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R语言中,for循环运行比较慢
for(i in 1:1000){print(i^2)}
补充:R语言:for循环使用小结
基本结构展示:
vals =c(5,6,7)for(v in vals){ print(v)}#即把大括号里的内容对vals里的每一个值都循环run一遍
实例展示:
1. paste() 命令是把几个字符连接起来
如paste("A","B","C",sep=" ")得到的就是“A B C”,在次基础上写如下for loop:
partnumber = c(1,2,5,78)for(i in partnumber){ print(paste("participant number",i, sep = " ")) }#就可以得到一串参与者号码,根据上面给定的几个值, 从"participant number 1" 到"participant number 8"
2. 双重loop
partnumber = c(1,2,5,78)institution =c("cancer center", "RMH", "Florey")for(i in partnumber){ for(j in institution){ print(paste("participant number",i,", institution",j,sep = " "))}}# 先对j循环,后对i循环,得到如下结果[1] "participant number 1 , institution cancer center"[1] "participant number 1 , institution RMH"[1] "participant number 1 , institution Florey"[1] "participant number 2 , institution cancer center"[1] "participant number 2 , institution RMH"[1] "participant number 2 , institution Florey"[1] "participant number 5 , institution cancer center"[1] "participant number 5 , institution RMH"[1] "participant number 5 , institution Florey"[1] "participant number 78 , institution cancer center"[1] "participant number 78 , institution RMH"[1] "participant number 78 , institution Florey"# 两个loop的话,output得放最中心的loop里面,如果只要要第一层loop,就放在靠外一层括号里面,第二层括号就保留最后的一个值
3. 数据库实例演示
Titanic=read.csv("https://goo.gl/4Gqsnz") #从网络读取数据<0.2, 0.2-0.6还是>0.6。
目的:看不同舱位(Pclass)和不同性别(Sex)的人的生存率是
A<- sort(unique(Pclass)) #sort可以把类别按大小顺序排,unique()命令是把分类变量的种类提取出来B<- sort(unique(Sex))for(i in A){ for(j in B){ if(mean(Survived[Pclass==i&Sex==j])<0.2){ print(paste("for class",i,"sex",j,"mean survival is less than 0.2")) } else if (mean(Survived[Pclass==i&Sex==j])>0.6){ print(paste("for class",i,"sex",j,"mean survival is more than 0.6")) } else { print(paste("for class",i,"sex",j,"mean survival is between 0.2 and 0.6"))} } }
结果如下:
[1] "for class 1 sex female mean survival is more than 0.6"
[1] "for class 1 sex male mean survival is between 0.2 and 0.6"
[1] "for class 2 sex female mean survival is more than 0.6"
[1] "for class 2 sex male mean survival is less than 0.2"
[1] "for class 3 sex female mean survival is between 0.2 and 0.6"
[1] "for class 3 sex male mean survival is less than 0.2"
补充:R语言for循环批量生成变量,并且赋值
看代码~
rm(list=ls())data <- read.table("MS_identified_information.txt",header = T,sep = "\t",quote="",na.strings = "",row.names = 1,comment.char = "")name1 <- paste("H1299",sep = "_",c(1:3))name2 <- paste("Metf",sep = "_",c(1:3))name3 <- paste("OEMetf",sep = "_",c(1:3))name <- data.frame(name1,name2,name3)mean.data=data.frame(row.names(data))for (i in 1:3){ tmp <- subset(data,select = as.vector.factor(name[,i])) #筛选特定的样本 mean_ <- as.data.frame(apply(tmp, 1, mean)) #行求平均值 //assign()功能就是对变量进行赋值如i=1时,df1=mean_ //把三次结果组合起来 mean.data <- cbind.data.frame(mean.data,assign(paste("df", i, sep=""), mean_)) //这里没有体现出变量,实际上生成了df1,df2,df3结果}colnames(mean.data) <- c("ID","H1299","Metf","OEMetf")write.table(mean.data,file="MS_mean.xls",row.names = FALSE,sep = "\t",na="")
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