加盟v提供兩種dataframes用階乘組合

Question

我接下來的兩個數據幀：

table_1<-data.frame(col1=round(runif(10, 1, 10)), col2=round(runif(10, 1, 10)),col3=round(runif(10, 1, 10)),col4=round(runif(10, 1, 10)),col5=round(runif(10, 1, 10)),col6=round(runif(10, 1, 10))) 
table_2<-data.frame(col1=round(runif(10, 1, 10)), col2=round(runif(10, 1, 10)),col3=round(runif(10, 1, 10)),col4=round(runif(10, 1, 10)),col5=round(runif(10, 1, 10)),col5=round(runif(10, 1, 10))) 

comb<-lapply(1:6, function(n) combn(names(table_1),n)) 

[[1]] 
    [,1] [,2] [,3] [,4] [,5] [,6] 
[1,] "col1" "col2" "col3" "col4" "col5" "col6" 

[[2]] 
    [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] 
[1,] "col1" "col1" "col1" "col1" "col1" "col2" "col2" "col2" "col2" "col3" "col3" "col3" "col4" "col4" 
[2,] "col2" "col3" "col4" "col5" "col6" "col3" "col4" "col5" "col6" "col4" "col5" "col6" "col5" "col6" 
    [,15] 
[1,] "col5" 
[2,] "col6" 

[[3]] 
    [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] 
[1,] "col1" "col1" "col1" "col1" "col1" "col1" "col1" "col1" "col1" "col1" "col2" "col2" "col2" "col2" 
[2,] "col2" "col2" "col2" "col2" "col3" "col3" "col3" "col4" "col4" "col5" "col3" "col3" "col3" "col4" 
[3,] "col3" "col4" "col5" "col6" "col4" "col5" "col6" "col5" "col6" "col6" "col4" "col5" "col6" "col5" 
    [,15] [,16] [,17] [,18] [,19] [,20] 
[1,] "col2" "col2" "col3" "col3" "col3" "col4" 
[2,] "col4" "col5" "col4" "col4" "col5" "col5" 
[3,] "col6" "col6" "col5" "col6" "col6" "col6" 

而我想要做的是加入使用張貼在「梳狀」所有組合的兩個表。因此，使用梳狀的第一個匹配[[1]]（只有一個組合）將是：

table_1$col1=table_2$col1 or table_1$col2=table_2$col2 or table_1$col3=table_2$col3 or .... 

第二組合（梳[[2]]）將是

table_1$col1=table_2$col1 and table_1$col2=table_2$col2) or (table_1$col1=table_2$col1 or table_1$col3=table_2$col3) .. and so on. 

誰能幫助我與此。

Answer 1

lapply(comb, function(y) 
      lapply(1:ncol(y),function(x) 
        data.frame(table_1[y[,x]], table_2[y[,x]]) 
      ) 
     ) 

這會給你data.frame的嵌套列表是採取組合來創建一個數據幀，例如

[[2]] 
[[2]][[1]] 
    col1 col2 col1.1 col2.1 
1  6 9  4  7 
2  3 7  4  2 
3  4 8  10  5 
4  5 9  5  5 
5  4 9  9  8 
6  6 3  3  3 
7  9 7  2  6 
8  2 5  5  9 
9  5 6  2  9 
10 10 4  2  7