0. 問題導入

有時候我們會碰到這樣一種情況，那就是空間圖非常華麗叛本，但很難定量地描述信息沪蓬。于是，我們可能想著另附一副統(tǒng)計圖說明問題来候。但是跷叉，強迫癥爆發(fā)的時刻又特別想在左下角空白處填上統(tǒng)計子圖，難搞哦（圖1）营搅？然后云挟，問題來了。转质。园欣。如何在空間圖中繪制統(tǒng)計子圖？今天這篇文章給出解決方案～
繪圖所用packages 附于文末

圖1

1. 數(shù)據(jù)準備

main plot data (SSP(共享社會經(jīng)濟路徑數(shù)據(jù)) 2010 GDP)

2. 數(shù)據(jù)預處理

#1. import data
setwd('...input path...')
pl_df_m = read.csv('test.csv',header = T)
pl_df_m = pl_df_m[,-1]
pl_df_m = as.data.frame(pl_df_m)

pl_df_m$cuts = cut(pl_df_m$value, breaks = c(0,0.5,1,2,3,4,5,6,7,8,9,10,Inf))

3. 劃分區(qū)域分別統(tǒng)計GDP各區(qū)間大小出現(xiàn)的頻率

注：實際操作過程中可以通過各大洲的邊界裁剪選取數(shù)據(jù)峭拘，本例重點不在此俊庇，故采用經(jīng)緯度范圍進行分區(qū)統(tǒng)計

  section1 = which(pl_df_m$long<(-100) & pl_df_m$long >=(-180))
  section2 = which(pl_df_m$long<(0) & pl_df_m$long >=(-100))
  section3 = which(pl_df_m$long<(100) & pl_df_m$long >=(0))
  section4 = which(pl_df_m$long >=(100))
  
 
  len_stat <- function(x){
   sec1 = length(which(pl_df_m[section1,]$class ==x))
   sec2 = length(which(pl_df_m[section2,]$class ==x))
   sec3 = length(which(pl_df_m[section3,]$class ==x))
   sec4 = length(which(pl_df_m[section4,]$class ==x))
   return(c(sec1,sec2,sec3,sec4))
  }
  x = 1:12
  s_trial = sapply(x,len_stat)
  class_in_order = unique(as.character(cut(seq(0.2,11,0.5),breaks = c(0,0.5,1,2,3,4,5,6,7,8,9,10,Inf))))
  # 完成子圖統(tǒng)計數(shù)據(jù)表構建 
  pl_stat_df = data.frame(
    section = rep(c('S1','S2','S3','S4'),
                  each = 12),
    class = factor(rep(class_in_order,4)),
    value = c(s_trial[1,],s_trial[2,],
              s_trial[3,],s_trial[4,])
  )

4. 繪制主圖

mycolor = colorRampPalette(brewer.pal(11,'Spectral'))(12)
  color_group = paste0('a',1:12)

  fontsize = 12
  
  main_plot = ggplot()+
    geom_hline(aes(yintercept = 50),linetype = 'dashed',alpha = 0.5,lwd = 0.5,color = 'black')+
    geom_hline(aes(yintercept = 0),linetype = 'dashed',alpha = 0.5,lwd = 0.5,color = 'black')+
    geom_hline(aes(yintercept = -50),linetype = 'dashed',alpha = 0.5,lwd = 0.5,color = 'black')+
    geom_vline(aes(xintercept = 0),linetype = 'dashed',alpha = 0.5,lwd = 0.5,color = 'black')+
    geom_vline(aes(xintercept = -100),linetype = 'dashed',alpha = 0.5,lwd = 0.5,color = 'black')+
    geom_vline(aes(xintercept = 100),linetype = 'dashed',alpha = 0.5,lwd = 0.5,color = 'black')+
    geom_tile(data = pl_df_m,aes(x = long,y = lat, fill = cuts))+
    theme(panel.background = element_rect(fill = 'transparent',color = 'black'),
          axis.text = element_text(face='bold',colour='black',size=fontsize,hjust=.5),
          axis.title = element_text(face='bold',colour='black',size=fontsize,hjust=.5),
          legend.position=c('bottom'),
          legend.direction = c('horizontal'))+
    scale_fill_manual(values = mycolor)+
    coord_fixed(1.3)+
    geom_hline(aes(yintercept = 0),linetype = 'dashed',alpha = 0.5,lwd = 0.5,color = 'black')+
    guides(fill=guide_legend(nrow=2))+
    xlab('Longitude')+
    ylab('Latitude')

5. 繪制子圖

inset_plot = ggplot()+
    geom_bar(data = pl_stat_df,aes(x = section, y = value, 
                                   fill= fct_inorder(class)),
             stat = 'identity',position = 'fill')+
    scale_fill_manual(values = mycolor)+
    guides(fill=guide_legend(nrow=2))+
    theme(legend.position = 'none')

6. 將子圖繪制進子圖

 integrated_plot = ggdraw()+
    draw_plot(main_plot)+
    draw_plot(inset_plot, x = 0.07, y = 0.37,
              width = 0.22, height = 0.15)

7. 圖件導出為PNG 格式

png('test3.png',
      height = 25,
      width = 25,
      units = 'cm',
      res = 1000)
  print(integrated_plot)
  dev.off()

8. 結果圖示例

如圖2所是，完成在空間圖左下角添加統(tǒng)計子圖鸡挠。

圖2

8. 總結

本次繪圖所用R-packages
注：如沒有安裝如下包的辉饱，請采用install.pacakges('package name')進行安裝

  library(ggplot2)
  library(cowplot)
  library(data.table)
  library(RColorBrewer)
  library(forcats)