[R] Aggregating data

[David Winsemius]

On Aug 8, 2011, at 7:51 PM, Jeffrey Joh wrote:

>
> 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.
>

 > aggregate(results[, c("C_lo", "C_hi")], results["date"], median)
   date        C_lo        C_hi
1  719 0.003925818 0.006977558
2 1027 0.008223774 0.011320763
3 1030 0.008663793 0.019046317

dat <-.Last.value
  matplot(dat[1], dat[-1], type="b", ylim=with(results, range(c(C_lo,  
C_hi)) )  )
  with(results, points(date, C_lo))
  with(results, points(date, C_hi))

-- 
David.

>
>
> 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$n, na.rm=T)
> }
>
>
>
> Jeff
>
>
>
> ----------------------------------------
>> Date: Fri, 5 Aug 2011 11:59:37 -0700
>> Subject: Re: [R] Aggregating data
>> From: djmuser at gmail.com
>> To: johjeffrey at hotmail.com
>> CC: r-help at r-project.org
>>
>> Hi:
>>
>> This is the type of problem at which the plyr package excels. Write a
>> utility function that produces the plot you want using a data frame  
>> as
>> its input argument, and then do something like
>>
>> library('plyr')
>> d_ply(results, .(a, b, c), plotfun)
>>
>> where plotfun is a placeholder for the name of the name of your plot
>> function. The d in d_ply means to take a data frame as input and _
>> means return nothing. This is used in particular when a side effect,
>> such as a plot, is the desired 'output'. See
>> http://www.jstatsoft.org/v40/i01, which contains an example  
>> (baseball)
>> where groupwise plots are produced. (Don't actually run the example
>> unless you're willing to wait for 1100+ ggplots to be rendered :)
>>
>> If memory serves, you should also be able to produce graphics for  
>> each
>> data subset using the data.table package as well.
>>
>> If you want a more concrete solution, provide a more concrete  
>> example.
>>
>> HTH,
>> Dennis
>>
>> On Fri, Aug 5, 2011 at 9:55 AM, Jeffrey Joh  
>> <johjeffrey at hotmail.com> wrote:
>>>
>>>
>>> I aggregated my data: aggresults <-aggregate(results,  
>>> by=list(results$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 at 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.
>>> 		 	   		
> ______________________________________________
> R-help at 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.

David Winsemius, MD
West Hartford, CT