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）

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

plot(mtcars$disp,mtcars$wt)

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

type = "l" #线
type = "p" #点
type = "b" #点线

 5）lty : 线条的类型

plot(mtcars$disp,mtcars$wt,type = "l",col = "blue",lty = 2) #lty = 2代表虚线

6）lwd : 线的粗细，默认为1

plot(mtcars$disp,mtcars$wt,type = "l",col = "blue",lty = 2,lwd = 2) 

7）main : 添加标题

plot(mtcars$disp,mtcars$wt,type = "l",col = "blue",lty = 2,lwd = 2,
     main = "disp vs mt")

8）sub : 副标题

plot(mtcars$disp,mtcars$wt,type = "l",col = "blue",lty = 2,lwd = 2,
     main = "disp vs mt",sub = "a tu3")

 9）xlab, ylab 坐标轴标签

plot(mtcars$disp,mtcars$wt,type = "l",col = "blue",lty = 2,lwd = 2,
     main = "disp vs mt",sub = "a tu3", xlab = "disp", ylab = "wt")

10）xlim, ylim : 指定坐标轴范围

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))

11) abline : 添加辅助线（直线or 斜线）

#添加辅助线
abline(h=c(3,4), v=c(150,400))  #h:横线，v:竖线 

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), col = "red", lty = 3, lwd=1.5)  #h:横线，v:竖线

 

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))

 

?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

 

#添加图例
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