我想创建一个包含9个饼图(3x3)的网格,每个图表根据其大小进行缩放。使用
我还发现了一个类似的问题(Pie charts in ggplot2 with variable pie sizes),它使用了
所以,以下是我的样本代码:
这是
这就是调整rel_widths的效果:
总之,我需要的是两者的混合物:在网格中缩放的饼图。
ggplot2
和cowplot
我能够创建我所需的内容,但我无法进行缩放。我是忽略了某个函数还是应该使用其他软件包?我还尝试了gridExtra包的grid.arrange和ggplot的facet_grid
函数,但两者都没有产生我要找的结果。我还发现了一个类似的问题(Pie charts in ggplot2 with variable pie sizes),它使用了
facet_grid
。不幸的是,在我的情况下,这并不起作用,因为我不是将两个变量与所有可能的结果进行比较。所以,以下是我的样本代码:
#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?
这是
plot_grid
生成的内容:
不带缩放的饼图
使用rel_widths
参数,我只能调整比例,但无法保持3x3的网格。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]))
这就是调整rel_widths的效果:
![没有网格的缩放饼图](https://istack.dev59.com/2zOyX.webp)
sizes
。已经为您的情况进行了更正,现在应该可以按预期工作了。 - J. Ring