Merge data sets by row differening columns [duplicate]

Question

I have the need to merge data sets by row but they have differing columns. How can I easily get R to merge the rows, add missing columns and fill in the missing columns with NAs? Currently I would do it like this (very time consuming for multiple merges):

Creating fake data...

x1<-LETTERS[1:3]
x2<-letters[1:3]
x3<-rnorm(3)
x4<-rnorm(3)
x5<-rnorm(3)

Example of multiple data.frames with some similar columns, some different...

data.frame(x1,x2,x3,x4,x5)
data.frame(x1,x3,x4,x5)
data.frame(x2,x3,x4,x5)
data.frame(x1,x2,x3,x4,x5)

How I merge it now...

DF<-data.frame(rbind(data.frame(x1,x2,x3,x4,x5),
data.frame(x1,x2,x3,x4,x5),
data.frame("x2"=rep(NA,3),data.frame(x1,x3,x4,x5)),
data.frame("x1"=rep(NA,3),data.frame(x2,x3,x4,x5))))

DF

EDIT: I tried the suggested code as follows:

l <- list(data.frame(x1,x2,x3,x4,x5),
          data.frame(x1,x3,x4,x5),
          data.frame(x2,x3,x4,x5),
          data.frame(x1,x2,x3,x4,x5))

merger <- function(l) lapply(2:length(l), function(x) merge(l[[x-1]], l[[x]], all=TRUE)) 
while (length(l) != 1) l<-merger(l) 

l

Which yields:

[[1]]
  x1       x3      x4        x5 x2
1  A  0.25492 0.30160  0.259287  a
2  B -0.25937 0.45936 -0.075415  b
3  C -0.53493 1.18316  0.627335  c

Not:

> DF
     x1   x2       x3      x4        x5
1     A    a  0.25492 0.30160  0.259287
2     B    b -0.25937 0.45936 -0.075415
3     C    c -0.53493 1.18316  0.627335
4     A    a  0.25492 0.30160  0.259287
5     B    b -0.25937 0.45936 -0.075415
6     C    c -0.53493 1.18316  0.627335
7     A <NA>  0.25492 0.30160  0.259287
8     B <NA> -0.25937 0.45936 -0.075415
9     C <NA> -0.53493 1.18316  0.627335
10 <NA>    a  0.25492 0.30160  0.259287
11 <NA>    b -0.25937 0.45936 -0.075415
12 <NA>    c -0.53493 1.18316  0.627335

EDIT 2: Sorry to extend my original post but my low rep will not allow me to answer my own question.

Combining Jaron and daroczig's responses results in exactly what I want. I don't want to assign each data frame to an object, so combining them as a list and then using rbind fill works very nicely (see code below)

Thank you to both of you!

x1<-LETTERS[1:3] 
x2<-letters[1:3] 
x3<-rnorm(3) 
x4<-rnorm(3) 
x5<-rnorm(3)

DFlist<-list(data.frame(x1,x2,x3,x4,x5), 
             data.frame(x1,x3,x4,x5),
             data.frame(x2,x3,x4,x5), 
             data.frame(x1,x2,x3,x4,x5))

rbind.fill(DFlist) 

Answer 1

I had to read your question quite a few times before I understood what you were looking for, but maybe you want rbind.fill from plyr:

d1 <- data.frame(x1,x2,x3,x4,x5)
d2 <- data.frame(x1,x3,x4,x5)
d3 <- data.frame(x2,x3,x4,x5)
d4 <- data.frame(x1,x2,x3,x4,x5)

> rbind.fill(d1,d4,d2,d3)
     x1   x2        x3         x4         x5
1     A    a 1.1216923  0.9236393  0.2749292
2     B    b 1.1913278  1.1145664 -0.5070576
3     C    c 0.2837657 -0.6631544 -1.0675885
4     A    a 1.1216923  0.9236393  0.2749292
5     B    b 1.1913278  1.1145664 -0.5070576
6     C    c 0.2837657 -0.6631544 -1.0675885
7     A <NA> 1.1216923  0.9236393  0.2749292
8     B <NA> 1.1913278  1.1145664 -0.5070576
9     C <NA> 0.2837657 -0.6631544 -1.0675885
10 <NA>    a 1.1216923  0.9236393  0.2749292
11 <NA>    b 1.1913278  1.1145664 -0.5070576
12 <NA>    c 0.2837657 -0.6631544 -1.0675885

Answer 2

Using data.table::rbindlist with fill = TRUE option:

data.table::rbindlist(
  list(data.frame(x1,x2,x3,x4,x5), 
       data.frame(x1,x3,x4,x5),
       data.frame(x2,x3,x4,x5), 
       data.frame(x1,x2,x3,x4,x5)),
  fill = TRUE)