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How to convert matrix rows into a list in R?
Depending on our objective, a matrix rows might be needed to converted into a list that means each row will be an element of the list. This can be done by using the function as.list but firstly we need to convert the matrix into data frame after transposing. For example, if we have a matrix called M then it’s rows will be converted to a list using the command writtem below −
as.list(data.frame(t(M)))
Example1
M1<−matrix(1:25,nrow=5) M1
Output
[,1] [,2] [,3] [,4] [,5] [1,] 1 6 11 16 21 [2,] 2 7 12 17 22 [3,] 3 8 13 18 23 [4,] 4 9 14 19 24 [5,] 5 10 15 20 25
Example
as.list(data.frame(t(M1)))
Output
$X1 [1] 1 6 11 16 21 $X2 [1] 2 7 12 17 22 $X3 [1] 3 8 13 18 23 $X4 [1] 4 9 14 19 24 $X5 [1] 5 10 15 20 25
Example2
M2<−matrix(rnorm(36),nrow=6) M2
Output
[,1] [,2] [,3] [,4] [,5] [,6] [1,] 1.320181 0.17152409 −1.76634091 −0.48085533 −1.6186915 −1.4374249 [2,] −0.220481 −0.31776877 −2.16503900 −1.04481201 −1.2440593 −0.5943860 [3,] −0.138843 1.24491033 −0.23453374 0.09363227 0.1624981 −2.2085699 [4,] −0.535679 1.05556228 1.27692225 −1.00761472 −0.6388036 0.2438138 [5,] 1.563999 −0.08637959 −0.10161734 −3.03514376 −0.2729878 −0.4657192 [6,] 1.252191 2.09451091 −0.04484482 −0.96138526 1.2211188 −0.5685082
Example
as.list(data.frame(t(M2)))
Output
$X1 [1] 1.3201811 0.1715241 −1.7663409 −0.4808553 −1.6186915 −1.4374249 $X2 [1] −0.2204810 −0.3177688 −2.1650390 −1.0448120 −1.2440593 −0.5943860 $X3 [1] −0.13884303 1.24491033 −0.23453374 0.09363227 0.16249808 −2.20856995 $X4 [1] −0.5356790 1.0555623 1.2769222 −1.0076147 −0.6388036 0.2438138 $X5 [1] 1.56399912 −0.08637959 −0.10161734 −3.03514376 −0.27298782 −0.46571917 $X6 [1] 1.25219067 2.09451091 −0.04484482 −0.96138526 1.22111884 −0.56850819
Example3
M3<−matrix(rpois(16,2),ncol=4) M3
Output
[,1] [,2] [,3] [,4] [1,] 1 2 2 2 [2,] 0 5 1 3 [3,] 1 4 3 1 [4,] 0 1 4 2
Example
as.list(data.frame(t(M3)))
Output
$X1 [1] 1 2 2 2 $X2 [1] 0 5 1 3 $X3 [1] 1 4 3 1 $X4 [1] 0 1 4 2
Example4
M4<−matrix(runif(25,2,10),nrow=5) M4
Output
[,1] [,2] [,3] [,4] [,5] [1,] 9.470178 3.844069 3.126983 7.666309 8.801446 [2,] 4.517685 6.602599 6.353498 9.570915 2.854464 [3,] 5.104221 5.793673 4.875067 6.810684 2.926270 [4,] 2.694206 4.677686 8.749031 6.201677 4.149385 [5,] 2.085755 9.849269 9.084727 3.010815 7.153298
Example
as.list(data.frame(t(M4)))
Output
$X1 [1] 9.470178 3.844069 3.126983 7.666309 8.801446 $X2 [1] 4.517685 6.602599 6.353498 9.570915 2.854464 $X3 [1] 5.104221 5.793673 4.875067 6.810684 2.926270 $X4 [1] 2.694206 4.677686 8.749031 6.201677 4.149385 $X5 [1] 2.085755 9.849269 9.084727 3.010815 7.153298
Example5
M5<−matrix(rexp(16),nrow=4) M5
Output
[,1] [,2] [,3] [,4] [1,] 1.4500225 1.2780952 3.8074267 0.5150933 [2,] 0.6914497 3.0919047 4.9547217 1.5925355 [3,] 0.6407890 0.1222374 1.3573294 1.1416469 [4,] 1.0918338 1.1835358 0.8053099 0.2225276
Example
as.list(data.frame(t(M5)))
Output
$X1 [1] 1.4500225 1.2780952 3.8074267 0.5150933 $X2 [1] 0.6914497 3.0919047 4.9547217 1.5925355 $X3 [1] 0.6407890 0.1222374 1.3573294 1.1416469 $X4 [1] 1.0918338 1.1835358 0.8053099 0.2225276
Updated on: 05-Feb-2021
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