使用ggplot2根據R中的大小按比例縮放多個餅圖

Question

我想創建一個包含9個餅圖（3x3）的網格，每個圖表根據其大小進行縮放。 使用ggplot2和cowplot我能夠創建我正在尋找的東西，但我無法進行縮放。 我只是忽略了一個函數，還是應該使用另一個包？ 我也嘗試了gridExtra包和ggplot的facet_grid函數的grid.arrange，但都沒有產生我在找的東西。

我還發現了一個類似的問題（Pie charts in ggplot2 with variable pie sizes），它使用了facet_grid。 不幸的是，這不適用於我的情況，因爲我沒有比較所有可能結果的兩個變量。

所以這是我的示例代碼：

#sample data 
x <- data.frame(c("group01", "group01", "group02", "group02", "group03", "group03", 
        "group04", "group04", "group05", "group05", "group06", "group06", 
        "group07", "group07", "group08", "group08", "group09", "group09"), 
       c("w","m"), 
       c(8,8,6,10,26,19,27,85,113,70,161,159,127,197,179,170,1042,1230), 
       c(1,1,1,1,3,3,7,7,11,11,20,20,20,20,22,22,142,142)) 
colnames(x) <- c("group", "sex", "data", "scale") 
#I have divided the group size by the smallest group (group01, 16 people) in order to receive the scaling-variable. 
#Please note that I doubled the values here for simplicity-reasons for both men and women per group (for plot-scaling only one value is needed that I calculate 
#seperately in the original data in the plot-scaling part underneath). 
#In this example I am also going to use the scaling-variable as indicator of the sequence of the plots. 

library(ggplot2) 
library(cowplot) 

#Then I create 9 pie-charts, each one containing one group and showing the quantity of men vs. women in a very simplistic style 
#(only the name of the group showing; color of each sex is explained seperately in the according text) 
p1 <- ggplot(x[c(1,2),], aes("", y = data, fill = factor(sex), x$scale[1]))+ 
    geom_bar(width = 4, stat="identity") + coord_polar("y", start = 0, direction = 1)+ 
    ggtitle(label=x$group[1])+ 
    theme_classic()+theme(legend.position = "none")+ 
    theme(axis.title=element_blank(),axis.line=element_blank(),axis.ticks=element_blank(),axis.text=element_blank(),plot.background = element_blank(), 
     plot.title=element_text(color="black",size=10,face="plain",hjust=0.5)) 
p2 <- ggplot(x[c(3,4),], aes("", y = data, fill = factor(sex), x$scale[3]))+ 
    geom_bar(width = 4, stat="identity") + coord_polar("y", start = 0, direction = 1)+ 
    ggtitle(label=x$group[3])+ 
    theme_classic()+theme(legend.position = "none")+ 
    theme(axis.title=element_blank(),axis.line=element_blank(),axis.ticks=element_blank(),axis.text=element_blank(),plot.background = element_blank(), 
     plot.title=element_text(color="black",size=10,face="plain",hjust=0.5)) 
p3 <- ggplot(x[c(5,6),], aes("", y = data, fill = factor(sex), x$scale[5]))+ 
    geom_bar(width = 4, stat="identity") + coord_polar("y", start = 0, direction = 1)+ 
    ggtitle(label=x$group[5])+ 
    theme_classic()+theme(legend.position = "none")+ 
    theme(axis.title=element_blank(),axis.line=element_blank(),axis.ticks=element_blank(),axis.text=element_blank(),plot.background = element_blank(), 
     plot.title=element_text(color="black",size=10,face="plain",hjust=0.5)) 
p4 <- ggplot(x[c(7,8),], aes("", y = data, fill = factor(sex), x$scale[7]))+ 
    geom_bar(width = 4, stat="identity") + coord_polar("y", start = 0, direction = 1)+ 
    ggtitle(label=x$group[7])+ 
    theme_classic()+theme(legend.position = "none")+ 
    theme(axis.title=element_blank(),axis.line=element_blank(),axis.ticks=element_blank(),axis.text=element_blank(),plot.background = element_blank(), 
     plot.title=element_text(color="black",size=10,face="plain",hjust=0.5)) 
p5 <- ggplot(x[c(9,10),], aes("", y = data, fill = factor(sex), x$scale[9]))+ 
    geom_bar(width = 4, stat="identity") + coord_polar("y", start = 0, direction = 1)+ 
    ggtitle(label=x$group[9])+ 
    theme_classic()+theme(legend.position = "none")+ 
    theme(axis.title=element_blank(),axis.line=element_blank(),axis.ticks=element_blank(),axis.text=element_blank(),plot.background = element_blank(), 
     plot.title=element_text(color="black",size=10,face="plain",hjust=0.5)) 
p6 <- ggplot(x[c(11,12),], aes("", y = data, fill = factor(sex), x$scale[11]))+ 
    geom_bar(width = 4, stat="identity") + coord_polar("y", start = 0, direction = 1)+ 
    ggtitle(label=x$group[11])+ 
    theme_classic()+theme(legend.position = "none")+ 
    theme(axis.title=element_blank(),axis.line=element_blank(),axis.ticks=element_blank(),axis.text=element_blank(),plot.background = element_blank(), 
     plot.title=element_text(color="black",size=10,face="plain",hjust=0.5)) 
p7 <- ggplot(x[c(13,14),], aes("", y = data, fill = factor(sex), x$scale[13]))+ 
    geom_bar(width = 4, stat="identity") + coord_polar("y", start = 0, direction = 1)+ 
    ggtitle(label=x$group[13])+ 
    theme_classic()+theme(legend.position = "none")+ 
    theme(axis.title=element_blank(),axis.line=element_blank(),axis.ticks=element_blank(),axis.text=element_blank(),plot.background = element_blank(), 
     plot.title=element_text(color="black",size=10,face="plain",hjust=0.5)) 
p8 <- ggplot(x[c(15,16),], aes("", y = data, fill = factor(sex), x$scale[15]))+ 
    geom_bar(width = 4, stat="identity") + coord_polar("y", start = 0, direction = 1)+ 
    ggtitle(label=x$group[15])+ 
    theme_classic()+theme(legend.position = "none")+ 
    theme(axis.title=element_blank(),axis.line=element_blank(),axis.ticks=element_blank(),axis.text=element_blank(),plot.background = element_blank(), 
     plot.title=element_text(color="black",size=10,face="plain",hjust=0.5)) 
p9 <- ggplot(x[c(17,18),], aes("", y = data, fill = factor(sex), x$scale[17]))+ 
    geom_bar(width = 4, stat="identity") + coord_polar("y", start = 0, direction = 1)+ 
    ggtitle(label=x$group[17])+ 
    theme_classic()+theme(legend.position = "none")+ 
    theme(axis.title=element_blank(),axis.line=element_blank(),axis.ticks=element_blank(),axis.text=element_blank(),plot.background = element_blank(), 
     plot.title=element_text(color="black",size=10,face="plain",hjust=0.5)) 

#Using cowplot, I create a grid that contains my plots 
plot_grid(p1,p2,p3,p4,p5,p6,p7,p8,p9, align = "h", ncol = 3, nrow = 3) 

#But now I want to scale the size of the plots according to their real group size (e.g. 
#group01 with 16 people vs. group09 with more than 2000 people) 


#In this context, ggplot's facet_grid function produces similar results of what I want to get, 
#but since it looks at the data as a whole instead of separating groups from each other, it does not show 
#complete pie charts per group 

#So is there a possibility to scale each of the 9 charts according to their group size? 

這是plot_grid生產： pie-charts without scaling

使用rel_widths說法我只能調節比例，但未能維持3×3格。

plot_grid(p1,p2,p3,p4,p5,p6,p7,p8,p9, 
      align="h",ncol=(nrow(x)/2),   
      rel_widths = c(x$scale[1], 
         x$scale[3], 
         x$scale[5], 
         x$scale[7], 
         x$scale[9], 
         x$scale[11], 
         x$scale[13], 
         x$scale[15], 
         x$scale[17])) 

這是調整rel_widths做：

總之，我需要的是兩者的混合物：縮放餅圖中的網格。

Answer 1

這是怎麼回事？

x$scale <- as.numeric(x$scale) 
x$data <- as.numeric(x$data) 
x$group <- factor(x$group, levels=levels(x$group)[order(x$scale[seq(1,nrow(x),2)])]) 

ggplot(x, aes(x=scale/2, y = data, fill = factor(sex), width=scale))+ 
    geom_bar(position="fill", stat="identity") + coord_polar("y")+ 
    facet_wrap(~ group, nrow=3) + 
    theme_classic()+theme(legend.position = "none")+ 
    theme(axis.title=element_blank(), axis.line=element_blank(), 
     axis.ticks=element_blank(), axis.text=element_blank(), 
     plot.background = element_blank(), 
     plot.title=element_text(color="black",size=10,face="plain",hjust=0.5), 
     strip.background = element_blank(), 
     strip.text.x = element_text(color = "transparent")) 

Answer 2

你走在正確的道路上。問題是您正在爲3x3輸出分配c(...)值。這裏有兩個方法可以做到：

# Option 1  
# individually for each row 
     plot_upper <- plot_grid(p1, p2, p3, labels = "", ncol = 3, rel_widths = c(1, 1.1, 1.2)) 
     plot_middle <- plot_grid(p4, p5, p6, labels = "", ncol = 3, rel_widths = c(1.3, .3, 1.3)) 
     plot_lower <- plot_grid(p7, p8, p9, labels = "", ncol = 3, rel_widths = c(1.2, 1.1, 1)) 
     plot_grid(plot_upper, plot_middle, plot_lower, ncol = 1, rel_heights = c(1, 2.5, 1.7)) 
# Option 2 
# Set size matrix 
    sizes <- matrix(c(x$scale[1], 
       x$scale[3], 
       x$scale[5], 
       x$scale[7], 
       x$scale[9], 
       x$scale[11], 
       x$scale[13], 
       x$scale[15], 
       x$scale[17]), ncol = 3) 
    plot_grid(p1,p2,p3,p4,p5,p6,p7,p8,p9, align = "h", ncol = 3, nrow = 3, rel_widths = sizes, rel_heights = sizes) 

Here是文檔的鏈接和here是一些例子。

所以，如果你調整你的比例矩陣，並將其插入選項2，你應該獲得你想要的。此外，定義您的data.frame時不需要使用...cbind(...。