Xtykutl

I have a list containing two matrices:

a <- list("m1"=matrix(1:9, nrow = 3, ncol = 3),

          "m2"=matrix(1:9, nrow = 3, ncol = 3))

I want to bind the two matrices (row-bind), and to distinguish the rows, I want to add a column that contains the name of the matrix. I can bind the rows using r bind:

b <- do.call(rbind, a) %>% as.data.frame

which yields

  V1 V2 V3

1  1  4  7

2  2  5  8

3  3  6  9

4  1  4  7

5  2  5  8

6  3  6  9

But how do I add a column containing the names? I can do b$id <- c("m1","m1","m1","m2","m2","m2"), but there must be an easier way than this (?)

Here's how to do it in dplyr / purrr

a %>% purrr::map(as.data.frame) %>% dplyr::bind_rows(.id = "origin")

  origin V1 V2 V3

1     m1  1  4  7

2     m1  2  5  8

3     m1  3  6  9

4     m2  1  4  7

5     m2  2  5  8

6     m2  3  6  9

That converts the matrices to data-frames before row-binding them.

You can use bind_rows on a list of matrices. But it doesn't return what you expect.

a %>% bind_rows(.id = "origin")

# A tibble: 9 x 3

  origin    m1    m2

  <chr>  <int> <int>

1 1          1     1

2 1          2     2

3 1          3     3

4 1          4     4

5 1          5     5

6 1          6     6

7 1          7     7

8 1          8     8

9 1          9     9

This happens because m1 and m2 are vectors (because they are matrices) of the same length, and bind_rows sees a list of constant-length vectors as a single data-frame. So the latter call is equivalent to

bind_rows(data.frame(m1 = as.vector(m1), m2 = as.vector(m2)), .id = "origin")

So, make sure you convert your matrices to data.frames before you bind them together.

You can do:

b <- do.call(rbind.data.frame, a)



#     V1 V2 V3

#m1.1  1  4  7

#m1.2  2  5  8

#m1.3  3  6  9

#m2.1  1  4  7

#m2.2  2  5  8

#m2.3  3  6  9

or if you not happy with this,

b    <- do.call(rbind.data.frame, a)

b$id <- sub("[.].+", "", rownames(b))



#     V1 V2 V3 id

#m1.1  1  4  7 m1

#m1.2  2  5  8 m1

#m1.3  3  6  9 m1

#m2.1  1  4  7 m2

#m2.2  2  5  8 m2

#m2.3  3  6  9 m2