How to find the maximum value for each column of a matrix in R?

To find the maximum value for each column of a matrix, we need to use apply function. For example, if we have a matrix M that contains 2 rows and 2 columns with values 1, 2 in the first row and 3, 4 in the second row then the maximum for each of the columns in that matrix can be found by using the syntax; apply(M,2,max), hence the result will be 3, 4.
 Live Demo
M1−-matrix(1:36,ncol=6)
M1
   [,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1    7    13   19   25   31
[2,] 2    8    14   20   26   32
[3,] 3    9    15   21   27   33
[4,] 4    10   16   22   28   34
[5,] 5    11   17   23   29   35
[6,] 6    12   18   24   30   36
apply(M1,2,max)
[1] 6 12 18 24 30 36
 Live Demo
M2<-matrix(1:100,ncol=10)
M2
   [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1    11   21   31    41   51 61    71   81    91
[2,] 2    12   22   32    42   52 62    72   82    92
[3,] 3    13   23   33    43   53 63    73   83    93
[4,] 4    14   24   34    44   54 64    74   84    94
[5,] 5    15   25   35    45   55 65    75   85    95
[6,] 6    16   26   36    46   56 66    76   86    96
[7,] 7    17   27   37    47   57 67    77   87    97
[8,] 8    18   28   38    48   58 68    78   88    98
[9,] 9    19   29   39    49   59 69    79   89    99
[10,] 10  20   30   40    50   60 70    80   90    100
apply(M2,2,max)
[1] 10 20 30 40 50 60 70 80 90 100
 Live Demo
M3<-matrix(sample(rnorm(10),25,replace=TRUE),ncol=5)
M3
         [,1]       [,2]       [,3]       [,4]       [,5]
[1,] -0.8410610 -0.8410610 -1.1271937 -0.8410610 -0.1262492
[2,] -1.1271937 -0.3367099 -0.8410610 -0.2109494 -0.2109494
[3,] -0.1262492 -1.0366269 -0.2109494 -0.3367099 -0.2109494
[4,] -0.2109494 -0.3367099 -0.3367099 -0.3367099 -1.9793046
[5,] -1.2250289 -0.1262492 -0.1262492 -1.0366269 -1.1271937
apply(M3,2,max)
[1] -0.1262492 -0.1262492 -0.1262492 -0.2109494 -0.1262492
 Live Demo
M4<-matrix(sample(rnorm(100,10,1),25),ncol=5)
M4
      [,1]       [,2]       [,3]    [,4]    [,5]
[1,] 8.880632 9.932590 12.152003 10.745158 12.644492
[2,] 8.743728 9.223513 9.937427  9.327102  9.490583
[3,] 7.502350 10.231251 9.350336 10.823048 9.282358
[4,] 9.830723 9.045965  10.197617 9.194218 9.420975
[5,] 9.974345 10.835077 9.982087 10.112384 9.404278
apply(M4,2,max)
[1] 9.974345 10.835077 12.152003 10.823048 12.644492
 Live Demo
M5<-matrix(sample(rpois(100,10),64),ncol=8)
M5
    [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
[1,] 16    4    9    9    10    5   15    9
[2,]  3    6    11   6    15    17   5    9
[3,]  7    10   9    6    16    14   6    2
[4,] 12    10   9    5    10    9    7    11
[5,] 11    9    10   9    12    10   17   6
[6,] 11    10   7    10    9    12   8    9
[7,] 11    7    6    11    8    9    9    8
[8,]  9    12   12    9    12   12   14   12
apply(M5,2,max)
[1] 16 12 12 11 16 17 17 12
 Live Demo
M6<-matrix(sample(1:10,100,replace=TRUE),ncol=10)
M6
   [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 7    1    7    3    5    7    8    7    10    4
[2,] 6    9    7    4    6    5    5    10   9    7
[3,] 10   4    2    2    8    9    9    4    4    1
[4,] 3    1    7    3    3    7    10   8    7    4
[5,] 5    10   7    8    10   3    5    1    8    4
[6,] 7    3    10   4    5    1    5    5    3    4
[7,] 6    4    4    2    1    9    3    6    6    2
[8,] 10   4    2    8    6    10   6    2    5    8
[9,] 6    9    10   7    3    4    6    6    5    4
[10,] 7   10   5    3    6    7    3    8    9    2
apply(M6,2,max)
[1] 10 10 10 8 10 10 10 10 10 8
 Live Demo
M7<-matrix(sample(runif(10,2,5),25,replace=TRUE),ncol=5)
M7
      [,1]       [,2]     [,3]    [,4]    [,5]
[1,] 2.637646 4.744968 3.122147 4.563885 4.744968
[2,] 3.418107 2.637646 3.331060 3.122147 2.845479
[3,] 2.190630 3.331060 2.637646 2.190630 4.834246
[4,] 4.834246 4.563885 2.845479 2.845479 3.418107
[5,] 2.845479 2.190630 2.190630 4.744968 2.637646
apply(M7,2,max)
[1] 4.834246 4.744968 3.331060 4.744968 4.834246
 Live Demo
M8<-matrix(sample(5001:9999,64),ncol=8)
M8
     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
[1,] 5294 5567 9539 5907 9808 6692 6810 9809
[2,] 9005 5150 9502 7604 8849 8504 6631 6261
[3,] 6694 5162 7813 5995 9684 8647 7094 9828
[4,] 5055 7450 7588 8006 8480 5145 9741 8959
[5,] 8300 5964 8411 6109 5320 8649 5777 9473
[6,] 9054 5585 7304 6827 6231 5199 8518 8958
[7,] 5912 8356 6741 9949 6363 9488 7093 6813
[8,] 6312 7701 5741 6947 6012 6579 6873 7793
apply(M8,2,max)
[1] 9054 8356 9539 9949 9808 9488 9741 9828