从GitHub下载源码，并参照原著逐段分析
因为在markdown代码块中，被“#”注释的语句颜色偏暗，故通过简单的“＃”→“＊”字符替换，使观看效果更好，若想复制到R中并运行，请先反向替换字符。

源码分析

*------------------------------------------------------------*
* R in Action (3rd ed): Chapter 2                            *
* Creating a dataset                                         *
*------------------------------------------------------------*
*第二章-创建数据集
* Types of vectors`向量类型`
a <- c(1, 2, 5, 3, 6, -2, 4) *numeric`数值型向量`
b <- c("one", "two", "three") * character`字符型向量`
c <- c(TRUE, TRUE, TRUE, FALSE, TRUE, FALSE) * logical`逻辑型向量`

* subsetting vectors`构造子集向量(原书中文版译为访问向量中的元素)`
a <- c("k", "j", "h", "a", "c", "m")*向量创建
a[3]*访问第3个元素
a[c(1, 3, 5)]*访问第1,3,5个向量."[]"中c(1,3,5)的输出结果是"1 3 5",但不能直接用a[1,3,5]访问,否则会报错
a[2:6]*访问第2至6个元素,等价于a[c(2,3,4,5,6)]

* Listing 2.1 Creating matrices`创建矩阵`
y <- matrix(1:20, nrow = 5, ncol = 4)*用matrix()函数创建一个5x4的矩阵.其中nrow指定行数,ncol指定列数,默认按列填充
y*输出y
cells <- c(1, 26, 24, 68)*创建向量
rnames <- c("R1", "R2")
cnames <- c("C1", "C2")
mymatrix <- matrix(cells,
  nrow = 2, ncol = 2, byrow = TRUE,
  dimnames = list(rnames, cnames))*创建2x2矩阵,设置byrow=TRUE使按行填充,默认情况byrow=FALSE故按列填充.dimnames=list(r,c),"()"中r具体值对应列名标签,c具体值对应行名标签.
mymatrix
mymatrix <- matrix(cells,
  nrow = 2, ncol = 2, byrow = FALSE,
  dimnames = list(rnames, cnames))*将该矩阵设置为byrow=FAKASE使按列填充
mymatrix

* Listing 2.2 Using matrix subscripts`矩阵下标的使用`
x <- matrix(1:10, nrow = 2)*创建2xN矩阵x
x
x[2, ]*选择(访问)第2行的元素
x[, 2]*选择第2列的元素
x[1, 4]*选择第1行第4列的元素
x[1, c(4, 5)]*选择第1行第4&5个元素

* Listing 2.3 Creating an array`创建一个数组`
dim1 <- c("A1", "A2")*向量创建
dim2 <- c("B1", "B2", "B3")
dim3 <- c("C1", "C2", "C3", "C4")
z <- array(1:24, c(2, 3, 4), dimnames = list(dim1, dim2, dim3))*使用array()创建数组z.在"array()"中,1:24表示具有数字1~24;c(2,3,4)表示组成数组z的每个矩阵(即三维数组的二维"切面")应为2行3列,共4个矩阵;dimnames=list(1,2,3)使每个矩阵的行名为1,列名为2,每个矩阵的名字对应3中的字符
z

* Listing 2.4 Creating a data frame`创建一个数据框`
patientID <- c(1, 2, 3, 4)
age <- c(25, 34, 28, 52)
diabetes <- c("Type1", "Type2", "Type1", "Type1")
status <- c("Poor", "Improved", "Excellent", "Poor")
patientdata <- data.frame(patientID, age, diabetes, status)*用data.frame()创建数据框patientdata,使"()"中的4个向量组成该数据框的4个列.列向量之间可以是不同类型.
patientdata

* Listing 2.5 Specifying elements of a data frame`选取数据框中的元素`
patientdata[1:2]*选取第1&2列
patientdata$age*选取数据框patientdata中的age变量
patientdata["age"]*选取数据框中的age列*该行是源码分析者自主新增,原书无
patientdata[c("diabetes", "status")]*选取数据框中的diabetes和status列

* Listing 2.6 Using factors`因子的使用`
*本节已被增改,下面是被if(FALSE){...}语句"沉默"的源代码块,R默认不支持多行注释,因此无法使用"***"等方式进行多行注释
if(FALSE){
patientID <- c(1, 2, 3, 4)
age <- c(25, 34, 28, 52)
diabetes <- c("Type1", "Type2", "Type1", "Type1")
status <- c("Poor", "Improved", "Excellent", "Poor")
diabetes <- factor(diabetes)
status <- factor(status, order = TRUE)
patientdata <- data.frame(patientID, age, diabetes, status)
str(patientdata)
summary(patientdata)
}
*下面使源码加print()进行逐行输出,便于查看
print(patientID <- c(1,2,3,4))*以向量形式输入数据
print(age <- c(25,34,28,52))
print(diabetes <- c("Type1","Type2","Type1","Type1"))
print(status <- c("Poor","Improved","Excellent","Poor"))
print(diabetes <- factor(diabetes))*用factor()函数,将diabetes指定为普通因子
print(status <- factor(status))*先将status指定为普通因子*自主新增行,原书无
print(status <- factor(status,order=TRUE))*设置order=TRUE,最后将status指定为有序因子
print(patientdata <- data.frame(patientID,age,diabetes,status))*将()中的数据合并为数据框
print(str(patientdata))*显示对象的结构
print(summary(patientdata))*显示对象的统计概要

* Listing 2.7 Creating a list`创建一个列表`
g <- "My First List"
h <- c(25, 26, 18, 39)
j <- matrix(1:10, nrow = 5)
k <- c("one", "two", "three")
mylist <- list(title = g, ages = h, j, k)*用list()函数创建列表mylist,用g作为第1个成分并命名为title,依次放入第2~4个成分
mylist
mylist[[2]]*选取第2个成分
mylist[["ages"]]*选取被命名为ages的成分,即第2个成分

输出结果

> *------------------------------------------------------------*
> * R in Action (3rd ed): Chapter 2                            *
> * Creating a datas .... [TRUNCATED] 

> b <- c("one", "two", "three") * character`字符型向量`

> c <- c(TRUE, TRUE, TRUE, FALSE, TRUE, FALSE) * logical`逻辑型向量`

> * subsetting vectors`构造子集向量(原书中文版译为访问向量中的元素)`
> a <- c("k", "j", "h", "a", "c", "m")*向量创建

> a[3]*访问第3个元素
[1] "h"

> a[c(1, 3, 5)]*访问第1,3,5个向量."[]"中c(1,3,5)的输出结果是"1 3 5",但不能直接用a[1,3,5]访问,否则会报错
[1] "k" "h" "c"

> a[2:6]*访问第2至6个元素,等价于a[c(2,3,4,5,6)]
[1] "j" "h" "a" "c" "m"

> * Listing 2.1 Creating matrices`创建矩阵`
> y <- matrix(1:20, nrow = 5, ncol = 4)*用matrix()函数创建一个5x4的矩阵.其中nrow指定行数,ncol指定列数,默认按列填充

> y*输出y
     [,1] [,2] [,3] [,4]
[1,]    1    6   11   16
[2,]    2    7   12   17
[3,]    3    8   13   18
[4,]    4    9   14   19
[5,]    5   10   15   20

> cells <- c(1, 26, 24, 68)*创建向量

> rnames <- c("R1", "R2")

> cnames <- c("C1", "C2")

> mymatrix <- matrix(cells,
+   nrow = 2, ncol = 2, byrow = TRUE,
+   dimnames = list(rnames, cnames))*创建2x2矩阵,设置byrow=TRUE使按行填充,默认情况byrow=FALSE故按列填充. .... [TRUNCATED] 

> mymatrix
   C1 C2
R1  1 26
R2 24 68

> mymatrix <- matrix(cells,
+   nrow = 2, ncol = 2, byrow = FALSE,
+   dimnames = list(rnames, cnames))*将该矩阵设置为byrow=FAKASE使按列填充

> mymatrix
   C1 C2
R1  1 24
R2 26 68

> * Listing 2.2 Using matrix subscripts`矩阵下标的使用`
> x <- matrix(1:10, nrow = 2)*创建2xN矩阵x

> x
     [,1] [,2] [,3] [,4] [,5]
[1,]    1    3    5    7    9
[2,]    2    4    6    8   10

> x[2, ]*选择(访问)第2行的元素
[1]  2  4  6  8 10

> x[, 2]*选择第2列的元素
[1] 3 4

> x[1, 4]*选择第1行第4列的元素
[1] 7

> x[1, c(4, 5)]*选择第1行第4&5个元素
[1] 7 9

> * Listing 2.3 Creating an array`创建一个数组`
> dim1 <- c("A1", "A2")*向量创建

> dim2 <- c("B1", "B2", "B3")

> dim3 <- c("C1", "C2", "C3", "C4")

> z <- array(1:24, c(2, 3, 4), dimnames = list(dim1, dim2, dim3))*使用array()创建数组z.在"array()"中,1:24表示具有数字1~24;c(2,3,4)表示组成数组z的每个矩阵(即三维数组的二维"切面")应为2行3列,共 .... [TRUNCATED] 

> z
, , 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


> * Listing 2.4 Creating a data frame`创建一个数据框`
> patientID <- c(1, 2, 3, 4)

> age <- c(25, 34, 28, 52)

> diabetes <- c("Type1", "Type2", "Type1", "Type1")

> status <- c("Poor", "Improved", "Excellent", "Poor")

> patientdata <- data.frame(patientID, age, diabetes, status)*用data.frame()创建数据框patientdata,使"()"中的4个向量组成该数据框的4个列.列向量之间可以是不同类型.

> patientdata
  patientID age diabetes    status
1         1  25    Type1      Poor
2         2  34    Type2  Improved
3         3  28    Type1 Excellent
4         4  52    Type1      Poor

> * Listing 2.5 Specifying elements of a data frame`选取数据框中的元素`
> patientdata[1:2]*选取第1&2列
  patientID age
1         1  25
2         2  34
3         3  28
4         4  52

> patientdata$age*选取数据框patientdata中的age变量
[1] 25 34 28 52

> patientdata["age"]*选取数据框中的age列*该行是源码分析者自主新增,原书无
  age
1  25
2  34
3  28
4  52

> patientdata[c("diabetes", "status")]*选取数据框中的diabetes和status列
  diabetes    status
1    Type1      Poor
2    Type2  Improved
3    Type1 Excellent
4    Type1      Poor

> * Listing 2.6 Using factors`因子的使用`
> ---*本节由源码分析者增改,下面是被井号单行注释的源码,R默认不支持多行注释
+ *patientID <- c(1, 2, 3, 4)
+ *age <- c(25, 34, 28, 52)
+ *diabetes < .... [TRUNCATED] 
[1] 1 2 3 4
[1] 1 2 3 4

> print(age <- c(25,34,28,52))
[1] 25 34 28 52

> print(diabetes <- c("Type1","Type2","Type1","Type1"))
[1] "Type1" "Type2" "Type1" "Type1"

> print(status <- c("Poor","Improved","Excellent","Poor"))
[1] "Poor"      "Improved"  "Excellent" "Poor"     

> print(diabetes <- factor(diabetes))*用factor()函数,将diabetes指定为普通因子
[1] Type1 Type2 Type1 Type1
Levels: Type1 Type2

> print(status <- factor(status))*先将status指定为普通因子*自主新增行,原书无
[1] Poor      Improved  Excellent Poor     
Levels: Excellent Improved Poor

> print(status <- factor(status,order=TRUE))*设置order=TRUE,最后将status指定为有序因子
[1] Poor      Improved  Excellent Poor     
Levels: Excellent < Improved < Poor

> print(patientdata <- data.frame(patientID,age,diabetes,status))*将()中的数据合并为数据框
  patientID age diabetes    status
1         1  25    Type1      Poor
2         2  34    Type2  Improved
3         3  28    Type1 Excellent
4         4  52    Type1      Poor

> print(str(patientdata))*显示对象的结构
'data.frame':   4 obs. of  4 variables:
 $ patientID: num  1 2 3 4
 $ age      : num  25 34 28 52
 $ diabetes : Factor w/ 2 levels "Type1","Type2": 1 2 1 1
 $ status   : Ord.factor w/ 3 levels "Excellent"<"Improved"<..: 3 2 1 3
NULL

> print(summary(patientdata))*显示对象的统计概要
   patientID         age         diabetes       status 
 Min.   :1.00   Min.   :25.00   Type1:3   Excellent:1  
 1st Qu.:1.75   1st Qu.:27.25   Type2:1   Improved :1  
 Median :2.50   Median :31.00             Poor     :2  
 Mean   :2.50   Mean   :34.75                          
 3rd Qu.:3.25   3rd Qu.:38.50                          
 Max.   :4.00   Max.   :52.00                          

> * Listing 2.7 Creating a list`创建一个列表`
> g <- "My First List"

> h <- c(25, 26, 18, 39)

> j <- matrix(1:10, nrow = 5)

> k <- c("one", "two", "three")

> mylist <- list(title = g, ages = h, j, k)*用list()函数创建列表mylist,用g作为第1个成分并命名为title,依次放入第2~4个成分

> mylist
$title
[1] "My First List"

$ages
[1] 25 26 18 39

[[3]]
     [,1] [,2]
[1,]    1    6
[2,]    2    7
[3,]    3    8
[4,]    4    9
[5,]    5   10

[[4]]
[1] "one"   "two"   "three"


> mylist[[2]]*选取第2个成分
[1] 25 26 18 39

> mylist[["ages"]]*选取被命名为ages的成分,即第2个成分
[1] 25 26 18 39