r - Converting table to a matrix -

in image, want arrange table (on left-side) table (on right-side) containing 3 rows.

https://drive.google.com/file/d/0b4ggtf6nyi4ymhltwjrkedhob3m/view?usp=sharing

that is, have table this

     0      3       6       9       13      16      31     64 n    100,0  98,7    96,7    97,5    91,2    15,7    0,4   0,6 n1   100,0  102,0   97,8    98,6    89,8    11,0    0,3   0,2 

and want arrange this:

alkanes time    degradation n   0   100,0 n   3   98,7 n   6   96,7 n   9   97,5 n   13  91,2 n   16  15,7 n   31  0,4 n   64  0,6 n1  0   100,0 n1  3   102,0 n1  6   97,8 n1  9   98,6 n1  13  89,8 n1  16  11,0 n1  31  0,3 n1  64  0,2 

sample data:

x <- structure(list(x = structure(1:3, .label = c("n", "n1", "n2"), class = "factor"), x0 = c(100, 100, 100), x3 = c(98.7, 102, 95.1), x6 = c(96.7, 97.8, 94.5), x9 = c(97.5, 98.6, 101), x13 = c(91.2, 89.8, 89.4), x16 = c(15.7, 11, 22.5), x31 = c(0.4, 0.3, 0), x64 = c(0.6, 0.2, 0)), .names = c("x", "x0", "x3", "x6", "x9", "x13", "x16", "x31", "x64"), class = "data.frame", row.names = c(na, -3l)) 

desired output:

y <- structure(list(alkanes = structure(c(1l, 1l, 1l, 1l, 1l, 1l, 1l, 1l, 2l, 2l, 2l, 2l, 2l, 2l, 2l, 2l, 3l, 3l, 3l, 3l, 3l, 3l, 3l, 3l), .label = c("n", "n1", "n2"), class = "factor"), time = c(0l, 3l, 6l, 9l, 13l, 16l, 31l, 64l, 0l, 3l, 6l, 9l, 13l, 16l, 31l, 64l, 0l, 3l, 6l, 9l, 13l, 16l, 31l, 64l), degradation = c(100, 98.7, 96.7, 97.5, 91.2, 15.7, 0.4, 0.6, 100, 102, 97.8, 98.6, 89.8, 11, 0.3, 0.2, 100, 95.1, 94.5, 101, 89.4, 22.5, 0, 0)), .names = c("alkanes", "time", "degradation"), class = "data.frame", row.names = c(na, -24l)) 

given "x" as:

x #    x  x0    x3   x6    x9  x13  x16 x31 x64 # 1  n 100  98.7 96.7  97.5 91.2 15.7 0.4 0.6 # 2 n1 100 102.0 97.8  98.6 89.8 11.0 0.3 0.2 # 3 n2 100  95.1 94.5 101.0 89.4 22.5 0.0 0.0 

you can try like:

as.data.frame(   as.table(     `dimnames<-`(as.matrix(x[-1]), list(x[[1]], gsub("x", "", names(x)[-1]))))) #    var1 var2  freq # 1     n    0 100.0 # 2    n1    0 100.0 # 3    n2    0 100.0 # 4     n    3  98.7 # 5    n1    3 102.0 # 6    n2    3  95.1 # 7     n    6  96.7 # 8    n1    6  97.8 # 9    n2    6  94.5 # 10    n    9  97.5 # 11   n1    9  98.6 # 12   n2    9 101.0 # 13    n   13  91.2 # 14   n1   13  89.8 # 15   n2   13  89.4 # 16    n   16  15.7 # 17   n1   16  11.0 # 18   n2   16  22.5 # 19    n   31   0.4 # 20   n1   31   0.3 # 21   n2   31   0.0 # 22    n   64   0.6 # 23   n1   64   0.2 # 24   n2   64   0.0 

from there, it's sorting , renaming columns, standard operations.