In `data.table` within R, is there a fast way to combine tables together?

Question

I am currently looking for a way to combine several tables together which have the same structure and column names. For example, I would like to combine these three tables:

>dt1
user     number
A        32
A        33
A        35
A        23
A        32
A        44
A        33

>dt2
user     number
B        32
B        33
B        35
B        23
B        32
B        44
B        33

>dt3
user     number
C        32
C        33
C        35
C        23
C        32
C        44
C        33

and get:

>dt_combined
user     number
A        32
A        33
A        35
A        23
A        32
A        44
A        33
B        32
B        33
B        35
B        23
B        32
B        44
B        33
C        32
C        33
C        35
C        23
C        32
C        44
C        33

I have been trying to use either join or merge, but as simple as this problem is, I can't seem to pinpoint the fast and easy solution within data.table. Would anyone have any suggestions? Thanks!

Answer 1

You've tagged this as data.table , which has a convenient function rbindlist .

You can use it in conjunction with mget , like this:

library(data.table)
rbindlist(mget(ls(pattern = "dt\\d")))

The mget step creates a list of the objects in your workspace matching a naming pattern like dt1 , dt2 , and so on ( dt + "digits"). rbindlist takes that list and makes it into one big data.table .

---

> print(rbindlist(mget(ls(pattern = "dt\\d"))), topn = 3)
    user number
 1:    A     32
 2:    A     33
 3:    A     35
---            
19:    C     32
20:    C     44
21:    C     33