How to simplify this R code to rbind all the tables of a list?

Question

There must a easy way to rbind all the tables in a list, how to do it?

rbind(tempOut[[1]], tempOut[[2]], tempOut[[3]], tempOut[[4]], 
                 tempOut[[5]], tempOut[[6]], tempOut[[7]], tempOut[[8]], 
                 tempOut[[9]], tempOut[[10]], tempOut[[11]], tempOut[[12]],
                 tempOut[[13]], tempOut[[14]], tempOut[[15]], tempOut[[16]],
                 tempOut[[17]], tempOut[[18]], tempOut[[19]], tempOut[[20]],
                 tempOut[[21]], tempOut[[22]], tempOut[[23]], tempOut[[24]],
                 tempOut[[25]], tempOut[[26]], tempOut[[27]], tempOut[[28]], 
                 tempOut[[29]], tempOut[[30]], tempOut[[31]], tempOut[[32]])

You can try `dplyr::bind_rows`. If you can provide sample data, may be solution can be fine-tuned. — MKR, Jun 30 '18 at 12:23

G. Grothendieck · Accepted Answer · 2018-06-30T13:37:27.603

1) do.call Using the first line to provide reproducible test input (where BOD is a builtin 6 row data frame) we use do.call with rbind as shown. No packages are used.

tempOut <- list(BOD, 10*BOD, 100*BOD) # test input

do.call("rbind", tempOut)

giving:

   Time demand
1     1    8.3
2     2   10.3
3     3   19.0
4     4   16.0
5     5   15.6
6     7   19.8
7    10   83.0
8    20  103.0
9    30  190.0
10   40  160.0
11   50  156.0
12   70  198.0
13  100  830.0
14  200 1030.0
15  300 1900.0
16  400 1600.0
17  500 1560.0
18  700 1980.0

2) Reduce A second base alternative is:

Reduce("rbind", tempOut)

3) packages There are also some packages which provide this functionality including rbindlist in data.table, bind_rows in dplyr and rbind.fill in plyr.

3a) purrr::map_dfr Of particular interest if you want to keep track of which table each row came from is the purrr solution -- also note that data.table's rbindlist has an idcol= argument as per @Henrik's comment.

library(dplyr) # map_dfr from purrr also requires dplyr
library(purrr)
map_dfr(tempOut, identity, .id = "id")

giving:

   id Time demand
1   1    1    8.3
2   1    2   10.3
3   1    3   19.0
4   1    4   16.0
5   1    5   15.6
6   1    7   19.8
7   2   10   83.0
8   2   20  103.0
9   2   30  190.0
10  2   40  160.0
11  2   50  156.0
12  2   70  198.0
13  3  100  830.0
14  3  200 1030.0
15  3  300 1900.0
16  3  400 1600.0
17  3  500 1560.0
18  3  700 1980.0

Regarding "_Of particular interest if you want to keep track of which table each row came_", `data.table::rbindlist` has `id.col` argument, and `dplyr::bind_rows` has `.id` argument. — Henrik, Jun 30 '18 at 12:53

How to simplify this R code to rbind all the tables of a list?

1 Answers1