Ranney, Steven
2008-Dec-22 21:51 UTC
[R] Summary information by groups programming assitance
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
hadley wickham
2008-Dec-22 21:59 UTC
[R] Summary information by groups programming assitance
On Mon, Dec 22, 2008 at 3:51 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?You might want to have a look at the plyr package, http://had.co.nz/plyr, which provides a set of tools to make tasks like this easy. The are a number of similar examples in the introductory pdf that should get you started. Regards, Hadley -- http://had.co.nz/
Søren Højsgaard
2008-Dec-22 22:25 UTC
[R] Summary information by groups programming assitance
Maybe summaryBy (or lapplyBy/splitBy) in the doBy package might help you.
Regards
S?ren
________________________________
Fra: r-help-bounces at r-project.org p? vegne af Ranney, Steven
Sendt: ma 22-12-2008 22:51
Til: r-help at r-project.org
Emne: [R] Summary information by groups programming assitance
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
______________________________________________
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.
Gabor Grothendieck
2008-Dec-23 00:15 UTC
[R] Summary information by groups programming assitance
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
>
> ______________________________________________
> 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.
>