Here is a sample of what I'm trying to do:
structure(list(C_lo = c(0.00392581816943354, 0.00901222644518829,
0.00484396253385175, 0.00822377400482716, 0.00780070460187192,
0.00952688235337435), C_hi = c(0.00697755827622381, 0.0123301031600017,
0.0113207627868435, 0.0112887993422598, 0.018567245397701, 0.0195253894885054
), house = c(1, 1, 1, 1, 1, 1), date = c(719, 1027, 1027,
1027, 1030, 1030), hour = c(18, 8, 8, 8, 11, 11), .Names = c("1000",
"10000",
"10001", "10002", "10003", "10004"), press = structure(c(1L,
1L, 1L, 1L, 1L, 1L), .Names = c("1000", "10000",
"10001", "10002", "10003", "10004"), .Label = c("DEPR",
"PRESS"), class = "factor")), .Names = c("C_lo", "C_hi",
"house", "date", "hour", "number", "press"
), class = "data.frame", row.names = c("1000", "10000",
"10001", "10002", "10003", "10004"))
I'd like to aggregate the data by the date. I'd like to have a table with the
median C_lo and C_hi values grouped by date.
I'd also like to plot these points with date on the x-axis, C on y-axis, and
lines going through these medians.
For plyr, would it be something like: ddply(results, .(date),median, na.rm=T)
I tried making a for loop to get the medians, but that doesn't work either.
splitresults = split (results, results$date, drop=T)
mediann <- matrix (,seq_along(splitresults),2)
for (i in seq_along(splitresults)) {
piece <- splitresults[[i]]
mediann [i,1] <- unique(piece$date)
mediann [i,2] <- median (piece$n, na.rm=T)
}
Jeff
----------------------------------------
> Date: Fri, 5 Aug 2011 11:59:37 -0700
> Subject: Re: [R] Aggregating data
> From: djmu...@gmail.com
> To: johjeff...@hotmail.com
> CC: r-help@r-project.org
>
> Hi:
>
> This is the type of problem at which the plyr package excels. Write a
> utility function that produces the plot you want using a data frame as
> its input argument, and then do something like
>
> library('plyr')
> d_ply(results, .(a, b, c), plotfun)
>
> where plotfun is a placeholder for the name of the name of your plot
> function. The d in d_ply means to take a data frame as input and _
> means return nothing. This is used in particular when a side effect,
> such as a plot, is the desired 'output'. See
> http://www.jstatsoft.org/v40/i01, which contains an example (baseball)
> where groupwise plots are produced. (Don't actually run the example
> unless you're willing to wait for 1100+ ggplots to be rendered :)
>
> If memory serves, you should also be able to produce graphics for each
> data subset using the data.table package as well.
>
> If you want a more concrete solution, provide a more concrete example.
>
> HTH,
> Dennis
>
> On Fri, Aug 5, 2011 at 9:55 AM, Jeffrey Joh <johjeff...@hotmail.com> wrote:
> >
> >
> > I aggregated my data: aggresults <-aggregate(results, by=list(results$a,
> > results$b, results$c), FUN=mean, na.rm=TRUE)
> >
> >
> >
> > results has about 8000 lines of data, and aggresults has about 80 lines. I
> > would like to create a separate variable for each of the 80 aggregates,
> > each containing the 100 lines that were aggregated. I would also like to
> > create plots for each of those 80 datasets.
> >
> >
> >
> > Is there a way of automating this, so that I don't have to do each of the
> > 80 aggregates individually?
> >
> >
> >
> > Jeff
> > ______________________________________________
> > R-help@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.
> >
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