R - re-order columns based on match (template)

Question

So I have a large dataset that looks like this:

     V1       V2   V3         V4
1 Sleep Domestic  Eat Child Care
2 Sleep Domestic  Eat       Paid
3 Sleep Domestic  Eat Child Care
4 Sleep      Eat Paid       <NA>

What I would like to do is to reorder the columns based on a "template"

["Sleep", "Eat", "Domestic", "Paid", "Child care"] 

To get (ouput)

   V1    V2       V3      V4            V5
Sleep   Eat Domestic      NA    Child Care
Sleep   Eat Domestic    Paid            NA
Sleep   Eat Domestic      NA    Child Care
Sleep   Eat       NA    Paid            NA

So in columns 1 Sleep, columns 2 Eat, ...

I have no idea where to start with this. Any idea ?

data

x = structure(list(V1 = c("Sleep", "Sleep", "Sleep", "Sleep"), V2 = c("Domestic", 
"Domestic", "Domestic", "Eat"), V3 = c("Eat", "Eat", "Eat", "Paid"
), V4 = c("Child Care", "Paid", "Child Care", NA)), .Names = c("V1", 
"V2", "V3", "V4"), row.names = c(NA, 4L), class = "data.frame")

template = c('Sleep', 'Eat', 'Domestic', 'Paid', 'Child care')

Answer 1

Check the rowSums for each template value and then piece it together again:

template <- c("Sleep", "Eat", "Domestic", "Paid", "Child Care")
# i've fixed this template so the case matches the values for 'Child Care'

data.frame(lapply(
  setNames(template, seq_along(template)),
  function(v) c(NA,v)[(rowSums(x==v,na.rm=TRUE)>0)+1]
))

#     X1  X2       X3   X4         X5
#1 Sleep Eat Domestic <NA> Child Care
#2 Sleep Eat Domestic Paid       <NA>
#3 Sleep Eat Domestic <NA> Child Care
#4 Sleep Eat     <NA> Paid       <NA>

Or an alternative using pmax:

data.frame(
  lapply(
    setNames(template, seq_along(template)), 
    function(v) do.call(pmax, c(replace(x, x != v,NA),na.rm=TRUE)) 
  )
)