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How to divide the row values by row mean in R matrix?
To divide matrix row values by row mean in R, we can follow the below steps −
- First of all, create a matrix.
- Then, use apply function to divide the matrix row values by row mean.
Create the matrix
Let’s create a matrix as shown below −
M<-matrix(sample(1:10,75,replace=TRUE),ncol=3) M
On executing, the above script generates the below output(this output will vary on your system due to randomization) −
[,1] [,2] [,3] [1,] 9 1 5 [2,] 1 7 5 [3,] 6 7 5 [4,] 6 2 6 [5,] 9 8 7 [6,] 5 7 1 [7,] 9 5 1 [8,] 4 9 4 [9,] 10 2 6 [10,] 3 2 6 [11,] 2 5 1 [12,] 10 2 7 [13,] 4 8 1 [14,] 9 2 4 [15,] 2 1 7 [16,] 3 9 6 [17,] 7 10 7 [18,] 6 4 3 [19,] 2 10 6 [20,] 10 4 10 [21,] 8 5 8 [22,] 9 4 10 [23,] 10 7 1 [24,] 1 2 6 [25,] 2 10 8
Divide the matrix row values by row mean
Using apply function to divide the row values of M by row mean −
M<-matrix(sample(1:10,75,replace=TRUE),ncol=3) M_new<-t(apply(M,1, function(x) x/mean(x))) M_new
Output
[,1] [,2] [,3] [1,] 1.8000000 0.2000000 1.0000000 [2,] 0.2307692 1.6153846 1.1538462 [3,] 1.0000000 1.1666667 0.8333333 [4,] 1.2857143 0.4285714 1.2857143 [5,] 1.1250000 1.0000000 0.8750000 [6,] 1.1538462 1.6153846 0.2307692 [7,] 1.8000000 1.0000000 0.2000000 [8,] 0.7058824 1.5882353 0.7058824 [9,] 1.6666667 0.3333333 1.0000000 [10,] 0.8181818 0.5454545 1.6363636 [11,] 0.7500000 1.8750000 0.3750000 [12,] 1.5789474 0.3157895 1.1052632 [13,] 0.9230769 1.8461538 0.2307692 [14,] 1.8000000 0.4000000 0.8000000 [15,] 0.6000000 0.3000000 2.1000000 [16,] 0.5000000 1.5000000 1.0000000 [17,] 0.8750000 1.2500000 0.8750000 [18,] 1.3846154 0.9230769 0.6923077 [19,] 0.3333333 1.6666667 1.0000000 [20,] 1.2500000 0.5000000 1.2500000 [21,] 1.1428571 0.7142857 1.1428571 [22,] 1.1739130 0.5217391 1.3043478 [23,] 1.6666667 1.1666667 0.1666667 [24,] 0.3333333 0.6666667 2.0000000 [25,] 0.3000000 1.5000000 1.2000000
Updated on: 13-Aug-2021
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