我想自动生成一些ggplots:
通用数据集:
mydata<-data.frame(matrix(rnorm(100),ncol=5))
names(mydata)<-c("Tijd","X1","X2","X3","X4")
指定要包含的变量:
Start=2
Stop=5
将图表保存在以下列表中:
gvec<-vector("list",length=length(Start:Stop))
创建图表:
for(i in Start:Stop){
graphy<-ggplot(mydata,aes_string(x="Tijd",y=names(mydata)[i]))+geom_point()+mytheme
gvec[[i-Start+1]]<-graphy
}
保存地块:
for(i in Start:Stop){
tiff(paste0("Test/Residu/Plots/Prei/mydata.",names(mydata)[i],"09.14.tiff"),width=720,height=720)
gvec[[i-Start+1]]
graphics.off()
}
生成图表列表;我也可以手动保存图表。但是,使用最后一个循环生成的文件都是空白的。我无法弄清楚这个的原因。
根据Roland的建议,我试过了
print(gvec[[i-Start+1]])
但我仍然得到空白文件作为输出。
答案 0 :(得分:53)
以下是在循环中创建ggplots的完全可重现的示例。
# Plot separate ggplot figures in a loop.
library(ggplot2)
# Make list of variable names to loop over.
var_list = combn(names(iris)[1:3], 2, simplify=FALSE)
# Make plots.
plot_list = list()
for (i in 1:3) {
p = ggplot(iris, aes_string(x=var_list[[i]][1], y=var_list[[i]][2])) +
geom_point(size=3, aes(colour=Species))
plot_list[[i]] = p
}
# Save plots to tiff. Makes a separate file for each plot.
for (i in 1:3) {
file_name = paste("iris_plot_", i, ".tiff", sep="")
tiff(file_name)
print(plot_list[[i]])
dev.off()
}
# Another option: create pdf where each page is a separate plot.
pdf("plots.pdf")
for (i in 1:3) {
print(plot_list[[i]])
}
dev.off()
答案 1 :(得分:11)
您还可以使用ggsave
库中的ggplot2
功能。
library(ggplot2)
data("iris")
# list of values to loop over
uniq_species = unique(iris$Species)
# Loop
for (i in uniq_species) {
temp_plot = ggplot(data= subset(iris, Species == i)) +
geom_point(size=3, aes(x=Petal.Length, y=Petal.Width )) +
ggtitle(i)
ggsave(temp_plot, file=paste0("plot_", i,".png"), width = 14, height = 10, units = "cm")
}
答案 2 :(得分:1)
您可以在同一循环中创建和导出绘图。合并后的代码为:
for(i in Start:Stop){
graphy<-ggplot(mydata,aes_string(x="Tijd",y=names(mydata)[i]))+geom_point()+mytheme
tiff(paste0("Test/Residu/Plots/Prei/mydata.",names(mydata)[i],"09.14.tiff"),width=720,height=720)
print(graphy)
dev.off()
}
对于堆叠数据的一般情况,id
变量对应于子组(国家,个人等)):
for (i in 1:10) {
mydata_id <- subset(mydata, id == i) # subselect group
p <- ggplot(mydata_id, aes(x, y)) + geom_line() # create graph
png(paste("plot_", i, ".png", sep = ""), width=600, height=500, res=120) # start export
print(p)
dev.off() # finish export
}