一，条形图
安装包
R
install.packages("vcd")绘制简单的条形图
R
barplot(c(1,2,4,5,6,3))
水平条形图
R
barplot(c(1,2,4,5,6,3),horiz = TRUE)
堆砌条形图
R
> d1<-c("Placebo","Treated")
> d2<-c("None","Some","Marked")
> c<-c(29,13,7,7,7,21)
> a<-matrix(c,nrow=3,ncol = 2,byrow = TRUE,dimnames = list(d2,d1))
> a
Placebo Treated
None 29 13
Some 7 7
Marked 7 21
> barplot(a)
分组
R
barplot(a,beside = TRUE)
均值
R
> state.region
[1] South West West South West West Northeast
[8] South South South West West North Central North Central
[15] North Central North Central South South Northeast South Northeast
[22] North Central North Central South North Central West North Central West
[29] Northeast Northeast West Northeast South North Central North Central
[36] South West Northeast Northeast South North Central South
[43] South West Northeast South West South North Central
[50] West
Levels: Northeast South North Central West
> state.x77
Population Income Illiteracy Life Exp Murder HS Grad Frost Area
Alabama 3615 3624 2.1 69.05 15.1 41.3 20 50708
Alaska 365 6315 1.5 69.31 11.3 66.7 152 566432
Arizona 2212 4530 1.8 70.55 7.8 58.1 15 113417
Arkansas 2110 3378 1.9 70.66 10.1 39.9 65 51945
California 21198 5114 1.1 71.71 10.3 62.6 20 156361
Colorado 2541 4884 0.7 72.06 6.8 63.9 166 103766
Connecticut 3100 5348 1.1 72.48 3.1 56.0 139 4862
Delaware 579 4809 0.9 70.06 6.2 54.6 103 1982
Florida 8277 4815 1.3 70.66 10.7 52.6 11 54090
Georgia 4931 4091 2.0 68.54 13.9 40.6 60 58073
Hawaii 868 4963 1.9 73.60 6.2 61.9 0 6425
Idaho 813 4119 0.6 71.87 5.3 59.5 126 82677
Illinois 11197 5107 0.9 70.14 10.3 52.6 127 55748
Indiana 5313 4458 0.7 70.88 7.1 52.9 122 36097
Iowa 2861 4628 0.5 72.56 2.3 59.0 140 55941
Kansas 2280 4669 0.6 72.58 4.5 59.9 114 81787
Kentucky 3387 3712 1.6 70.10 10.6 38.5 95 39650
Louisiana 3806 3545 2.8 68.76 13.2 42.2 12 44930
Maine 1058 3694 0.7 70.39 2.7 54.7 161 30920
Maryland 4122 5299 0.9 70.22 8.5 52.3 101 9891
Massachusetts 5814 4755 1.1 71.83 3.3 58.5 103 7826
Michigan 9111 4751 0.9 70.63 11.1 52.8 125 56817
Minnesota 3921 4675 0.6 72.96 2.3 57.6 160 79289
Mississippi 2341 3098 2.4 68.09 12.5 41.0 50 47296
Missouri 4767 4254 0.8 70.69 9.3 48.8 108 68995
Montana 746 4347 0.6 70.56 5.0 59.2 155 145587
Nebraska 1544 4508 0.6 72.60 2.9 59.3 139 76483
Nevada 590 5149 0.5 69.03 11.5 65.2 188 109889
New Hampshire 812 4281 0.7 71.23 3.3 57.6 174 9027
New Jersey 7333 5237 1.1 70.93 5.2 52.5 115 7521
New Mexico 1144 3601 2.2 70.32 9.7 55.2 120 121412
New York 18076 4903 1.4 70.55 10.9 52.7 82 47831
North Carolina 5441 3875 1.8 69.21 11.1 38.5 80 48798
North Dakota 637 5087 0.8 72.78 1.4 50.3 186 69273
Ohio 10735 4561 0.8 70.82 7.4 53.2 124 40975
Oklahoma 2715 3983 1.1 71.42 6.4 51.6 82 68782
Oregon 2284 4660 0.6 72.13 4.2 60.0 44 96184
Pennsylvania 11860 4449 1.0 70.43 6.1 50.2 126 44966
Rhode Island 931 4558 1.3 71.90 2.4 46.4 127 1049
South Carolina 2816 3635 2.3 67.96 11.6 37.8 65 30225
South Dakota 681 4167 0.5 72.08 1.7 53.3 172 75955
Tennessee 4173 3821 1.7 70.11 11.0 41.8 70 41328
Texas 12237 4188 2.2 70.90 12.2 47.4 35 262134
Utah 1203 4022 0.6 72.90 4.5 67.3 137 82096
Vermont 472 3907 0.6 71.64 5.5 57.1 168 9267
Virginia 4981 4701 1.4 70.08 9.5 47.8 85 39780
Washington 3559 4864 0.6 71.72 4.3 63.5 32 66570
West Virginia 1799 3617 1.4 69.48 6.7 41.6 100 24070
Wisconsin 4589 4468 0.7 72.48 3.0 54.5 149 54464
Wyoming 376 4566 0.6 70.29 6.9 62.9 173 97203
> states<-data.frame(state.region,state.x77)
> states
state.region Population Income Illiteracy Life.Exp Murder HS.Grad Frost Area
Alabama South 3615 3624 2.1 69.05 15.1 41.3 20 50708
Alaska West 365 6315 1.5 69.31 11.3 66.7 152 566432
Arizona West 2212 4530 1.8 70.55 7.8 58.1 15 113417
Arkansas South 2110 3378 1.9 70.66 10.1 39.9 65 51945
California West 21198 5114 1.1 71.71 10.3 62.6 20 156361
Colorado West 2541 4884 0.7 72.06 6.8 63.9 166 103766
Connecticut Northeast 3100 5348 1.1 72.48 3.1 56.0 139 4862
Delaware South 579 4809 0.9 70.06 6.2 54.6 103 1982
Florida South 8277 4815 1.3 70.66 10.7 52.6 11 54090
Georgia South 4931 4091 2.0 68.54 13.9 40.6 60 58073
Hawaii West 868 4963 1.9 73.60 6.2 61.9 0 6425
Idaho West 813 4119 0.6 71.87 5.3 59.5 126 82677
Illinois North Central 11197 5107 0.9 70.14 10.3 52.6 127 55748
Indiana North Central 5313 4458 0.7 70.88 7.1 52.9 122 36097
Iowa North Central 2861 4628 0.5 72.56 2.3 59.0 140 55941
Kansas North Central 2280 4669 0.6 72.58 4.5 59.9 114 81787
Kentucky South 3387 3712 1.6 70.10 10.6 38.5 95 39650
Louisiana South 3806 3545 2.8 68.76 13.2 42.2 12 44930
Maine Northeast 1058 3694 0.7 70.39 2.7 54.7 161 30920
Maryland South 4122 5299 0.9 70.22 8.5 52.3 101 9891
Massachusetts Northeast 5814 4755 1.1 71.83 3.3 58.5 103 7826
Michigan North Central 9111 4751 0.9 70.63 11.1 52.8 125 56817
Minnesota North Central 3921 4675 0.6 72.96 2.3 57.6 160 79289
Mississippi South 2341 3098 2.4 68.09 12.5 41.0 50 47296
Missouri North Central 4767 4254 0.8 70.69 9.3 48.8 108 68995
Montana West 746 4347 0.6 70.56 5.0 59.2 155 145587
Nebraska North Central 1544 4508 0.6 72.60 2.9 59.3 139 76483
Nevada West 590 5149 0.5 69.03 11.5 65.2 188 109889
New Hampshire Northeast 812 4281 0.7 71.23 3.3 57.6 174 9027
New Jersey Northeast 7333 5237 1.1 70.93 5.2 52.5 115 7521
New Mexico West 1144 3601 2.2 70.32 9.7 55.2 120 121412
New York Northeast 18076 4903 1.4 70.55 10.9 52.7 82 47831
North Carolina South 5441 3875 1.8 69.21 11.1 38.5 80 48798
North Dakota North Central 637 5087 0.8 72.78 1.4 50.3 186 69273
Ohio North Central 10735 4561 0.8 70.82 7.4 53.2 124 40975
Oklahoma South 2715 3983 1.1 71.42 6.4 51.6 82 68782
Oregon West 2284 4660 0.6 72.13 4.2 60.0 44 96184
Pennsylvania Northeast 11860 4449 1.0 70.43 6.1 50.2 126 44966
Rhode Island Northeast 931 4558 1.3 71.90 2.4 46.4 127 1049
South Carolina South 2816 3635 2.3 67.96 11.6 37.8 65 30225
South Dakota North Central 681 4167 0.5 72.08 1.7 53.3 172 75955
Tennessee South 4173 3821 1.7 70.11 11.0 41.8 70 41328
Texas South 12237 4188 2.2 70.90 12.2 47.4 35 262134
Utah West 1203 4022 0.6 72.90 4.5 67.3 137 82096
Vermont Northeast 472 3907 0.6 71.64 5.5 57.1 168 9267
Virginia South 4981 4701 1.4 70.08 9.5 47.8 85 39780
Washington West 3559 4864 0.6 71.72 4.3 63.5 32 66570
West Virginia South 1799 3617 1.4 69.48 6.7 41.6 100 24070
Wisconsin North Central 4589 4468 0.7 72.48 3.0 54.5 149 54464
Wyoming West 376 4566 0.6 70.29 6.9 62.9 173 97203
> x<-aggregate(states$Illiteracy,by=list(state.region),FUN=mean)
> x
Group.1 x
1 Northeast 1.000000
2 South 1.737500
3 North Central 0.700000
4 West 1.023077
> barplot(x$x,names.arg = x$Group.1)
条形图的微调
R
par(mar=c(5,8,4,2))
> a
Placebo Treated
None 29 13
Some 7 7
Marked 7 21
> barplot(a,horiz = TRUE,cex.names = 0.8,names.arg = c("Noimproved","someimproved"))
标签水平
R
> par(las=2)
> barplot(a,horiz = TRUE,cex.names = 0.8,names.arg = c("Noimproved","someimproved"))
二，饼图
绘制简单的饼图
R
> par(mfrow=c(2,2))
> x<-c(10,12,4,16,8)
> lab<-c("US","UK","AUS","GMY","FRC")
> pie(x,lab,main="袁震")
有百分比的饼图
R
> pct<-round(x/sum(x)*100)
> pct
[1] 18 22 7 29 15
> lab1<-paste(lab," ",pct,"%",seq=" ")
> lab1
[1] "US 18 % " "UK 22 % " "AUS 7 % " "GMY 29 % " "FRC 15 % "
> pie(x,lab1,col=rainbow(length(lab1)),main = "袁震2")
3D饼图
R
> library(plotrix)
> pie3D(x,explode = 0.1,main="袁震3")
扇形
R
> fan.plot(x,labels = lab,main = "袁震4")
三，直方图
R
> x<-mtcars$mpg
> x
[1] 21.0 21.0 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 17.8 16.4 17.3 15.2 10.4 10.4 14.7 32.4 30.4 33.9
[21] 21.5 15.5 15.2 13.3 19.2 27.3 26.0 30.4 15.8 19.7 15.0 21.4
> hist(x)
R
> hist(x)
> hist(x,breaks = 12,col = "red",xlab = "袁震")
R
> hist(x,freq = FALSE,breaks = 12,col="green",xlab = "袁震")
> rug(jitter(x))
> lines(density(x),col="red",lwd=2)
四，核密度图
R
> x<-density(mtcars$mpg)
> mtcars$mpg
[1] 21.0 21.0 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 17.8 16.4 17.3 15.2 10.4 10.4 14.7 32.4 30.4 33.9
[21] 21.5 15.5 15.2 13.3 19.2 27.3 26.0 30.4 15.8 19.7 15.0 21.4
> x
Call:
density.default(x = mtcars$mpg)
Data: mtcars$mpg (32 obs.); Bandwidth 'bw' = 2.477
x y
Min. : 2.97 Min. :6.481e-05
1st Qu.:12.56 1st Qu.:5.461e-03
Median :22.15 Median :1.926e-02
Mean :22.15 Mean :2.604e-02
3rd Qu.:31.74 3rd Qu.:4.530e-02
Max. :41.33 Max. :6.795e-02
> plot(x)
R
> library(sm)
Package 'sm', version 2.2-6.0: type help(sm) for summary information
> mpg
[1] 21.0 21.0 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 17.8 16.4 17.3 15.2 10.4 10.4 14.7 32.4 30.4 33.9
[21] 21.5 15.5 15.2 13.3 19.2 27.3 26.0 30.4 15.8 19.7 15.0 21.4
> cyl
[1] 6 6 4 6 8 6 8 4 4 6 6 8 8 8 8 8 8 4 4 4 4 8 8 8 8 4 4 4 8 6 8 4
> sm.density.compare(mpg,cyl,xlab="袁震")
五，箱线图
R
> boxplot(mtcars$mpg,main="袁震",ylab="Miles per gallon")
R
boxplot(mpg~cyl,data = mtcars,main="袁震",xlab = "Number of cylinders",ylab = "Miles per gallon")