[R] Forloop/ifelse program problem and list of dataframes

[Ivan Calandra]

Hi Ian,

I haven't read in details because you don't provide a reproducible 
example (see ?dput) but you might want to take a look at the aggregate() 
and doBy::summaryBy() functions.

HTH,
Ivan

--
Ivan CALANDRA
Université de Bourgogne
UMR CNRS/uB 6282 Biogéosciences
6 Boulevard Gabriel
21000 Dijon, FRANCE
+33(0)3.80.39.63.06
ivan.calandra at u-bourgogne.fr
http://biogeosciences.u-bourgogne.fr/calandra


Le 21/03/12 16:44, Ian Craig a écrit :
> Hello R Community,
>
> I don't post to these things often so excuse me if I stumble on my forum
> etiquette.  This is a complex problem for me, which may require two forum
> entries, but I will try my best to be concise.   Also, I am a self taught
> coder, so if my code is not to convention, your constructive criticism is
> always welcome.
>
> I need to split up a data frame by participant (gpsarc - factor), status
> (testpo - factor), and by date (LocalDate), then sum the distance
> (Dist_Bef_m - numeric) records for each date and average them across each
> status state for each participant.  Each participant has several records
> for each date and for at least 1 of 3 different possible status types (max
> 3).   In the end, I want a table with participant number and the status
> state as my column headings with means for each status state under their
> appropriate heading (see example below).  I am confident I made this way
> more complicated than it needs to be.  I really appreciate any help you can
> offer.
>
> Here is my relevant coding so far:
>
> s1<- split(data[,c(4,10,20,42)], data$gpsarc)
>    for(i in 1:length(s1))
> s1[[i]]<- split(s1[[i]],s1[[i]]$testpo)
>    s2<- vector("list", length(s1))
>    for(i in 1:length(s2))
>     s2[[i]]<- ldply(s1[[i]],
> function(x)
>   {
>    if(nrow(x) == 0)  ####  if one status state does not exist, but still
> accounted in the split sublist because its a factor, I would get an error,
> so I added this If/Else portion to remove those entries with no records
>     {
>      remove(x)
>     }
>    else
>     {
>      by(x, x[["LocalDate"]],
>   function(x1)
> {
>   sum(x1[["Dist_Bef_m"]])
>   })
>       }
>    })
>
> s3<- vector("list", length(s2))
>    for(i in 1:length(s3))
>    s3[[i]]<- data.frame(mean = apply(s2[[i]][,-1],1,mean,na.rm=TRUE),
> row.names = as.character(s2[[i]][,1]))
>
> here is a sample of the s3 result:
>
> [[1]]
>       mean
> 2 12533.2
>
> [[2]]
>        mean
> 2 26300.96
> 3 25313.93
>
> [[3]]
>        mean
> 1 48489.15
> 3 27398.23
>
> [[4]]
>        mean
> 1 34783.97
>
> [[5]]
>        mean
> 1 21293.19
> 2 21962.41
> 3 18272.67
>
> ##### I really want it to look like this:
>
>   ppt     1                   2                 3
> 1          NA               12533.2     NA
> 2          NA               26300.96   25313.93
> 3          48489.15    NA              27398.23
> 4          34783.97    NA              NA
> 5          21293.19    21962.41   18272.67
>
> 	[[alternative HTML version deleted]]
>
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>
>