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Define column and row names of a square matrix in a single line code if they are same in R.
If we have a square matrix or we want to create a square matrix and the row names and column names for this matrix are same then we can define these names in a single line of code.
For Example, if we have a matrix called M that has 10 rows and 10 columns that has first ten alphabets as row and column names then we can define the column names as colnames(M)<-rownames(M)<-LETTERS[1:10].
Example 1
Consider the matrix given below −
M1<-matrix(rpois(25,5),ncol=5) M1
The following dataframe is created
[,1] [,2] [,3] [,4] [,5] [1,] 3 5 7 6 6 [2,] 8 6 6 6 4 [3,] 2 6 2 8 7 [4,] 1 3 5 9 4 [5,] 3 6 6 7 3
To define the column names and row names of M1 on the above created data frame, add the following code to the above snippet −
M1<-matrix(rpois(25,5),ncol=5) colnames(M1)<-rownames(M1)<-LETTERS[1:5] M1
Output
If you execute all the above given snippets as a single program, it generates the following Output −
A B C D E A 3 5 7 6 6 B 8 6 6 6 4 C 2 6 2 8 7 D 1 3 5 9 4 E 3 6 6 7 3
Example 2
Consider the matrix given below −
M2<-matrix(rpois(25,50),ncol=5) M2
The following dataframe is created
[,1] [,2] [,3] [,4] [,5] [1,] 54 40 53 42 51 [2,] 59 44 54 67 55 [3,] 51 42 54 47 55 [4,] 68 38 37 47 39 [5,] 35 52 53 58 51
To define the column names and row names of M2 on the above created data frame, add the following code to the above snippet −
M2<-matrix(rpois(25,50),ncol=5)
colnames(M2)<-rownames(M2)<-c("Asia","Americas","Africa","Europe","Oceania")
M2Output
If you execute all the above given snippets as a single program, it generates the following Output −
Asia Americas Africa Europe Oceania Asia 54 40 53 42 51 Americas 59 44 54 67 55 Africa 51 42 54 47 55 Europe 68 38 37 47 39 Oceania 35 52 53 58 51
Example 3
Consider the following matrix
M3<-matrix(round(rnorm(25),2),ncol=5) M3
The following dataframe is created
[,1] [,2] [,3] [,4] [,5] [1,] 0.68 -0.35 0.76 -0.22 0.36 [2,] -0.42 -0.28 -0.63 0.09 1.22 [3,] 0.05 -0.91 1.21 -0.17 0.86 [4,] 0.99 -0.71 -0.20 -0.58 -0.02 [5,] -0.21 -1.43 1.45 -0.26 -1.51
To define the column names and row names of M3 on the above created data frame, add the following code to the above snippet −
M3<-matrix(round(rnorm(25),2),ncol=5)
colnames(M3)<-rownames(M3)<-c("Rate1","Rate2","Rate3","Rate4","Rate5")
M3Output
If you execute all the above given snippets as a single program, it generates the following Output −
Rate1 Rate2 Rate3 Rate4 Rate5 Rate1 0.68 -0.35 0.76 -0.22 0.36 Rate2 -0.42 -0.28 -0.63 0.09 1.22 Rate3 0.05 -0.91 1.21 -0.17 0.86 Rate4 0.99 -0.71 -0.20 -0.58 -0.02 Rate5 -0.21 -1.43 1.45 -0.26 -1.51
Example 4
Consider the matrix given below −
M4<-matrix(round(rnorm(25,500,),0),ncol=5) M4
The following dataframe is created
[,1] [,2] [,3] [,4] [,5] [1,] 499 500 499 498 502 [2,] 501 501 501 501 499 [3,] 499 500 501 503 500 [4,] 501 502 500 500 501 [5,] 500 499 500 500 502
To define the column names and row names of M4 on the above created data frame, add the following code to the above snippet −
colnames(M4)<-rownames(M4)<-c("Score1","Score2","Score3","Score4","Score5")
M4Output
If you execute all the above given snippets as a single program, it generates the following Output −
Score1 Score2 Score3 Score4 Score5 Score1 499 500 499 498 502 Score2 501 501 501 501 499 Score3 499 500 501 503 500 Score4 501 502 500 500 501 Score5 500 499 500 500 502
Example 5
Consider the matrix given below −
M5<-matrix(rpois(25,100),ncol=5) M5
The following dataframe is created
[,1] [,2] [,3] [,4] [,5] [1,] 92 116 107 100 91 [2,] 111 94 110 95 93 [3,] 87 98 91 88 107 [4,] 106 91 98 94 104 [5,] 97 94 108 104 102
To define the column names and row names of M5 on the above created data frame, add the following code to the above snippet −
M5<-matrix(rpois(25,100),ncol=5)
colnames(M5)<-rownames(M5)<-c("Sour","Salty","Meaty","Sweet","Bitter")
M5Output
If you execute all the above given snippets as a single program, it generates the following Output −
Sour Salty Meaty Sweet Bitter Sour 92 116 107 100 91 Salty 111 94 110 95 93 Meaty 87 98 91 88 107 Sweet 106 91 98 94 104 Bitter 97 94 108 104 102
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