要将矩阵转换为以列名和行名作为变量的数据框，我们首先需要将矩阵转换为表，然后使用as.data.frame将其读取为数据框。例如，如果我们有一个矩阵M，那么可以使用以下命令完成它-
as.data.frame(as.table(M))
> M1<-matrix(1:36,nrow=6) > M1输出结果
[,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
> rownames(M1)<-1:6 > colnames(M1)<-LETTERS[1:6] > M1输出结果
A B C D E F 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
> as.data.frame(as.table(M1))输出结果
Var1 Var2 Freq 1 1 A 1 2 2 A 2 3 3 A 3 4 4 A 4 5 5 A 5 6 6 A 6 7 1 B 7 8 2 B 8 9 3 B 9 10 4 B 10 11 5 B 11 12 6 B 12 13 1 C 13 14 2 C 14 15 3 C 15 16 4 C 16 17 5 C 17 18 6 C 18 19 1 D 19 20 2 D 20 21 3 D 21 22 4 D 22 23 5 D 23 24 6 D 24 25 1 E 25 26 2 E 26 27 3 E 27 28 4 E 28 29 5 E 29 30 6 E 30 31 1 F 31 32 2 F 32 33 3 F 33 34 4 F 34 35 5 F 35 36 6 F 36
> M2<-matrix(rnorm(25),nrow=5) > M2输出结果
[,1] [,2] [,3] [,4] [,5] [1,] 0.1811644 0.1186978 -0.48697926 -1.1266623 0.3416455 [2,] 0.3232652 1.4545730 -1.81291997 1.8850307 -1.7641560 [3,] 0.4408050 -0.1402909 -0.08482793 0.5007377 0.2754002 [4,] 2.9937629 -0.1804370 -0.05752013 -2.7011690 -0.1628883 [5,] -0.9448278 -0.2615532 -0.05046240 -0.9994324 1.4588645
> rownames(M2)<-c("R1","R2","R3","R4","R5")
> colnames(M2)<-c("C1","C2","C3","C4","C5")
> M2输出结果C1 C2 C3 C4 C5 R1 0.1811644 0.1186978 -0.48697926 -1.1266623 0.3416455 R2 0.3232652 1.4545730 -1.81291997 1.8850307 -1.7641560 R3 0.4408050 -0.1402909 -0.08482793 0.5007377 0.2754002 R4 2.9937629 -0.1804370 -0.05752013 -2.7011690 -0.1628883 R5 -0.9448278 -0.2615532 -0.05046240 -0.9994324 1.4588645
> as.data.frame(as.table(M2))输出结果
Var1 Var2 Freq 1 R1 C1 0.18116436 2 R2 C1 0.32326518 3 R3 C1 0.44080495 4 R4 C1 2.99376289 5 R5 C1 -0.94482784 6 R1 C2 0.11869776 7 R2 C2 1.45457299 8 R3 C2 -0.14029090 9 R4 C2 -0.18043699 10 R5 C2 -0.26155322 11 R1 C3 -0.48697926 12 R2 C3 -1.81291997 13 R3 C3 -0.08482793 14 R4 C3 -0.05752013 15 R5 C3 -0.05046240 16 R1 C4 -1.12666228 17 R2 C4 1.88503065 18 R3 C4 0.50073769 19 R4 C4 -2.70116904 20 R5 C4 -0.99943242 21 R1 C5 0.34164554 22 R2 C5 -1.76415604 23 R3 C5 0.27540019 24 R4 C5 -0.16288833 25 R5 C5 1.45886447