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目录
1.列表
1.1创建
1.2 访问
1.2.1 下标访问
1.2.2 名称访问?
1.2.3?符号访问
?1.3 注意
2.数据框
2.1 创建
2.2 访问
2.2.1 下标访问
2.2.2 名称访问
2.2.3 符号访问
2.2.4 函数访问
1.列表
1.1创建
> a<-c(1:20)
> b<-matrix(1:20,4,5)
> mlist<-list(a,b)
> mlist
[[1]]
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14
[15] 15 16 17 18 19 20
[[2]]
[,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
1.2 访问
1.2.1 下标访问
> mlist[1]
[[1]]
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14
[15] 15 16 17 18 19 20
> mlist[2]
[[1]]
[,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
1.2.2 名称访问?
> state.center["x"]
$x
[1] -86.7509 -127.2500 -111.6250 -92.2992
[5] -119.7730 -105.5130 -72.3573 -74.9841
[9] -81.6850 -83.3736 -126.2500 -113.9300
[13] -89.3776 -86.0808 -93.3714 -98.1156
[17] -84.7674 -92.2724 -68.9801 -76.6459
[21] -71.5800 -84.6870 -94.6043 -89.8065
[25] -92.5137 -109.3200 -99.5898 -116.8510
[29] -71.3924 -74.2336 -105.9420 -75.1449
[33] -78.4686 -100.0990 -82.5963 -97.1239
[37] -120.0680 -77.4500 -71.1244 -80.5056
[41] -99.7238 -86.4560 -98.7857 -111.3300
[45] -72.5450 -78.2005 -119.7460 -80.6665
[49] -89.9941 -107.2560
1.2.3?符号访问
> state.center$x
[1] -86.7509 -127.2500 -111.6250 -92.2992
[5] -119.7730 -105.5130 -72.3573 -74.9841
[9] -81.6850 -83.3736 -126.2500 -113.9300
[13] -89.3776 -86.0808 -93.3714 -98.1156
[17] -84.7674 -92.2724 -68.9801 -76.6459
[21] -71.5800 -84.6870 -94.6043 -89.8065
[25] -92.5137 -109.3200 -99.5898 -116.8510
[29] -71.3924 -74.2336 -105.9420 -75.1449
[33] -78.4686 -100.0990 -82.5963 -97.1239
[37] -120.0680 -77.4500 -71.1244 -80.5056
[41] -99.7238 -86.4560 -98.7857 -111.3300
[45] -72.5450 -78.2005 -119.7460 -80.6665
[49] -89.9941 -107.2560
?1.3 注意
一个中括号和两个中括号的区别
一个中括号输出的是列表的一个子列表，两个中括号输出的是列表的元素
> class(mlist[1])
[1] "list"
> class(mlist[[1]])
[1] "integer"
?我们添加元素时要注意用两个中括号
2.数据框
2.1 创建
> state<-data.frame(state.name,state.abb,state.area)
> state
state.name state.abb state.area
1 Alabama AL 51609
2 Alaska AK 589757
3 Arizona AZ 113909
4 Arkansas AR 53104
5 California CA 158693
6 Colorado CO 104247
7 Connecticut CT 5009
8 Delaware DE 2057
9 Florida FL 58560
10 Georgia GA 58876
11 Hawaii HI 6450
12 Idaho ID 83557
13 Illinois IL 56400
14 Indiana IN 36291
15 Iowa IA 56290
16 Kansas KS 82264
17 Kentucky KY 40395
18 Louisiana LA 48523
19 Maine ME 33215
20 Maryland MD 10577
21 Massachusetts MA 8257
22 Michigan MI 58216
23 Minnesota MN 84068
24 Mississippi MS 47716
25 Missouri MO 69686
26 Montana MT 147138
27 Nebraska NE 77227
28 Nevada NV 110540
29 New Hampshire NH 9304
30 New Jersey NJ 7836
31 New Mexico NM 121666
32 New York NY 49576
33 North Carolina NC 52586
34 North Dakota ND 70665
35 Ohio OH 41222
36 Oklahoma OK 69919
37 Oregon OR 96981
38 Pennsylvania PA 45333
39 Rhode Island RI 1214
40 South Carolina SC 31055
41 South Dakota SD 77047
42 Tennessee TN 42244
43 Texas TX 267339
44 Utah UT 84916
45 Vermont VT 9609
46 Virginia VA 40815
47 Washington WA 68192
48 West Virginia WV 24181
49 Wisconsin WI 56154
50 Wyoming WY 97914
>
2.2 访问
2.2.1 下标访问
> state[1]
state.name
1 Alabama
2 Alaska
3 Arizona
4 Arkansas
5 California
6 Colorado
7 Connecticut
8 Delaware
9 Florida
10 Georgia
11 Hawaii
12 Idaho
13 Illinois
14 Indiana
15 Iowa
16 Kansas
17 Kentucky
18 Louisiana
19 Maine
20 Maryland
21 Massachusetts
22 Michigan
23 Minnesota
24 Mississippi
25 Missouri
26 Montana
27 Nebraska
28 Nevada
29 New Hampshire
30 New Jersey
31 New Mexico
32 New York
33 North Carolina
34 North Dakota
35 Ohio
36 Oklahoma
37 Oregon
38 Pennsylvania
39 Rhode Island
40 South Carolina
41 South Dakota
42 Tennessee
43 Texas
44 Utah
45 Vermont
46 Virginia
47 Washington
48 West Virginia
49 Wisconsin
50 Wyoming
2.2.2 名称访问
> state["state.name"]
state.name
1 Alabama
2 Alaska
3 Arizona
4 Arkansas
5 California
6 Colorado
7 Connecticut
8 Delaware
9 Florida
10 Georgia
11 Hawaii
12 Idaho
13 Illinois
14 Indiana
15 Iowa
16 Kansas
17 Kentucky
18 Louisiana
19 Maine
20 Maryland
21 Massachusetts
22 Michigan
23 Minnesota
24 Mississippi
25 Missouri
26 Montana
27 Nebraska
28 Nevada
29 New Hampshire
30 New Jersey
31 New Mexico
32 New York
33 North Carolina
34 North Dakota
35 Ohio
36 Oklahoma
37 Oregon
38 Pennsylvania
39 Rhode Island
40 South Carolina
41 South Dakota
42 Tennessee
43 Texas
44 Utah
45 Vermont
46 Virginia
47 Washington
48 West Virginia
49 Wisconsin
50 Wyoming
2.2.3 符号访问
> state$state.name
[1] "Alabama" "Alaska"
[3] "Arizona" "Arkansas"
[5] "California" "Colorado"
[7] "Connecticut" "Delaware"
[9] "Florida" "Georgia"
[11] "Hawaii" "Idaho"
[13] "Illinois" "Indiana"
[15] "Iowa" "Kansas"
[17] "Kentucky" "Louisiana"
[19] "Maine" "Maryland"
[21] "Massachusetts" "Michigan"
[23] "Minnesota" "Mississippi"
[25] "Missouri" "Montana"
[27] "Nebraska" "Nevada"
[29] "New Hampshire" "New Jersey"
[31] "New Mexico" "New York"
[33] "North Carolina" "North Dakota"
[35] "Ohio" "Oklahoma"
[37] "Oregon" "Pennsylvania"
[39] "Rhode Island" "South Carolina"
[41] "South Dakota" "Tennessee"
[43] "Texas" "Utah"
[45] "Vermont" "Virginia"
[47] "Washington" "West Virginia"
[49] "Wisconsin" "Wyoming"
2.2.4 函数访问
> attach(state)
The following objects are masked from package:datasets:
state.abb, state.area, state.name
> state.name
[1] "Alabama" "Alaska"
[3] "Arizona" "Arkansas"
[5] "California" "Colorado"
[7] "Connecticut" "Delaware"
[9] "Florida" "Georgia"
[11] "Hawaii" "Idaho"
[13] "Illinois" "Indiana"
[15] "Iowa" "Kansas"
[17] "Kentucky" "Louisiana"
[19] "Maine" "Maryland"
[21] "Massachusetts" "Michigan"
[23] "Minnesota" "Mississippi"
[25] "Missouri" "Montana"
[27] "Nebraska" "Nevada"
[29] "New Hampshire" "New Jersey"
[31] "New Mexico" "New York"
[33] "North Carolina" "North Dakota"
[35] "Ohio" "Oklahoma"
[37] "Oregon" "Pennsylvania"
[39] "Rhode Island" "South Carolina"
[41] "South Dakota" "Tennessee"
[43] "Texas" "Utah"
[45] "Vermont" "Virginia"
[47] "Washington" "West Virginia"
[49] "Wisconsin" "Wyoming"
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