No.13 数据可视化02

主要内容:

  • 条形图
  • 饼图
  • 直方图
  • 核密度图等

1. 条形图 barplot()

1.1 调用数据mtcars

mtcars$gear
结果:
> mtcars$gear
 [1] 4 4 4 3 3 3 3 4 4 4 4 3 3 3 3 3 3 4 4 4 3 3 3 3 3 4 5 5 5 5 5 4

1.2 频数统计 table( )函数

#统计频数
table(mtcars$gear)

结果:
> #统计频数
> table(mtcars$gear)

 3  4  5 
15 12  5
barplot(table(mtcars$gear), names.arg = c('gear-3','gear-4','gear-5'),
        ylim = c(0,20),   
        col=c("blue","green","red"))   

barplot(table(mtcars$gear), names.arg = c('gear-3','gear-4','gear-5'),
        horiz = T,   #控制横向还是纵向
        xlim = c(0,20),
        col=c("blue","green","red")) 

 

1.3 叠加柱状图 (矩阵输入)

table(mtcars$gear,mtcars$vs)

barplot(table(mtcars$gear,mtcars$vs))

结果:
> table(mtcars$gear,mtcars$vs)
   
     0  1
  3 12  3
  4  2 10
  5  4  1

 

table(mtcars$gear,mtcars$vs)

barplot(table(mtcars$gear,mtcars$vs), col=c("blue","green","red"))
legend("topright", title = "gear",
       legend = c(3,4,5), col = c("blue","green","red"), pch = 15, cex = 0.6 )  #pch = 15表示方框, cex = 0.6 缩放因子

结果:
> table(mtcars$gear,mtcars$vs)
   
     0  1
  3 12  3
  4  2 10
  5  4  1

 

barplot(table(mtcars$gear,mtcars$vs), beside=T, col=c("blue","green","red"))    #beside = T表示不堆叠,默认堆叠
legend("topright", title = "gear",
       legend = c(3,4,5), col = c("blue","green","red"), pch = 15, cex = 0.6 )

 

 2. 饼图 pie( )

#R自带调色板
a <- rainbow(5)
pie(c(1,1,1,1,1),col=a)

 

 3. 直方图 hist( ) 

hist(mtcars$disp)

 

4. 其他

lines() #在plot() 绘制的图像上再绘制图像(曲线)

 

 

 

 

posted @ 2025-01-23 11:55  百里屠苏top  阅读(14)  评论(0)    收藏  举报