Today, I am going to introduce a matrix. In practical terms, I am sure this lesson will be helpful in the real word.
We learned new concept a "Vector" in a previous chapter, but in reality, we handle more complex data set, and variable. "Matrix" is one of the useful data set we can make.
I'll show you how to make a simple matrix.
First, I can make a matrix using several vectors.
> Pencil <- c(1,2,3,4,5)
> Computer <- c(10,20,30,40,50)
> Tree <- c(100,200,300,400,500)
> Export_Item <- cbind(Pencil,Computer, Tree)
> Export_Item
Pencil Computer Tree
[1,] 1 10 100
[2,] 2 20 200
[3,] 3 30 300
[4,] 4 40 400
[5,] 5 50 500
> Export_Item <- rbind(Pencil,Computer, Tree)
> Export_Item
[,1] [,2] [,3] [,4] [,5]
Pencil 1 2 3 4 5
Computer 10 20 30 40 50
Tree 100 200 300 400 500
# As you can see above, cbind binds vectors into a matrix by columns and
rbind binds vectors into a matrix by rows
Second, we can make a matrix using matrix function.
See, by default vectors pour into a matrix by columns but it can be done by rows by
setting the option "byrow=T"
> matrix (1:15, nrow=5, ncol=3)
[,1] [,2] [,3]
[1,] 1 6 11
[2,] 2 7 12
[3,] 3 8 13
[4,] 4 9 14
[5,] 5 10 15
> matrix (1:15,nrow=5, ncol=3,byrow=T)
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 4 5 6
[3,] 7 8 9
[4,] 10 11 12
[5,] 13 14 15
>
Now, you can calculate by matrix.
> Export_Item*Export_Item
[,1] [,2] [,3] [,4] [,5]
Pencil 1 4 9 16 25
Computer 100 400 900 1600 2500
Tree 10000 40000 90000 160000 250000
> Export_Item-Export_Item
[,1] [,2] [,3] [,4] [,5]
Pencil 0 0 0 0 0
Computer 0 0 0 0 0
Tree 0 0 0 0 0
> Export_Item+Export_Item
[,1] [,2] [,3] [,4] [,5]
Pencil 2 4 6 8 10
Computer 20 40 60 80 100
Tree 200 400 600 800 1000
If you want to change the first rows or column title into a new label.
Just do it like this.
> dimnames(Export_Item)[[2]]=c("JAN","FEB","MAR","APR","MAY")
> Export_Item
JAN FEB MAR APR MAY
Pencil 1 2 3 4 5
Computer 10 20 30 40 50
Tree 100 200 300 400 500
> dimnames(Export_Item)[[1]]=c("Teenager","Woman","MAN")
> Export_Item
JAN FEB MAR APR MAY
Teenager 1 2 3 4 5
Woman 10 20 30 40 50
MAN 100 200 300 400 500
I hope this lesson help your study..
see you next chapter.
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