffffcc", name: "无"}, 
      {from: 1, to: 20, color: "#d9f0a3"}, 
      {from: 20, to: 40, color: "#addd8e"}, 
      {from: 40, to: 60, color: "#78c679"}, 
      {from: 60, to: 80, color: "#31a354"}, 
      {from: 80, color: "#006837"}]')) %>% 
  hc_legend(align = 'right',
            layout = 'vertical',
            valueDecimals = 0,
            floating = TRUE,
            symbolRadius = 0,
            x = -20, y = -20,
            symbolHeight = 14, 
            backgroundColor = JS("(Highcharts.theme && Highcharts.theme.legendBackgroundColor) || 'rgba(255, 255, 255, 0.85)'"),
            title = list(text = "随机数据")) %>% 
  hc_add_theme(hc_theme_google()) %>% 
  hc_exporting(enabled = TRUE) %>% 
  hc_credits(enabled = TRUE) %>% 
  hc_mapNavigation(enabled = TRUE)