01
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图形组合布局
par(mfrow=c(2,2))
par(mfrow=c(2,2))，可以理解将绘图区域分割为2x2的矩阵区域，另可参照《R语言实战》3.5图形的组合
代码语言：javascript复制##################par(mfrow=c(2,2))####################attach(iris)opar <- par(no.readonly = TRUE)# data(iris)# head(iris)# > head(iris)# Sepal.Length Sepal.Width Petal.Length Petal.Width Species# 1 5.1 3.5 1.4 0.2 setosa# 2 4.9 3.0 1.4 0.2 setosa# 3 4.7 3.2 1.3 0.2 setosa# 4 4.6 3.1 1.5 0.2 setosa# 5 5.0 3.6 1.4 0.2 setosa# 6 5.4 3.9 1.7 0.4 setosa
par(mfrow=c(2,2)) # 设置2x2的布局plot(Sepal.Length,Sepal.Width, main = "第一张图")boxplot(Sepal.Length, horizontal = TRUE, main = "第二张图") boxplot(Sepal.Width, main = "第三张图") hist(Petal.Length, main = "第四张图")
par(opar)detach(iris)
02
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图形组合布局
par(fig=c(x1, x2, y1, y2), new = TRUE)
par(fig=c(x1, x2, y1, y2), new = TRUE)，取x1,x2,y1,y2四条线圈住的位置绘图图形，另可参照《R语言实战》3.5图形的组合
opar <- par(no.readonly = TRUE)# data(iris)# head(iris)# > head(iris)# Sepal.Length Sepal.Width Petal.Length Petal.Width Species# 1 5.1 3.5 1.4 0.2 setosa# 2 4.9 3.0 1.4 0.2 setosa# 3 4.7 3.2 1.3 0.2 setosa# 4 4.6 3.1 1.5 0.2 setosa# 5 5.0 3.6 1.4 0.2 setosa# 6 5.4 3.9 1.7 0.4 setosa
par(fig=c(0,0.8,0,0.8)) # 设置散点图的布局参数plot(iris$Sepal.Length,iris$Sepal.Width) #绘制散点图
par(fig=c(0,0.8,0.65,1),new = TRUE) #设置上方箱型图的布局参数boxplot(iris$Sepal.Length, horizontal = TRUE, axes=FALSE) # 绘制上方箱型图
par(fig=c(0.65,1,0,0.8),new = TRUE) #设置右侧箱型图的布局参数boxplot(iris$Sepal.Width, axes=FALSE) # 绘制右侧箱型图
mtext("par(fig=c(x1, x2, y1, y2), new = TRUE)",side = 3, outer=TRUE, line=-3)par(opar)
03
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图形组合布局
grid.layout & vplayout
代码语言：javascript复制library(grid)grid.newpage() ##新建页面pushViewport(viewport(layout = grid.layout(2,2))) #将页面分成2*2矩阵vplayout <- function(x,y){ viewport(layout.pos.row = x, layout.pos.col = y)}
print(p1, vp = vplayout(1,1)) #（1,1)的位置画图1print(p2, vp = vplayout(1,2)) #(1,2)的位置画图2print(p3, vp = vplayout(2,1:2)) #（2,:)的位置画图示例
代码语言：javascript复制library(ggplot2)
#绘制基本ggplot图base <- ggplot(mpg, aes(displ, hwy)) geom_point()p1 <- base geom_smooth() labs(title="图1") #如图1
#用% %调整映射关系中的数据base <- ggplot(mpg, aes(displ, hwy)) geom_point()# To override the data, you must use % % #也即覆盖原始数据必须通过% %p2 <- base % % subset(mpg, fl == "p") labs(title="图2") #图2
#第二种调整数据的方法list# Alternatively, you can add multiple components with a list.# This can be useful to return from a function.p3 <- base list(subset(mpg, fl == "p"), geom_smooth(), labs(title="图3")) #图3
###########一页多图########library(grid)grid.newpage() ##新建页面pushViewport(viewport(layout = grid.layout(2,2))) #将页面分成2*2矩阵vplayout <- function(x,y){ viewport(layout.pos.row = x, layout.pos.col = y)}
print(p1, vp = vplayout(1,1)) #（1,1)的位置画图1print(p2, vp = vplayout(1,2)) #(1,2)的位置画图2print(p3, vp = vplayout(2,1:2)) #（2,:)的位置画图
04
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图形组合布局
plot_grid {cowplot}
代码语言：javascript复制install.packages("cowplot") #安装cowplot包library(cowplot) # 加载?plot_grid #帮助函数查看具体usage示例
代码语言：javascript复制library(ggplot2)
df <- data.frame( x = 1:10, y1 = 1:10, y2 = (1:10)^2, y3 = (1:10)^3, y4 = (1:10)^4)
p1 <- ggplot(df, aes(x, y1)) geom_point()p2 <- ggplot(df, aes(x, y2)) geom_point()p3 <- ggplot(df, aes(x, y3)) geom_point()p4 <- ggplot(df, aes(x, y4)) geom_point()p5 <- ggplot(mpg, aes(as.factor(year), hwy)) geom_boxplot() facet_wrap(~class, scales = "free_y")# simple gridplot_grid(p1, p2, p3, p4)
05
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图形组合布局
multiplot{Rmisc}
代码语言：javascript复制############################# multiplot{Rmisc} ##################################library(Rmisc)library(ggplot2)
df <- data.frame( x = 1:10, y1 = 1:10, y2 = (1:10)^2, y3 = (1:10)^3, y4 = (1:10)^4)
p1 <- ggplot(df, aes(x, y1)) geom_point()p2 <- ggplot(df, aes(x, y2)) geom_point()p3 <- ggplot(df, aes(x, y3)) geom_point()p4 <- ggplot(df, aes(x, y4)) geom_point()p5 <- ggplot(mpg, aes(as.factor(year), hwy)) geom_boxplot() facet_wrap(~class, scales = "free_y")
multiplot(p1, p2, p3, p5, cols=2)
