cbind： 根据列进行合并，即叠加所有列，m列的矩阵与n列的矩阵cbind()最后变成m+n列，合并前提：cbind(a, c)中矩阵a、c的行数必需相符

rbind： 根据行进行合并，就是行的叠加，m行的矩阵与n行的矩阵rbind()最后变成m+n行，合并前提：rbind(a, c)中矩阵a、c的列数必需相符

> a <- matrix(1:12, 3, 4)
> print(a)
   [,1] [,2] [,3] [,4]
[1,]  1  4  7  10
[2,]  2  5  8  11
[3,]  3  6  9  12
> 
> b <- matrix(-1:-12, 3, 4)
> print(b)
   [,1] [,2] [,3] [,4]
[1,]  -1  -4  -7 -10
[2,]  -2  -5  -8 -11
[3,]  -3  -6  -9 -12
> 
> x=cbind(a,b)
> print(x)
   [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
[1,]  1  4  7  10  -1  -4  -7 -10
[2,]  2  5  8  11  -2  -5  -8 -11
[3,]  3  6  9  12  -3  -6  -9 -12
> 
> y=rbind(a,b)
> print(y)
   [,1] [,2] [,3] [,4]
[1,]  1  4  7  10
[2,]  2  5  8  11
[3,]  3  6  9  12
[4,]  -1  -4  -7 -10
[5,]  -2  -5  -8 -11
[6,]  -3  -6  -9 -12
> 
> 
> c <- matrix(-1:-20, 4, 5)
> print(c)
   [,1] [,2] [,3] [,4] [,5]
[1,]  -1  -5  -9 -13 -17
[2,]  -2  -6 -10 -14 -18
[3,]  -3  -7 -11 -15 -19
[4,]  -4  -8 -12 -16 -20
> 
> x2=cbind(a,c)
Error in cbind(a, c) : 矩阵的行数必需相符(见arg2)
> print(x2)
   [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
[1,]  1  4  7  10  -1  -4  -7 -10 -13
[2,]  2  5  8  11  -2  -5  -8 -11 -14
[3,]  3  6  9  12  -3  -6  -9 -12 -15
> 
> y2=rbind(a,c)
Error in rbind(a, c) : 矩阵的列数必需相符(见arg2)
> print(y2)
Error in print(y2) : 找不到对象'y2'
> 

merge函数

两个数据框拥有相同的时间或观测值，但这些列却不尽相同。处理的办法就是使用
merge(x, y ,by.x = ,by.y = ,all = ) 函数。

#merge／合并
ID<-c(1,2,3,4)
name<-c(“A”,”B”,”C”,”D”)
score<-c(60,70,80,90)
student1<-data.frame(ID,name)
student2<-data.frame(ID,score)
total_student1<-merge(student1,student2,by=”ID”)
total_student1

当我们需要将相同的观测对象得出的不同类型变量合并时，则采用cbind，也就是合并columm。