91、R语言编程基础

1、查看当前工作空间

> getwd()

[] "C:/Users/P0079482.HHDOMAIN/Documents"

>

2、查看内存中有哪些对象

> ls()

 [] "a"         "a1"        "b"         "bank"      "bank_full" "dat"

 [] "m1"        "tab"       "w"         "x"         "x1"        "x2"

>

3、把指定对象从内存中删除

> rm('a')

> ls()

 [] "a1"        "b"         "bank"      "bank_full" "dat"       "m1"

 [] "tab"       "w"         "x"         "x1"        "x2"

>

4、查看函数帮助

> help(matrix)

>

5、创建向量和矩阵

> x1=c(2,4,6,8,0)

> x2=c(1,3,5,7,9)
查看向量的长度

> length(x1)

[] 5
查看向量的类型

> mode(x1)

[] "numeric"

>

6、按行将向量排列成矩阵

> rbind(x1,x2)

[,1] [,2] [,3] [,4] [,5]

x1 2 4 6 8 0

x2 1 3 5 7 9

7、按列将向量排成矩阵

> cbind(x1,x2)

     x1 x2

[1,]  2  1

[2,]  4  3

[3,]  6  5

[4,]  8  7

[5,]  0  9

8、求向量的均值

> x=c(1:100)

> mean(x)

[] 50.5

>

9、求向量的和

> sum(x)

[] 5050

>

10、

> max(x)  求最大值

[] 100

> min(x)　　最小值

[] 1

> var(x)　　方差

[] 841.6667

> prod(x)    连乘

[] 9.332622e+157

> sd(x)      标准差

[] 29.01149

11、生成矩阵

> a1=c(1:12)

> matrix(a1,nrow=3,ncol=4)

     [,1] [,2] [,3] [,4]

[1,]    1    4    7   10

[2,]    2    5    8   11

[3,]    3    6    9   12

>

> matrix(a1,nrow=4,ncol=3)

     [,1] [,2] [,3]

[1,]    1    5    9

[2,]    2    6   10

[3,]    3    7   11

[4,]    4    8   12

> matrix(a1,nrow=4,ncol=3,byrow=T)

     [,1] [,2] [,3]

[1,]    1    2    3

[2,]    4    5    6

[3,]    7    8    9

[4,]   10    1    2

根据行生成矩阵

12、矩阵的转置

> a=matrix(1:12,nrow=3,ncol=4)

> a

     [,1] [,2] [,3] [,4]

[1,]    1    4    7   10

[2,]    2    5    8   11

[3,]    3    6    9   12

> t(a)

     [,1] [,2] [,3]

[1,]    1    2    3

[2,]    4    5    6

[3,]    7    8    9

[4,]   10   11   12

>

13、矩阵的加减

> a=b=matrix(1:12,nrow=3,ncol=4)

> a+b

     [,1] [,2] [,3] [,4]

[1,]    2    8   14   20

[2,]    4   10   16   22

[3,]    6   12   18   24

> a-b

     [,1] [,2] [,3] [,4]

[1,]    0    0    0    0

[2,]    0    0    0    0

[3,]    0    0    0    0

>

14、矩阵乘法

> a=matrix(1:12,nrow=3,ncol=4)

> b=matrix(1:12,nrow=4,ncol=3)

> a%*%b

     [,1] [,2] [,3]

[1,]   70  158  246

[2,]   80  184  288

[3,]   90  210  330

>

15、矩阵求对角元素

> a=matrix(1:16,nrow=4,ncol=4)

> a

     [,1] [,2] [,3] [,4]

[1,]    1    5    9   13

[2,]    2    6   10   14

[3,]    3    7   11   15

[4,]    4    8   12   16

> diag(a)

[]  1  6 11 16

> diag(diag(a))

     [,1] [,2] [,3] [,4]

[1,]    1    0    0    0

[2,]    0    6    0    0

[3,]    0    0   11    0

[4,]    0    0    0   16

> diag(4)

     [,1] [,2] [,3] [,4]

[1,]    1    0    0    0

[2,]    0    1    0    0

[3,]    0    0    1    0

[4,]    0    0    0    1

>

16、生成随机矩阵

> a=matrix(rnorm(16),4,4)

> a

           [,1]         [,2]        [,3]       [,4]

[1,]  0.2353978 -1.168817665 -0.03914636 -0.4350940

[2,]  0.5550182 -0.001076645 -1.92283070  1.1007430

[3,]  0.2582714 -0.846160178  0.94940298 -0.6125362

[4,] -2.1307575 -2.478207744 -0.44198013 -0.2581712

>

17、矩阵求逆

> solve(a)

           [,1]       [,2]       [,3]       [,4]

[1,]  0.2524842  0.3182516  0.5172485 -0.2958290

[2,]  0.4128992 -0.5045100 -1.1071800 -0.2200014

[3,] -1.7116774  0.4246262  1.9141867  0.1535275

[4,] -3.1169442  1.4892720  3.0819024  0.4171374

>

18、基本的数据结构，数据框

> x1=c(10,13,45,26,23,12,24,78,23,43,31,56)

> x2=c(20,65,32,32,27,87,60,13,42,51,77,35)

> x=data.frame(x1,x2)

> x

   x1 x2

1  10 20

2  13 65

3  45 32

4  26 32

5  23 27

6  12 87

7  24 60

8  78 13

9  23 42

10 43 51

11 31 77

12 56 35

>

> (x=data.frame('weight'=x1,'cost'=x2))

   weight cost

1      10   20

2      13   65

3      45   32

4      26   32

5      23   27

6      12   87

7      24   60

8      78   13

9      23   42

10     43   51

11     31   77

12     56   35

>

19、读取文本文件、

> (x=data.frame('weight'=x1,'cost'=x2))

   weight cost

1      10   20

2      13   65

3      45   32

4      26   32

5      23   27

6      12   87

7      24   60

8      78   13

9      23   42

10     43   51

11     31   77

12     56   35

> (x=read.table("abc.txt"))

    V1 V2

1  175 67

2  183 75

3  165 56

4  145 45

5  178 67

6  187 90

7  156 43

8  176 58

9  173 60

10 170 56

20、读取excell文件

> w<-read.table("test.prn",header = T)

> w

  X.. X...1

1   A     2

2   B     3

3   C     5

4   D     5

>

21、用readxl包读excell

> library(readxl)

> dat<-read_excel("test.xlsx")

> dat

# A tibble: 4 x 2

  `商品` `价格`

   <chr>  <dbl>

1      A      2

2      B      3

3      C      5

4      D      5

>

巴特西

91、R语言编程基础

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