No.12 数据可视化01
主要内容:
plot函数
1.数据——mtcars(R 内置数据集)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | mtcars结果:> mtcars 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 |
2.plot
1 | plot (mtcars$disp,mtcars$wt) |
1 | plot (mtcars$disp,mtcars$wt,pch = 16) |
2.1 点图参数:
1)pch : 点的形状
2)cex : 点的缩放比例
cex = 1.5 #默认值的1.5倍大
3)col : 颜色
2.2 线图参数
4)type :类型
1 2 3 | type = "l" #线 type = "p" #点 type = "b" #点线 |
5)lty : 线条的类型
1 | plot (mtcars$disp,mtcars$wt,type = "l" ,col = "blue" ,<strong>lty = 2</strong>) #<strong>lty = 2</strong>代表虚线 |
6)lwd : 线的粗细,默认为1
1 | plot (mtcars$disp,mtcars$wt,type = "l" ,col = "blue" ,lty = 2,<strong>lwd = 2</strong>) |
7)main : 添加标题
1 2 | plot (mtcars$disp,mtcars$wt,type = "l" ,col = "blue" ,lty = 2,lwd = 2, <strong>main = "disp vs mt" </strong>) |
8)sub : 副标题
1 2 | plot (mtcars$disp,mtcars$wt,type = "l" ,col = "blue" ,lty = 2,lwd = 2, main = "disp vs mt" ,<strong>sub = "a tu3" </strong>) |
9)xlab, ylab 坐标轴标签
1 2 | plot (mtcars$disp,mtcars$wt,type = "l" ,col = "blue" ,lty = 2,lwd = 2, main = "disp vs mt" ,sub = "a tu3" , <strong>xlab = "disp" , ylab = "wt" </strong>) |
10)xlim, ylim : 指定坐标轴范围
1 2 3 | plot (mtcars$disp,mtcars$wt,type = "l" ,col = "blue" ,lty = 2,lwd = 2, main = "disp vs mt" ,sub = "a tu3" , xlab = "disp" , ylab = "wt" , <strong>xlim = c (100,400),ylim = c (2,5)</strong>) |
11) abline : 添加辅助线(直线or 斜线)
1 2 | #添加辅助线 <strong> abline (h= c (3,4), v= c (150,400)) #h:横线,v:竖线</strong> |
1 2 3 4 5 6 | plot (mtcars$disp,mtcars$wt,type = "l" ,col = "blue" ,lty = 2,lwd = 2, main = "disp vs mt" ,sub = "a tu3" , xlab = "disp" , ylab = "wt" , xlim = c (100,400),ylim = c (2,5)) #添加辅助线 abline (h= c (3,4), v= c (150,400), <strong>col = "red" , lty = 3, lwd=1.5)</strong> #h:横线,v:竖线 |
1 2 3 4 5 6 7 | mtcars <- mtcars[ order (mtcars$disp),] plot (mtcars$disp,mtcars$wt,type = "l" ,col = "blue" ,lty = 2,lwd = 2, main = "disp vs mt" ,sub = "a tu3" , xlab = "disp" , ylab = "wt" , xlim = c (100,400),ylim = c (2,5)) #添加回归线,用lm() 函数,先y值,再x值,中间用“~”链接。 abline ( lm (mtcars$wt~mtcars$disp)) |
1 2 3 4 5 6 7 8 9 10 11 12 | ?mtcars #提取子集 #提取vs列值等于0的所有数据 m0 <- subset (mtcars,vs==0) #提取vs列值等于1的所有数据 m1 <- subset (mtcars,vs==1) #画出vs列值等于0和1的mt列和disp列的关系图 plot (m0$disp,m0$wt,pch=16,col= "blue" , xlim = range (mtcars$disp), ylim = range (mtcars$wt)) #不能再用plot(m1$disp,m1$wt,pch=17,col="green"),会覆盖上面的,用points() points (m1$disp,m1$wt,pch=17,col= "green" ) |
12)legend : 添加图例
1 2 3 4 5 | <strong> #添加图例</strong> legend ( "bottomright" , title = "class of vs" , legend = c ( "V-shaped" , "straight" ), col = c ( "blue" , "green" ), pch = c (16,17)) #点的类型 |
13)par() #全局修改图的参数
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