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How to find mean for x number of rows in a column in an R matrix?
To find the mean for x number of rows in a column, we can use colMeans function by accessing the column and providing the number of rows. For example, if we have a matrix called M that contains 20 rows and 5 columns then we can find the mean of column 5 for 5 number of rows can use the command colMeans(matrix(M[,5],nrow=5))
Example
Consider the below data frame −
M1<-matrix(rpois(40,8),ncol=2) M1
Output
[,1] [,2] [1,] 10 15 [2,] 13 2 [3,] 8 9 [4,] 10 10 [5,] 12 6 [6,] 9 9 [7,] 8 10 [8,] 10 7 [9,] 6 8 [10,] 8 6 [11,] 9 7 [12,] 7 11 [13,] 7 7 [14,] 3 9 [15,] 7 9 [16,] 5 8 [17,] 8 7 [18,] 8 9 [19,] 11 8 [20,] 12 6
Finding the column means for 5 rows of column 2 in matrix M1 −
Example
colMeans(matrix(M1[,2],nrow=5))
Output
[1] 8.4 8.0 8.6 7.6
Example
M2<-matrix(rpois(40,2),ncol=2) M2
Output
[,1] [,2] [1,] 3 2 [2,] 0 1 [3,] 2 0 [4,] 3 1 [5,] 2 5 [6,] 0 2 [7,] 4 1 [8,] 3 2 [9,] 1 1 [10,] 3 2 [11,] 4 1 [12,] 3 0 [13,] 3 0 [14,] 1 1 [15,] 1 3 [16,] 5 1 [17,] 1 3 [18,] 0 2 [19,] 0 0 [20,] 2 0
Finding the column means for 5 rows of column 1 in matrix M2 −
Example
colMeans(matrix(M2[,1],nrow=10))
Output
[1] 2.1 2.0
Example
M3<-matrix(rnorm(40),ncol=2) M3
Output
[,1] [,2] [1,] -0.86899396 0.18289633 [2,] 1.94158458 -0.41550961 [3,] -0.01652085 0.33423246 [4,] -0.42176679 -0.13531805 [5,] -0.12017362 0.06968550 [6,] 0.03800341 0.58490129 [7,] -1.18465429 -0.82407038 [8,] -0.73443569 -0.82960221 [9,] -0.24319549 2.37106377 [10,] 0.78948173 -0.43151208 [11,] 1.57152561 -1.10791821 [12,] -0.77984591 1.13553555 [13,] 0.20805120 -0.83979624 [14,] -0.56464950 -0.15396888 [15,] -0.88983476 0.49162747 [16,] -0.97218350 2.21226831 [17,] -0.10437036 -1.97389026 [18,] 0.38189778 -0.47881007 [19,] 0.61784737 0.07162197 [20,] 0.25541676 0.02707504
Finding the column means for 5 rows of column 1 in matrix M3 −
Example
colMeans(matrix(M3[,1],nrow=10))
Output
[1] -0.08206710 -0.02761453
Updated on: 17-Mar-2021
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