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❝最近在交流群中看到一张图「voronoiTreemap」也可以称为圆形树状图，本节来介绍如何使用「voronoiTreemap」包来绘制此图;绘图过程倒也简单，下面就通过两个小例子来介绍一下，「数据及代码已经上传VIP群，加群的观众老爷请自行下载」
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参考官方文档
❝https://github.com/uRosConf/voronoiTreemap
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安装R包
devtools::install_github("uRosConf/voronoiTreemap")
These packages have more recent versions available.
It is recommended to update all of them.
Which would you like to update?
1: All
2: CRAN packages only
3: None
4: rlang (1.0.5 -> 1.0.6 ) [CRAN]
5: digest (0.6.29 -> 0.6.30) [CRAN]
6: jsonlite (1.8.0 -> 1.8.3 ) [CRAN]
7: yaml (2.3.5 -> 2.3.6 ) [CRAN]
8: cli (3.3.0 -> 3.4.1 ) [CRAN]
9: lifecycle (1.0.2 -> 1.0.3 ) [CRAN]
10: commonmark (1.8.0 -> 1.8.1 ) [CRAN]
11: crayon (1.5.1 -> 1.5.2 ) [CRAN]
12: fontawesome (0.3.0 -> 0.4.0 ) [CRAN]
13: shiny (1.7.2 -> 1.7.3 ) [CRAN]
14: stringi (1.7.6 -> 1.7.8 ) [CRAN]
15: DT (0.25 -> 0.26 ) [CRAN]
加载R包
library(voronoiTreemap)
library(tidyverse)
加载内置数据
data(ExampleGDP)
查看数据
ExampleGDP %>% as_tibble()
# A tibble: 42 × 6
h1 h2 h3 color weight codes
<fct> <fct> <fct> <chr> <dbl> <chr>
1 Total Asia China #f58321 14.8 CN
2 Total Asia Japan #f58321 5.91 JP
3 Total Asia India #f58321 2.83 IN
4 Total Asia South Korea #f58321 1.86 KR
5 Total Asia Russia #f58321 1.8 RU
6 Total Asia Indonesia #f58321 1.16 ID
7 Total Asia Turkey #f58321 0.97 TR
8 Total Asia Saudi Arabia #f58321 0.87 SA
9 Total Asia Iran #f58321 0.57 IR
参数介绍
important functions:
vt_input_from_df ... easy data input as a data frame
vt_export_json ... export to json
vt_d3 ... create an htmlwidget
vt_app ... start a shiny to create a Voronoi treemap
案例一
gdp_json <- vt_export_json(vt_input_from_df(ExampleGDP, hierachyVar0 = "h1",
hierachyVar1 = "h2", hierachyVar2 = "h3",
colorVar = "color", weightVar="weight",
labelVar = "codes"))
vt_d3(gdp_json)
案例二
自定义构建数据集
df <- data.frame(country = c("Ukraine", "Russia", "Argentina", "China", "Romania", "Other"),
prod = c(11.0, 10.6, 3.1, 2.4, 2.1, 15.3))
vor <- data.frame(h1 = 'World',
h2 = c('Europe', 'Europe', 'Americas', 'Asia',
'Europe', 'Other'),
h3 = df$country,
color = c("#009593","#009593","#CED7BA","#E4D1B3","#009593","#D35C79"),
weight = df$prod,
codes = df$country)
vt <- vt_input_from_df(vor,
hierachyVar0 = "h1",
hierachyVar1 = "h2",
hierachyVar2 = "h3",
colorVar = "color",
weightVar="weight",
labelVar = "codes")
vt_d3(vt_export_json(vt),label = T,
color_border = "#000000",
legend = TRUE, legend_title = "Continents", seed = 1,
size_border = "1px")
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