R语言可视化（三十）：TreeMap树图绘制

bioinfomics 2020-10-25

1512

30. TreeMap树图绘制

清除当前环境中的变量

rm(list=ls())

设置工作目录

setwd("C:/Users/Dell/Desktop/R_Plots/30treemap/")

使用treemap包绘制矩形树状图

# 安装并加载所需的R包
#install.packages("treemap")
library(treemap)

# 加载并查看示例数据
data(GNI2014)
head(GNI2014)
##   iso3          country     continent population    GNI
## 3  BMU          Bermuda North America      67837 106140
## 4  NOR           Norway        Europe    4676305 103630
## 5  QAT            Qatar          Asia     833285  92200
## 6  CHE      Switzerland        Europe    7604467  88120
## 7  MAC Macao SAR, China          Asia     559846  76270
## 8  LUX       Luxembourg        Europe     491775  75990

# 使用treemap函数绘制矩形树状图
treemap(GNI2014,
        index="continent", #指定分组的列
        vSize="population", #指定面积大小的列
        vColor="GNI", #指定颜色深浅的列
        type="value", #指定颜色填充数据的类型
        format.legend = list(scientific = FALSE, big.mark = " "))

# colors indicate density (like a population density map)
treemap(GNI2014,
        index=c("continent","country"), #指定多个分组的列，先按continent分组，再按country分组
        vSize="population", #指定面积大小的列
        vColor="GNI", #指定颜色深浅的列
        type="dens")

# manual set the color palettes
treemap(GNI2014,
        index=c("continent","country"), #指定多个分组的列
        vSize="population", #指定面积大小的列
        vColor="GNI", #指定颜色深浅的列
        type="manual", #自定义颜色类型
        palette = terrain.colors(10))

treemap(GNI2014,
        index=c("continent","country"), #指定多个分组的列
        vSize="population", #指定面积大小的列
        vColor="GNI", #指定颜色深浅的列
        type = "value",
        palette = "RdYlBu", #自定义颜色画板
        #range = c(100,10000), #设置颜色的范围值
        fontsize.labels=c(12, 10), #设置标签字体大小
        align.labels=list(c("center", "center"), c("left", "top")), #设置标签对齐的方式
        border.col=c("black","red"), #设置边框的颜色  
        border.lwds=c(4,2), #设置边框的线条的宽度
        title = "My TreeMap")

使用treemapify包绘制矩形树状图

# 安装并加载所需的R包
#install.packages("treemapify")
library(treemapify)
library(ggplot2)

# 查看内置示例数据
head(G20)
##          region       country gdp_mil_usd   hdi econ_classification
## 1        Africa  South Africa      384315 0.629          Developing
## 2 North America United States    15684750 0.937            Advanced
## 3 North America        Canada     1819081 0.911            Advanced
## 4 North America        Mexico     1177116 0.775          Developing
## 5 South America        Brazil     2395968 0.730          Developing
## 6 South America     Argentina      474954 0.811          Developing
##   hemisphere
## 1   Southern
## 2   Northern
## 3   Northern
## 4   Northern
## 5   Southern
## 6   Southern

# 使用geom_treemap函数绘制矩形树状图
ggplot(G20, aes(area = gdp_mil_usd, fill = hdi)) +
  geom_treemap()

# 添加label标签，设置字体大小和类型
ggplot(G20, aes(area = gdp_mil_usd, fill = hdi, label = country)) +
  geom_treemap() +
  geom_treemap_text(fontface = "italic", colour = "white", 
                    size = 16, place = "centre")

# 添加多个分组信息
ggplot(G20, aes(area = gdp_mil_usd, fill = hdi,
                label = country,
                subgroup = region)) +
  geom_treemap() +
  geom_treemap_subgroup_border() +
  geom_treemap_subgroup_text(place = "centre", alpha = 0.5, 
                             colour = "black", fontface = "italic") +
  geom_treemap_text(colour = "white", place = "topleft", reflow = T) +
  scale_fill_gradientn(colours = c("blue","white","tomato"))

sessionInfo()
## R version 3.6.0 (2019-04-26)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 18363)
## 
## Matrix products: default
## 
## locale:
## [1] LC_COLLATE=Chinese (Simplified)_China.936 
## [2] LC_CTYPE=Chinese (Simplified)_China.936   
## [3] LC_MONETARY=Chinese (Simplified)_China.936
## [4] LC_NUMERIC=C                              
## [5] LC_TIME=Chinese (Simplified)_China.936    
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] ggplot2_3.2.0    treemapify_2.5.3 treemap_2.4-2   
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.5         compiler_3.6.0     pillar_1.4.2      
##  [4] later_0.8.0        RColorBrewer_1.1-2 tools_3.6.0       
##  [7] ggfittext_0.9.0    digest_0.6.20      lifecycle_0.2.0   
## [10] evaluate_0.14      tibble_2.1.3       gtable_0.3.0      
## [13] gridBase_0.4-7     pkgconfig_2.0.2    rlang_0.4.7       
## [16] igraph_1.2.4.1     shiny_1.3.2        yaml_2.2.0        
## [19] xfun_0.8           withr_2.1.2        stringr_1.4.0     
## [22] dplyr_1.0.2        knitr_1.23         generics_0.0.2    
## [25] vctrs_0.3.2        tidyselect_1.1.0   grid_3.6.0        
## [28] glue_1.4.2         data.table_1.12.2  R6_2.4.0          
## [31] rmarkdown_1.13     purrr_0.3.2        magrittr_1.5      
## [34] scales_1.0.0       promises_1.0.1     htmltools_0.3.6   
## [37] mime_0.7           colorspace_1.4-1   xtable_1.8-4      
## [40] httpuv_1.5.1       labeling_0.3       stringi_1.4.3     
## [43] lazyeval_0.2.2     munsell_0.5.0      crayon_1.3.4