R help - Jun 2007 - speed issues / pros & cons: dataframe vs. matrix

I've read that certain operations performed on a matrix (e.g. ribind, cbind)
are often much faster compared to operations performed on a data frame.

Other then the "bind functions", what are the main operations that are
significantly faster on a a matrix?

I know that data frames allow for columnnames and rownames, and that each column
in a data frame can have different data types.  Are there any other advantages
of storing data in a a dataframe rather then a matrix?

       
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On 22/06/2007 6:21 PM, Thomas Pujol wrote:
> I've read that certain operations performed on a matrix (e.g. ribind,
cbind) are often much faster compared to operations performed on a data frame.
> 
> Other then the "bind functions", what are the main operations
that are significantly faster on a a matrix?
Indexing (e.g. x[1,3]) is much faster on a matrix.
> 
> I know that data frames allow for columnnames and rownames, and that each
column in a data frame can have different data types.  Are there any other
advantages of storing data in a a dataframe rather then a matrix?
Data frames are lists, so you can use things like df$columnname, 
with(df, expression), attach(df), etc.  Data frame columns have names, 
but matrices don't necessarily.

I'd generally use data frames in any situation where the rows are cases 
and the columns are characteristics, until I found they were too slow: 
and then I'd consider temporary conversion to a matrix to speed things 
up.  As Knuth said, premature optimization is the root of all evil.

Duncan Murdoch