列表顧名思義就是用來(lái)存儲(chǔ)很多內(nèi)容的一個(gè)集合蚁趁，在其他編程語(yǔ)言中鞠眉，列表一般和數(shù)組是等同的欣孤，但是在R中凯旋，列表卻是R中最復(fù)雜的一種數(shù)據(jù)結(jié)構(gòu)呀潭，也是非常重要的一張數(shù)據(jù)結(jié)構(gòu)
列表就是一些對(duì)象的有序集合。列表中可以存儲(chǔ)若干向量至非，矩陣钠署，數(shù)據(jù)框，甚至其他列表組合
向量荒椭，數(shù)組和矩陣都要求相同的數(shù)據(jù)類型谐鼎，但是列表不用，更適用于實(shí)際環(huán)境中
- 1.在模式上和向量類似趣惠，都是一維數(shù)據(jù)的集合
- 2.向量只能存儲(chǔ)一種數(shù)據(jù)類型狸棍，列表中的對(duì)象可以是R中的任何數(shù)據(jù)結(jié)構(gòu)，甚至是列表本身
創(chuàng)建列表
> a <- c(1:20)
> b <- matrix(1:20,4)
> c <- mtcars
> d <- "This is a test list"
> a;b;c;d
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
[,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
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
[1] "This is a test list"
> mlist <- list(a,b,c,d)
> mlist
[[1]]
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 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
[[3]]
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
[[4]]
[1] "This is a test list"
> mlist <- list(first=a,second=b,third=c,forth=d)
使用索引訪問(wèn)列表元素
> mlist[1]
$first
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
> mlist[1,4]
Error in mlist[1, 4] : 量度數(shù)目不對(duì)
> mlist[c(1,4)]
$first
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
$forth
[1] "This is a test list"
> state.center[c("x","y")]
$x
[1] -86.7509 -127.2500 -111.6250 -92.2992 -119.7730 -105.5130
[7] -72.3573 -74.9841 -81.6850 -83.3736 -126.2500 -113.9300
[13] -89.3776 -86.0808 -93.3714 -98.1156 -84.7674 -92.2724
[19] -68.9801 -76.6459 -71.5800 -84.6870 -94.6043 -89.8065
[25] -92.5137 -109.3200 -99.5898 -116.8510 -71.3924 -74.2336
[31] -105.9420 -75.1449 -78.4686 -100.0990 -82.5963 -97.1239
[37] -120.0680 -77.4500 -71.1244 -80.5056 -99.7238 -86.4560
[43] -98.7857 -111.3300 -72.5450 -78.2005 -119.7460 -80.6665
[49] -89.9941 -107.2560
$y
[1] 32.5901 49.2500 34.2192 34.7336 36.5341 38.6777 41.5928 38.6777
[9] 27.8744 32.3329 31.7500 43.5648 40.0495 40.0495 41.9358 38.4204
[17] 37.3915 30.6181 45.6226 39.2778 42.3645 43.1361 46.3943 32.6758
[25] 38.3347 46.8230 41.3356 39.1063 43.3934 39.9637 34.4764 43.1361
[33] 35.4195 47.2517 40.2210 35.5053 43.9078 40.9069 41.5928 33.6190
[41] 44.3365 35.6767 31.3897 39.1063 44.2508 37.5630 47.4231 38.4204
[49] 44.5937 43.0504
使$訪問(wèn)列表元素
> mlist$second
[,1] [,2] [,3] [,4] [,5]
[1,] 1 5 9 13 17
[2,] 2 6 10 14 18
[3,] 3 7 11 15 19
[4,] 4 8 12 16 20
> state.center$x
[1] -86.7509 -127.2500 -111.6250 -92.2992 -119.7730 -105.5130
[7] -72.3573 -74.9841 -81.6850 -83.3736 -126.2500 -113.9300
[13] -89.3776 -86.0808 -93.3714 -98.1156 -84.7674 -92.2724
[19] -68.9801 -76.6459 -71.5800 -84.6870 -94.6043 -89.8065
[25] -92.5137 -109.3200 -99.5898 -116.8510 -71.3924 -74.2336
[31] -105.9420 -75.1449 -78.4686 -100.0990 -82.5963 -97.1239
[37] -120.0680 -77.4500 -71.1244 -80.5056 -99.7238 -86.4560
[43] -98.7857 -111.3300 -72.5450 -78.2005 -119.7460 -80.6665
[49] -89.9941 -107.2560
使用[[]]訪問(wèn)列表元素
> mlist[1] #用1個(gè)中括號(hào)訪問(wèn)的是以列表的形式
$first
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
> mlist[[1]] #用2個(gè)中括號(hào)訪問(wèn)的是本身的元素
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
> class(mlist[1])
[1] "list"
> class(mlist[[1]])
[1] "integer"
> mlist[[5]] <- "iris" #給列表添加元素必須是用兩個(gè)中括號(hào)
刪除元素
- 1.直接將元素的值賦為NULL
> mlist[[5]] <- NULL
- 2使用負(fù)索引再賦值給原來(lái)的列表
