unstack a data frame in R

Question

I have a stacked data frame

a <- c(1,1,1,1,2,2,3,3,3,3,3,4,4,4,4)  
b <- c(200,201,201,200,220,220,200,220,203,204,204,203,220,200,200)  
d <- c(500,500,500,500,500,501,501,501,501,501,502,502,502,502,502)  
f <- c("G","G","M","M", "G","G","M","M","M","G","M","G","M","G","G")  
df <- data.frame(a,d,b,f)

I use dcast from reshape2 to unstack the data as follows

dcast(df,a+d+b ~ f)   
      a     d   b G M  
1     1   500 200 1 1  
2     1   500 201 1 1  
3     2   500 220 1 0  
4     2   501 220 1 0  
5     3   501 200 0 1  
6     3   501 203 0 1  
7     3   501 204 1 0  
8     3   501 220 0 1  
9     3   502 204 0 1  
10    4   502 200 2 0  
11    4   502 203 1 0  
12    4   502 220 0 1

It defaults to length since I have not put any aggregating function. What I would like however is to get

a   d   b col_1 col_2  
1 500 200    G     M  
1 500 201    G     M  
2 500 220    G    NA  
...and so on  

I want to "widen" or unstack the data frame by transposing column f for a particular a+d+b combination and appending it to the frame. Is there an elegant way without having to loop through the combinations?

EDIT: Not necessarily just 2 levels G & M in col f. I just want to put up col_1 col_2 col_3 which will transpose out the column f per unique a+d+b combination. I've done it with a for loop; but with a large data set it is unwieldy. I was looking to make the code quicker!

Answer 1

dcast(df, a+d+b ~ f, fun.aggregate = function(x) as.character(x)[1])
#Using f as value column: use value.var to override.
#   a   d   b    G    M
#1  1 500 200    G    M
#2  1 500 201    G    M
#3  2 500 220    G <NA>
#4  2 501 220    G <NA>
#5  3 501 200 <NA>    M
#6  3 501 203 <NA>    M
#7  3 501 204    G <NA>
#8  3 501 220 <NA>    M
#9  3 502 204 <NA>    M
#10 4 502 200    G <NA>
#11 4 502 203    G <NA>
#12 4 502 220 <NA>    M

Re comment: perhaps you want this then:

library(data.table)
dt = data.table(df)

dt[, lapply(1:3, function(i) as.character(f)[i]), by = list(a, d, b)]
#    a   d   b V1 V2 V3
# 1: 1 500 200  G  M NA
# 2: 1 500 201  G  M NA
# 3: 2 500 220  G NA NA
# 4: 2 501 220  G NA NA
# 5: 3 501 200  M NA NA
# 6: 3 501 220  M NA NA
# 7: 3 501 203  M NA NA
# 8: 3 501 204  G NA NA
# 9: 3 502 204  M NA NA
#10: 4 502 203  G NA NA
#11: 4 502 220  M NA NA
#12: 4 502 200  G  G NA