[R] How to quickly convert a data.frame into a structure of lists

[Duncan Murdoch]

I would use the tapply function (which is designed for the case in which 
data exists for most pairs of the levels of A and B) or the 
reshape::sparseby function, or something else in the reshape package. 
These won't give you exactly the structure you were asking for, but they 
will separate the data properly.

By the way, it's a good idea when posting a question to post a simple 
example; then other solutions can be illustrated on the same example. 
It doesn't need to contain millions of rows.

Duncan Murdoch

On 11-08-09 8:58 PM, Frederic F wrote:
 > Hello,
 >
 > This is my first project in R, so I'm trying to work 'the R way', but it
 > still feels awkward sometimes.
 >
 > The problem that I'm facing right now is that I need to convert a 
data.frame
 > into a structure of lists. The data.frame has columns in the order of 
tens
 > (I need to focus on only three of them) and rows in the order of 
millions.
 > So it's quite a big dataset.
 > Let say that the columns of interest are A, B and C. I need to take the
 > data.frame and construct a structure of list where I have a list for 
every
 > level of A, those list all contain lists for every levels of B, and the
 > 'b-lists' contains all the values of C that match the corresponding 
levels
 > of A and B.
 > So, I should be able to write something like this:
 >> MyData at list_structure$x_level_of_A$y_level_of_B
 > and get a vector of the values of C that were on rows where 
A=x_level_of_A
 > and B=y_level_of_B.
 >
 > My first attempt was to use two imbricated "lapply" functions running
 > something like this:
 >
 > list_structure<-lapply(levels(A) function(x) {
 >    as.character(x) = lapply( levels(B), function(y) {
 >      as.character(y) = C[A==x&  B==y]
 >    })
 > })
 >
 > The real code was not quite as simple, but I managed to have it work, 
and it
 > worked well on my first dataset (where A and B had only few levels). 
I was
 > quite happy... but the imbricated loops killed me on a second dataset 
where
 > A had several thousand levels. So I tried something else.
 >
 > My second attempt was to go through every row of the data.frame and 
append
 > the value to the appropriate vector.
 >
 > I first initialized a structure of lists ending with NULL vector, 
then I did
 > something like this:
 >
 > for (i in 1:nrow(DataFrame)) {
 >    eval(
 >      substitute(
 >        append(MyData at list_structure$a_value$b_value, c_value),
 >        list(a_value=as.character(DF$A[i]), b_value=as.character(DF$B[i]),
 > c_value=as.character(DF$C[i]))
 >      )
 >    )
 > }
 >
 > This works... but way too slowly for my purpose.
 >
 > I would like to know if there is a better road to take to do this
 > transformation. Or, if there is a way of speeding one of the two 
solutions
 > that I have tried.
 >
 > Thank you very much for your help!
 >
 > (And in your replies, please remember that this is my first project 
in R, so
 > don't hesitate to state the obvious if it seems like I am missing it!)
 >
 > Frederic
 >
 > --
 > View this message in context: 
http://r.789695.n4.nabble.com/How-to-quickly-convert-a-data-frame-into-a-structure-of-lists-tp3731746p3731746.html
 > Sent from the R help mailing list archive at Nabble.com.
 >
 > ______________________________________________
 > R-help at r-project.org mailing list
 > https://stat.ethz.ch/mailman/listinfo/r-help
 > PLEASE do read the posting guide 
http://www.R-project.org/posting-guide.html
 > and provide commented, minimal, self-contained, reproducible code.