[R] Summary information by groups programming assitance
Gabor Grothendieck
ggrothendieck at gmail.com
Tue Dec 23 01:15:42 CET 2008
Here are two solutions assuming DF is your data frame:
# 1. aggregate is in the base of R
aggregate(DF[c("Length", "vol")], DF[c("Lake", "psd")], max)
or the following which is the same except it labels psd as Category:
aggregate(DF[c("Length", "vol")], with(DF, list(Lake = Lake, Category
= psd)), max)
# 2. sqldf. The sqldf package allows specification using SQL notation:
library|(sqldf)
sqldf("select Lake, psd as Category, max(Length), max(vol) from DF
group by Lake, psd")
There are many other good solutions too using various packages which
have already
been mentioned on this thread.
On Mon, Dec 22, 2008 at 4:51 PM, Ranney, Steven
<steven.ranney at montana.edu> wrote:
> All -
>
> I have data that looks like
>
> psd Species Lake Length Weight St.weight Wr
> Wr.1 vol
> 432 substock SMB Clear 150 41.00 0.01 95.12438
> 95.10118 0.0105
> 433 substock SMB Clear 152 39.00 0.01 86.72916
> 86.70692 0.0105
> 434 substock SMB Clear 152 40.00 3.11 88.95298
> 82.03689 3.2655
> 435 substock SMB Clear 159 48.00 0.04 92.42095
> 92.34393 0.0420
> 436 substock SMB Clear 159 48.00 0.01 92.42095
> 92.40170 0.0105
> 437 substock SMB Clear 165 47.00 0.03 80.38023
> 80.32892 0.0315
> 438 substock SMB Clear 171 62.00 0.21 94.58105
> 94.26070 0.2205
> 439 substock SMB Clear 178 70.00 0.01 93.91912
> 93.90571 0.0105
> 440 substock SMB Clear 179 76.00 1.38 100.15760
> 98.33895 1.4490
> 441 S-Q SMB Clear 180 75.00 0.01 97.09330
> 97.08035 0.0105
> 442 S-Q SMB Clear 180 92.00 0.02 119.10111
> 119.07522 0.0210
> ...
> [truncated]
>
> where psd and lake are categorical variables, with five and four
> categories, respectively. I'd like to find the maximum vol and the
> lengths associated with each maximum vol by each category by each lake.
> In other words, I'd like to have a data frame that looks something like
>
> Lake Category Length vol
> Clear substock 152 3.2655
> Clear S-Q 266 11.73
> Clear Q-P 330 14.89
> ...
> Pickerel substock 170 3.4965
> Pickerel S-Q 248 10.69
> Pickerel Q-P 335 25.62
> Pickerel P-M 415 32.62
> Pickerel M-T 442 17.25
>
>
> In order to originally get this, I used
>
> with(smb[Lake=="Clear",], tapply(vol, list(Length, psd),max))
> with(smb[Lake=="Enemy.Swim",], tapply(vol, list(Length, psd),max))
> with(smb[Lake=="Pickerel",], tapply(vol, list(Length, psd),max))
> with(smb[Lake=="Roy",], tapply(vol, list(Length, psd),max))
>
> and pulled the values I needed out by hand and put them into a .csv.
> Unfortunately, I've got a number of other data sets upon which I'll need
> to do the same analysis. Finding a programmable alternative would
> provide a much easier (and likely less error prone) method to achieve
> the same results. Ideally, the "Length" and "vol" data would be in a
> data frame such that I could then analyze with nls.
>
> Does anyone have any thoughts as to how I might accomplish this?
>
> Thanks in advance,
>
> Steven Ranney
>
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