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)
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!
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)
其它省的方法几乎一模一样,唯一不同的就是这个地图数据的链接啦,格式是这样的:https://data.jianshukeji.com/jsonp?filename=geochina/{文件名}
其中中国和各个省的文件名分别为:
大家就可以试试自己感兴趣的省份啦!