基于R语言for循环的替换方案

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R语言中，for循环运行比较慢

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									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：

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									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:

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									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

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									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

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									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

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									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~

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									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="")