r - 对齐R中字符矩阵中的行

Question

我有一个结构如下的字符矩阵:

dog    1   cow    9     mouse  7 
bird   10  tiger  1     gnu    2
tiger  3   deer   7     deer   27
skunk  2   rat    50    NA     NA
mouse  8   snake  3     NA     NA 
cow    7   NA     NA    NA     NA
sheep  21  NA     NA    NA     NA 
gnu    5   NA     NA    NA     NA 

想象这是一个语言环境中的动物矩阵，每个语言环境的数据由连续的列对定义。有些动物可能在语言环境中很常见，但语言环境也可能有独特的动物。最终我想制作这些数据的热图，因此需要重新排序这个矩阵以具有一个结构，其中所有类型的动物都有一列，每个区域的数字对应的连续列:

dog    1    NA    NA 
tiger  3    1     NA 
skunk  2    NA    NA
mouse  8    NA    NA
cow    7    9     NA
sheep  21   NA    NA
gnu    5    NA    2
deer   NA   7     27
rat    NA   50    NA
snake  NA   3     NA
mouse  NA   NA    7
bird   10   NA    NA

换句话说，我有

A1 <- c("dog", "bird", "tiger", "skunk", "mouse", "cow", "sheep", "gnu")
B1 <- as.character(c(1, 10, 3, 2, 8, 7, 21, 5))
A2 <- c("cow", "tiger", "deer", "rat", "snake", NA, NA, NA)
B2 <- as.character(c(9, 1, 7, 50, 3, NA, NA, NA))
A3 <- c("mouse", "gnu", "deer", NA, NA, NA, NA, NA)
B3 <- as.character(c(7, 2, 27, NA, NA, NA, NA, NA))
TheMatrix <- cbind(A1, B1, A2, B2, A3, B3)

并且想要

a1 <- c("dog", "tiger", "skunk", "mouse", "cow", "sheep", "gnu", "deer", "rat", "snake", "mouse", "bird")
b1 <- as.character(c(1, 3, 2, 8, 7, 21, 5, NA, NA, NA, NA, 10))
b2 <- as.character(c(NA, 1, NA, NA, 9, NA, NA, 7, 50, 3, NA, NA))
b3 <- as.character(c(NA, NA, NA, NA, NA, NA, 2, 27, NA, NA, 7, NA))
DesiredResult <- cbind(a1, b1, b2, b3)

关于如何实现这种重组的想法？它可以通过循环和会计来完成，但肯定有一种我缺少的更优雅的方式。

Answer 1

library(reshape2)

ncols = ncol(TheMatrix)
nrows = nrow(TheMatrix)

dcast(as.data.frame(na.omit(cbind(c(TheMatrix[,seq(1,ncols,2)]),
                                  c(TheMatrix[,seq(2,ncols,2)]),
                                  rep(colnames(TheMatrix)[seq(2,ncols,2)],
                                      each = nrows)))),
      V1 ~ V3, value.var = 'V2')
#      V1   B1   B2   B3
#1   bird   10 <NA> <NA>
#2    cow    7    9 <NA>
#3   deer <NA>    7   27
#4    dog    1 <NA> <NA>
#5    gnu    5 <NA>    2
#6  mouse    8 <NA>    7
#7    rat <NA>   50 <NA>
#8  sheep   21 <NA> <NA>
#9  skunk    2 <NA> <NA>
#10 snake <NA>    3 <NA>
#11 tiger    3    1 <NA>

这里发生了很多事情(每一个都非常简单)，要理解，只需自行运行每一点(从内部开始并走出去)。