这篇文章主要介绍了基于R语言for循环的替换方案，具有很好的参考价值，希望对大家有所帮助。一起跟随小编过来看看吧
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="") 以上就是基于R语言for循环的替换方案的详细内容，更多请关注0133技术站其它相关文章！
