标签：swift 大于 下标 cti data row 相同 false div
1、R中用来存储数据的结构：标量、向量、数组、数据框、列表。
2、R中可以处理的数据类型：数值、字符、逻辑、复数、原生（字节）。
3、向量：
# a <- c(1,2,3,5,8,11,19)
# b <- c("Python","go","R","C#","Ruby","swift")
> a <- c(1,2,3,5,8,11,19) > a[3] [1] 3 > a[c(1,2,3,6)] [1] 1 2 3 11 > a[c(3:6)] [1] 3 5 8 11
4、矩阵
矩阵是一个二维数组，每个元素都有相同的模式
通过matrix创建数组，并可用下标访问，举例如下：
> test01matrix=matrix(1:20,nrow=4,ncol=5)
> test01matrix
[,1] [,2] [,3] [,4] [,5]
[1,] 1 5 9 13 17
[2,] 2 6 10 14 18
[3,] 3 7 11 15 19
[4,] 4 8 12 16 20
> test01matrix[2,]
[1] 2 6 10 14 18
> test01matrix[3,]
[1] 3 7 11 15 19
> test01matrix[,3]
[1] 9 10 11 12
> test01matrix[2,3]
[1] 10
> test01matrix[2,c(2,3)]
[1] 6 10
>
>
> cells <- c(1,2,3,5,8,11)
> rnames <- c("R1","R2","R3")
> cnames <- c("C1","C2")
> test02matrix=matrix(cells,nrow=3,ncol=2,byrow=TRUE,dimnames=list(rnames,cnames))
> test02matrix
C1 C2
R1 1 2
R2 3 5
R3 8 11
> test02matrix=matrix(cells,nrow=3,ncol=2,byrow=FALSE,dimnames=list(rnames,cnames))
> test02matrix
C1 C2
R1 1 5
R2 2 8
R3 3 11
5、数组
数组是维度可以大于2的矩阵，通过array创建，举个栗子
> dim1 <- c("A1","A2")
> dim2 <- c("B1","B2","B3")
> dim3 <- c("C1","C2","C3","C4")
> test03array <- array(1:24,c(2,3,4),dimnames=list(dim1,dim2,dim3))
> test03array
, , C1
B1 B2 B3
A1 1 3 5
A2 2 4 6
, , C2
B1 B2 B3
A1 7 9 11
A2 8 10 12
, , C3
B1 B2 B3
A1 13 15 17
A2 14 16 18
, , C4
B1 B2 B3
A1 19 21 23
A2 20 22 24
6、数据框
数据框可包含不同模式的数据。可通过data.frame()创建。
每一列数据的模式必须一致
> ID <- c(1,2,3,4)
> age <- c(25,26,28,58)
> diabetes <- c("T1","T2","T1","T1")
> status <- c("good","none","none","poor")
> patientdata <- data.frame(ID,age,diabetes,status)
> patientdata
ID age diabetes status
1 1 25 T1 good
2 2 26 T2 none
3 3 28 T1 none
4 4 58 T1 poor
> patientdata[1:2]
ID age
1 1 25
2 2 26
3 3 28
4 4 58
> patientdata[c("diabetes","status")]
diabetes status
1 T1 good
2 T2 none
3 T1 none
4 T1 poor
> patientdata$age
[1] 25 26 28 58
> table(patientdata$ID,patientdata$status)
good none poor
1 1 0 0
2 0 1 0
3 0 1 0
4 0 0 1
函数attach()用来将数据框添加到路径中，detach()用来退出路径
函数with()也可达到同样的效果
标签：swift 大于 下标 cti data row 相同 false div
原文地址：http://www.cnblogs.com/matplot/p/7119150.html
