R語(yǔ)言列表和數(shù)據(jù)框的具體使用

更新時(shí)間：2022年01月11日 09:38:17 作者：ZDDWLIG

本文主要介紹了R語(yǔ)言列表和數(shù)據(jù)框的具體使用，文中通過(guò)示例代碼介紹的非常詳細(xì)，具有一定的參考價(jià)值，感興趣的小伙伴們可以參考一下

1.列表

列表“list”是一種比較的特別的對(duì)象集合，不同的序號(hào)對(duì)于不同的元素，當(dāng)然元素的也可以是不同類型的，那么我們用R語(yǔ)言先簡(jiǎn)單來(lái)構(gòu)造一個(gè)列表。

1.1創(chuàng)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 訪問(wèn)

1.2.1 下標(biāo)訪問(wèn)

> 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 名稱訪問(wèn)

> 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 符號(hào)訪問(wèn)

> 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

一個(gè)中括號(hào)和兩個(gè)中括號(hào)的區(qū)別

一個(gè)中括號(hào)輸出的是列表的一個(gè)子列表，兩個(gè)中括號(hào)輸出的是列表的元素

> class(mlist[1])
[1] "list"
> class(mlist[[1]])
[1] "integer"

我們添加元素時(shí)要注意用兩個(gè)中括號(hào)

2.數(shù)據(jù)框

數(shù)據(jù)框是R種的一個(gè)數(shù)據(jù)結(jié)構(gòu)，他通常是矩陣形式的數(shù)據(jù)，但矩陣各列可以是不同類型的，數(shù)據(jù)框每列是一個(gè)變量，沒(méi)行是一個(gè)觀測(cè)值。

但是，數(shù)據(jù)框又是一種特殊的列表對(duì)象，其class屬性為“data.frame”，各列表成員必須是向量（數(shù)值型、字符型、邏輯型）、因子、數(shù)值型矩陣、列表或者其它數(shù)據(jù)框。向量、因子成員為數(shù)據(jù)框提供一個(gè)變量，如果向量非數(shù)值型會(huì)被強(qiáng)型轉(zhuǎn)換為因子。而矩陣、列表、數(shù)據(jù)框等必須和數(shù)據(jù)框具有相同的行數(shù)。

2.1 創(chuàng)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 訪問(wèn)

2.2.1 下標(biāo)訪問(wèn)

> 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 名稱訪問(wèn)

> 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 符號(hào)訪問(wèn)

> 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 函數(shù)訪問(wèn)

> attach(state)
The following objects are masked from package:datasets:

2.2.4 函數(shù)訪問(wèn)

> 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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