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How to find the row standard deviation of columns having same name in R matrix?
To find the row standard deviation of columns having same name in R matrix, we can follow the below steps −
First of all, create a matrix with some columns having same name.
Then, use tapply along with colnames and sd function to find the row standard deviation of columns having same name.
Example
Create the matrix
Let’s create a matrix as shown below −
M<-matrix(rpois(100,5),ncol=4) colnames(M)<-c("C1","C2","C1","C2") M
Output
On executing, the above script generates the below output(this output will vary on your system due to randomization) −
C1 C2 C1 C2 [1,] 2 6 3 1 [2,] 9 4 3 4 [3,] 4 4 1 2 [4,] 3 2 2 4 [5,] 5 7 2 4 [6,] 3 9 7 2 [7,] 3 3 5 3 [8,] 6 5 4 5 [9,] 6 7 7 7 [10,] 7 6 5 5 [11,] 2 7 3 7 [12,] 1 4 4 7 [13,] 6 7 7 7 [14,] 1 3 1 2 [15,] 9 8 4 5 [16,] 4 4 4 2 [17,] 5 7 1 4 [18,] 3 6 6 9 [19,] 5 7 3 7 [20,] 4 7 4 5 [21,] 3 6 3 5 [22,] 2 6 5 3 [23,] 6 3 5 6 [24,] 5 3 5 6 [25,] 3 6 5 9
Find the row standard deviation of columns having same name
Using tapply along with colnames and sd function to find the row standard deviation of columns having same name in matrix M −
M<-matrix(rpois(100,5),ncol=4) colnames(M)<-c("C1","C2","C1","C2") t(apply(M,1, function(x) tapply(x,colnames(M),sd)))
Output
C1 C2 [1,] 0.7071068 3.5355339 [2,] 4.2426407 0.0000000 [3,] 2.1213203 1.4142136 [4,] 0.7071068 1.4142136 [5,] 2.1213203 2.1213203 [6,] 2.8284271 4.9497475 [7,] 1.4142136 0.0000000 [8,] 1.4142136 0.0000000 [9,] 0.7071068 0.0000000 [10,] 1.4142136 0.7071068 [11,] 0.7071068 0.0000000 [12,] 2.1213203 2.1213203 [13,] 0.7071068 0.0000000 [14,] 0.0000000 0.7071068 [15,] 3.5355339 2.1213203 [16,] 0.0000000 1.4142136 [17,] 2.8284271 2.1213203 [18,] 2.1213203 2.1213203 [19,] 1.4142136 0.0000000 [20,] 0.0000000 1.4142136 [21,] 0.0000000 0.7071068 [22,] 2.1213203 2.1213203 [23,] 0.7071068 2.1213203 [24,] 0.0000000 2.1213203 [25,] 1.4142136 2.1213203
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