Have you tried 'do.call(rbind,....)'? You did not provide a subset of
data, so it is hard to create an example.
On Mon, Nov 10, 2008 at 4:28 PM, Stavros Macrakis <[EMAIL PROTECTED]> wrote:
> I have a dataset of about 10^6 rows, each consisting of a timestamp,
> several factors, a string, some integers, and some floats.
>
> I'd like to graph this data in various ways, including straightforward
> ones (how many events per week over the past year for each of 4 values
> of some factor), some less straightforward. I've managed to do this
> by brute force, but I'd like to learn how to do it in more elegant,
> more R-like code.
>
> Consider for example the following, which graphs the 25th, 50th, and
> 75th percentile values per day of data$x
>
> perc <- function(code,data)
> { # select the part of the data with factor value
> slice <- data[data$factor == code,];
> # calc quartiles for each day
> quarts <- tapply(slice$x,
> slice$day,
> function(x) quantile(x,c(.25,.50,.75)));
> # returns a tagged list of tagged vectors
> # list("2008-10-07" = c("25%" = .05, "50%" = .47,
> ... ) , ...)
> # convert to a data frame -- is there some mapping function to do this?
> fr <- data.frame( day = to.time(names(quarts)), # strings
> back to dates (!)
> "25%" = sapply(quarts, function(x)
> x[[1]] ), # !!
> "50%" = sapply(quarts, function(x) x[[2]] ),
> "75%" = sapply(quarts, function(x) x[[3]] ) );
> # columns are now labelled "X25." etc. (!)
> for (i in 2:4) { plot( fr$day, res[[2]], type="l", ylim= c( 0,
> max(pmax(fr[[1]],fr[[2]],fr[[3]] )) ));
> par(new=TRUE); }
> par(new=FALSE);
> }
>
> This works, but is pretty ugly in a variety of ways. What is the
> right way to do this?
>
> Thanks,
>
> -s
>
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>
--
Jim Holtman
Cincinnati, OH
+1 513 646 9390
What is the problem that you are trying to solve?
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