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How to subset matrix row values based on different columns?
Suppose we have a matrix called M that contains three columns and we want to subset row values of M but from different columns that means the subset will not have values only from a single column.
Hence, before creating the subset we first need to find the column numbers that can be used for the creation of subset and this can be done with the help of sample function if column numbers are not known. After that we can use cbind function with single square brackets for subsetting.
Check out the Examples given below to understand how it can be done.
Example 1
Following snippet creates a sample matrix −
M1The following matrix is created −
[,1] [,2] [,3] [,4] [1,] 7 11 17 14 [3,] 6 5 10 9 [4,] 8 9 14 10 [5,] 10 14 9 6 [6,] 13 6 6 6 [7,] 10 15 10 10 [8,] 9 10 10 9 [9,] 13 9 14 10 [10,] 9 4 6 14 [11,] 12 11 11 6 [12,] 8 15 8 8 [13,] 7 13 11 9 [14,] 16 9 9 12 [15,] 10 9 11 13 [16,] 10 10 6 5 [17,] 11 7 15 13 [18,] 9 6 13 4 [19,] 18 4 14 11 [20,] 17 11 9 7To subset matrix row values based on different columns in R, on the above created matrix add the following code to the above snippet −
M1Output
If you execute all the above given snippets as a single program, it generates the following Output −
[1] 2 4 2 1 4 3 2 4 1 4 3 4 4 2 1 4 3 4 1 1To subset matrix row values based on different columns in R, on the above created matrix add the following code to the above snippet −
M1Output
If you execute all the above given snippets as a single program, it generates the following Output −
[1] 12 14 5 8 6 6 15 9 13 14 11 8 9 9 10 5 15 4 18 17Example 2
Following snippet creates a sample matrix −
M2The following matrix is created −
[,1] [,2] [1,] 0.0526401 -1.33823138 [2,] -0.9658880 -0.19916662 [3,] -0.1729805 0.38128801 [4,] 1.0575809 -1.74814941 [5,] 0.9132299 2.22706167 [6,] -1.0254388 0.72220810 [7,] -0.4295359 0.23052190 [8,] -0.5603532 -1.71916189 [9,] -1.0226156 -0.62879763 [10,] 0.4251926 0.51384615 [11,] 0.9658157 0.11204097 [12,] -1.1791793 0.90926504 [13,] -1.0283043 0.32224749 [14,] -1.0399879 -0.75888477 [15,] 0.2083132 -0.88142437 [16,] 1.1399261 -0.43637839 [17,] 0.3146594 0.84852872 [18,] 0.9208013 0.09130219 [19,] -0.7754234 -0.17243346 [20,] -1.8399159 0.35939999To subset matrix row values based on different columns in R, on the above created matrix add the following code to the above snippet −
M2Output
If you execute all the above given snippets as a single program, it generates the following Output −
[1] 1 2 1 1 1 2 2 2 2 1 2 2 1 1 2 2 1 2 1 2To subset matrix row values based on different columns in R, on the above created matrix add the following code to the above snippet −
M2Output
If you execute all the above given snippets as a single program, it generates the following Output −
[1] 0.05264010 -0.19916662 -0.17298052 1.05758086 0.91322994 0.72220810 [7] 0.23052190 -1.71916189 -0.62879763 0.42519260 0.11204097 0.90926504 [13] -1.02830426 -1.03998789 -0.88142437 -0.43637839 0.31465938 0.09130219 [19] -0.77542338 0.35939999Example 3
Following snippet creates a sample matrix −
M3The following matrix is created −
[,1] [,2] [,3] [1,] 3.82 2.32 3.00 [2,] 4.07 4.21 2.42 [3,] 1.98 4.75 4.18 [4,] 2.34 3.73 3.60 [5,] 2.63 2.69 4.82 [6,] 2.62 3.76 1.57 [7,] 4.28 2.62 4.12 [8,] 2.86 4.98 4.76 [9,] 2.36 1.61 2.00 [10,] 3.22 1.17 2.97 [11,] 2.04 2.41 3.90 [12,] 1.76 2.29 2.14 [13,] 3.05 1.07 2.43 [14,] 4.98 1.72 1.42 [15,] 3.57 2.90 4.89 [16,] 1.00 4.98 4.58 [17,] 2.09 1.49 1.88 [18,] 2.49 1.67 3.49 [19,] 2.59 1.55 1.21 [20,] 4.43 3.39 2.81To subset matrix row values based on different columns in R, on the above created matrix add the following code to the above snippet −
M3Output
If you execute all the above given snippets as a single program, it generates the following Output −
[1] 2 2 3 3 3 2 2 2 3 1 1 1 2 2 1 3 1 2 2 3To subset matrix row values based on different columns in R, on the above created matrix add the following code to the above snippet −
M3Output
If you execute all the above given snippets as a single program, it generates the following Output −
[1] 2.32 4.21 4.18 3.60 4.82 3.76 2.62 4.98 2.00 3.22 2.04 1.76 1.07 1.72 3.57 [16] 4.58 2.09 1.67 1.55 2.81
