连线图
> a=c(2,3,4,5,6) > b=c(4,7,8,9,12) > plot(a,b,type="l")
多条曲线效果
plot(rain$Tokyo,type="l",col="red",ylim=c(0,300), main="Monthly Rainfall in major cities", xlab="Month of Year", ylab="Rainfall(mm)", lwd=2) lines(rain$NewYork,type="l",col="blue",lwd=2) lines(rain$London,type="l",col="green",lwd=2) lines(rain$Berlin,type="l",col="orange",lwd=2)
（数据集没找着_(:з」∠)_）
密度图
> plot(density(rnorm(1000)))
R内置数据集
> data()#列出内置数据
Data sets in package ‘datasets’:
AirPassengers Monthly Airline Passenger Numbers 1949-1960
BJsales Sales Data with Leading Indicator
BJsales.lead (BJsales)
Sales Data with Leading Indicator
BOD Biochemical Oxygen Demand
CO2 Carbon Dioxide Uptake in Grass Plants
ChickWeight Weight versus age of chicks on different diets
DNase Elisa assay of DNase
EuStockMarkets Daily Closing Prices of Major European Stock
Indices, 1991-1998
Formaldehyde Determination of Formaldehyde
HairEyeColor Hair and Eye Color of Statistics Students
Harman23.cor Harman Example 2.3
Harman74.cor Harman Example 7.4
Indometh Pharmacokinetics of Indomethacin..........................略过略过～
热力图
> 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
>
> heatmap(as.matrix(mtcars),
+ Rowv=NA,
+ Colv=NA,
+ col=heat.colors(256),
+ scale="column",
+ margins=c(2,8),
+ main="Car characteristics by Model")
>
Iris（鸢尾花）数据集参数：
Sepal花萼
Petal花瓣
Species种属
> head(iris) Sepal.Length Sepal.Width Petal.Length Petal.Width Species 1 5.1 3.5 1.4 0.2 setosa 2 4.9 3.0 1.4 0.2 setosa 3 4.7 3.2 1.3 0.2 setosa 4 4.6 3.1 1.5 0.2 setosa 5 5.0 3.6 1.4 0.2 setosa 6 5.4 3.9 1.7 0.4 setosa
向日葵散点图
> sunflowerplot(iris[,3:4],col="gold",seg.col="gold")
散点图集
遍历样本中全部的变量配对画出二元图
直观地了解所有变量之间的关系
> pairs(iris[,1:4])
用plot也可以实现同样的效果
> plot(iris[,1:4], + main="Relationships between characteristics of iris flowers", + pch=19, + col="blue", + cex=0.9) >
散点图集
利用par()在同一个device输出多个散点图
par命令博大精深，用于设置绘图参数
> par(mfrow=c(3,1)) > plot(iris[,1],iris[,2]);plot(iris[,2],iris[,3]);plot(iris[,3],iris[,1])
关于绘图颜色
> colors()#颜色查询 [1] "white" "aliceblue" "antiquewhite" [4] "antiquewhite1" "antiquewhite2" "antiquewhite3" [7] "antiquewhite4" "aquamarine" "aquamarine1" [10] "aquamarine2" "aquamarine3" "aquamarine4" [13] "azure" "azure1" "azure2" [16] "azure3" "azure4" "beige" [19] "bisque" "bisque1" "bisque2" [22] "bisque3" "bisque4" "black" ..................................................哔～...................................... >dev.new()#建立新的图形框 >dev.list()#窗口列表 >dev.cur()#当前窗口 >dev.next()#下个窗口
三维散点图
> library(scatterplot3d) > scatterplot3d(iris[2:4])
三维作图
> x<-y<-seq(-2*pi,2*pi,pi/15) > f<-function(x,y)sin(x)*sin(y) > z<-outer(x,y,f) > contour(x,y,z,col="blue") > persp(x,y,z,theta=30,phi=30,expand=0.7,col="lightblue")
地图
> library(maps)
> map("state",interior=FALSE)
> map("state",boundary=FALSE,col="red",add=TRUE)
> map("world",fill=TRUE,col=heat.colors(10))