[R] proper way to process dataframe by rows

[Gabor Grothendieck]

Jack Tanner <ihok <at> hotmail.com> writes:

: 
: This is a best practices / style question.
: 
: The way I use RODBC is I something like this:
: 
:  > foo <- sqlQuery(db, "select * from foo")
:  > apply(foo, 1, function{...})
: 
: That is, I use apply to iterate over each result -- row -- in the 
: RODBC-produced dataframe. Is this how one generally wants to do this?
: 
: My concern is that when apply iterates over the rows, it uses 
: as.matrix() to convert the dataframe to a character representation of 
: itself. Thus my database's carefully planned data types (that RODBC 
: carefully preserved when returning query results) get completely lost as 
: I process the data. I've taken to judiciously sprinkling as.numeric() 
: and friends here and there, but this is just begging for bugs.
: 
: In other words, what is the smart way to process a dataframe by rows? Or 
: is there, by chance, a specific technique or practice that is available 
: for RODBC results but not for dataframes in general?
: 

Don't know about the best way but here is one way that does not 
convert to charadter:

R> data(iris)
R> irish <- head(iris)
R> irish
  Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1          5.1         3.5          1.4         0.2  setosa
2          4.9         3.0          1.4         0.2  setosa
3          4.7         3.2          1.3         0.2  setosa
4          4.6         3.1          1.5         0.2  setosa
5          5.0         3.6          1.4         0.2  setosa
6          5.4         3.9          1.7         0.4  setosa
R> f <- function(i) with(irish[i,], Sepal.Length + Sepal.Width)
R> sapply(1:nrow(irish), f)
[1] 8.6 7.9 7.9 7.7 8.6 9.3