Dealing with repetitive tasks in R

Question

I often find myself having to perform repetitive tasks in R. It gets extremely frustrating having to constantly run the same function on one or more data structures over and

Answer 1

If the names are similar you could iterate over them using the pattern argument to ls:

for (i in ls(pattern="df")){
  assign(paste("t",i,sep=""),na.omit(get(i)))
}

However, a more "R" way of doing it seems to be to use separate environment and eapply:

# setup environment
env <- new.env()

# copy dataframes across (using common pattern)
for (i in ls(pattern="df")){
  asssign(i,get(i),envir=env)
  }

# apply function on environment
eapply(env,na.omit)

Which yields:

$df3
     Region variable value
1      Asia     2006   300
2    Africa     2006   200
3    Europe     2006   200
4 N.America     2006   500
5 S.America     2006   300

$df2
     Region variable value
1      Asia     2005    55
2    Africa     2005   350
3    Europe     2005    40
4 N.America     2005    90
5 S.America     2005    99

$df1
     Region variable value
1      Asia     2004    35
2    Africa     2004    20
3    Europe     2004    20
4 N.America     2004    50
5 S.America     2004    30

Unfortunately, this is one huge list so getting this out as seperate objects is a little tricky. Something on the lines of:

lapply(eapply(env,na.omit),function(x) assign(paste("t",substitute(x),sep=""),x,envir=.GlobalEnv))

should work, but the substitute is not picking out the list element names properly.