R help - Jan 2005 - Function to modify existing data.frame

I'm used to statistical languages, such as Stata, in which it's trivial
to
pass a list of variables to a function & have that function modify those
variables in the existing dataset rather than create copies of the variables
or having to replace the entire dataset to change a few variables.  In R, I
suppose I could paste together the right instructions in a function and then
execute it, but is there any more straightforward way of doing this I'm
missing?

Thx,

Peter

On Tue, 2005-01-18 at 10:18 -0500, Peter Muhlberger
wrote:
> I'm used to statistical languages, such as Stata, in which it's
trivial to
> pass a list of variables to a function & have that function modify
those
> variables in the existing dataset rather than create copies of the
variables
> or having to replace the entire dataset to change a few variables.  In R, I
> suppose I could paste together the right instructions in a function and
then
> execute it, but is there any more straightforward way of doing this I'm
> missing?
> 
> Thx,
> 
> Peter

What type of modifications?

Take a look at:

?replace
?transform

HTH,

Marc Schwartz

On Tue, 18 Jan 2005, Peter Muhlberger wrote:
> I'm used to statistical languages, such as Stata, in which it's
trivial to
> pass a list of variables to a function & have that function modify
those
> variables in the existing dataset rather than create copies of the
variables
> or having to replace the entire dataset to change a few variables.  In R, I
> suppose I could paste together the right instructions in a function and
then
> execute it, but is there any more straightforward way of doing this I'm
> missing?
>
Yes and no.

This isn't so much a question of pass-by-reference, as one reply 
suggested, but of macros vs functions.

Stata is (largely) a macro language: it does operations on command strings 
and then evaluates them.  It's not that Stata programs work with 
references, it's that all objects (except local macros) are global.

  R is based on functions: it evaluates arguments and then operates on 
them.  When you have functions, with local variables, it then becomes 
relevant to ask whether the arguments to the function are just copies or 
are references to the real thing. In R they are just copies (from a 
language point of view) but are often references from an efficiency point 
of view.


There are two ways to get the effect you are looking for. I don't 
recommend either, though.


1) Store your variables in an environment, rather than a data frame. 
Environments are passed by reference.

2) The right combinations of eval() and substitute() and lazy evaluation 
make it possible to write macros in R.  There's an R Newsletter article 
about this.

 	-thomas