R help - Dec 2011 - Group several variables and apply a function to the group

Dear R-experts,
I am struggling with the following problem, and I am looking for advice
from more experienced R-users: I have a data frame with 2 identifying
variables (comn and mi), and an output variable (x). comn is a variable for
a company and mi is a variable for a month.

comn<-c("abc", "abc", "abc", "abc",
"abc", "abc", "xyz",
"xyz","xyz", "xyz")
mi<- c("1", "1","1", "2",
"2", "2", "1", "1", "3",
"3")
x<- c("-0.0031", "0.0009", "-0.007",
"0.1929","0.0087", "0.099","-0.089",
"0.005", "-0.0078", "0.67" )
df<- data.frame(comn=comn, mi=mi, x=x)


For each company, within a particular month, I would like to compute the
standard deviation of x: for example, for abc, I would like to compute the
sd of x for month1 (when mi=1) and for month2 (when mi=2).

In other languages (Stata for instance), I would create a grouping variable
(group comnn and mi) and then, apply the sd function for each group.

However, I don't find an elegant way to do the same in R:

I was thinking about the following: I could subset my data frame by mi and
create one file per month, and then make a loop and in each file, use a
"by" operator for each comn. I am sure it would work, but I feel that
it
would be like killing an ant with a tank.

I was wondering if anyone knew a more straightforward way to implement that
kind of operation?

Thanks a lot,

Best,
Aurelien

	[[alternative HTML version deleted]]

 Like this?
library(plyr)
ddply(df,.(comn,mi),summarise,stDEV=sd(x))

Felipe D. Carrillo
Supervisory Fishery Biologist
Department of the Interior
US Fish & Wildlife Service
California, USA
http://www.fws.gov/redbluff/rbdd_jsmp.aspx


From: Aurélien PHILIPPOT
<aurelien.philippot@gmail.com>
>To: R-help@r-project.org 
>Sent: Sunday, December 4, 2011 12:32 PM
>Subject: [R] Group several variables and apply a function to the group
>
>Dear R-experts,
>I am struggling with the following problem, and I am looking for advice
>from more experienced R-users: I have a data frame with 2 identifying
>variables (comn and mi), and an output variable (x). comn is a variable for
>a company and mi is a variable for a month.
>
>comn<-c("abc", "abc", "abc",
"abc", "abc", "abc", "xyz",
"xyz","xyz", "xyz")
>mi<- c("1", "1","1", "2",
"2", "2", "1", "1", "3",
"3")
>x<- c("-0.0031", "0.0009", "-0.007",
"0.1929","0.0087", "0.099","-0.089",
>"0.005", "-0.0078", "0.67" )
>df<- data.frame(comn=comn, mi=mi, x=x)
>
>
>For each company, within a particular month, I would like to compute the
>standard deviation of x: for example, for abc, I would like to compute the
>sd of x for month1 (when mi=1) and for month2 (when mi=2).
>
>In other languages (Stata for instance), I would create a grouping variable
>(group comnn and mi) and then, apply the sd function for each group.
>
>However, I don't find an elegant way to do the same in R:
>
>I was thinking about the following: I could subset my data frame by mi and
>create one file per month, and then make a loop and in each file, use a
>"by" operator for each comn. I am sure it would work, but I feel
that it
>would be like killing an ant with a tank.
>
>I was wondering if anyone knew a more straightforward way to implement that
>kind of operation?
>
>Thanks a lot,
>
>Best,
>Aurelien
>
>    [[alternative HTML version deleted]]
>
>______________________________________________
>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.
>
>
>
	[[alternative HTML version deleted]]

Aur?lien PHILIPPOT wrote
> 
> Dear R-experts,
> I am struggling with the following problem, and I am looking for advice
> from more experienced R-users: I have a data frame with 2 identifying
> variables (comn and mi), and an output variable (x). comn is a variable
> for
> a company and mi is a variable for a month.
> 
> comn<-c("abc", "abc", "abc",
"abc", "abc", "abc", "xyz",
"xyz","xyz",
> "xyz")
> mi<- c("1", "1","1", "2",
"2", "2", "1", "1", "3",
"3")
> x<- c("-0.0031", "0.0009", "-0.007",
"0.1929","0.0087", "0.099","-0.089",
> "0.005", "-0.0078", "0.67" )
> df<- data.frame(comn=comn, mi=mi, x=x)
> 
> 
> For each company, within a particular month, I would like to compute the
> standard deviation of x: for example, for abc, I would like to compute the
> sd of x for month1 (when mi=1) and for month2 (when mi=2).
> 
> In other languages (Stata for instance), I would create a grouping
> variable
> (group comnn and mi) and then, apply the sd function for each group.
> 
> However, I don't find an elegant way to do the same in R:
> 
> I was thinking about the following: I could subset my data frame by mi and
> create one file per month, and then make a loop and in each file, use a
> "by" operator for each comn. I am sure it would work, but I feel
that it
> would be like killing an ant with a tank.
> 
> I was wondering if anyone knew a more straightforward way to implement
> that
> kind of operation?
> 
> Thanks a lot,
> 
> Best,
> Aurelien
> 
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
> R-help@ 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.
> 
One way would be to use the aggregate function. 

# Your Data ... 
# Note:  I have removed the quotes off the output variable x
comn<-c("abc", "abc", "abc", "abc",
"abc", "abc", "xyz",
"xyz","xyz", "xyz")
mi<- c("1", "1","1", "2",
"2", "2", "1", "1", "3",
"3")
x<- c(-0.0031, 0.0009, -0.007, 0.1929,0.0087, 0.099,-0.089, 0.005, -0.0078,
0.67)
df<- data.frame(comn=comn, mi=mi, x=x)

# Aggregate Function
aggregate(df$x, by=list(df$comn,df$mi),FUN=sd)

HTH

Pete

--
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Sent from the R help mailing list archive at Nabble.com.

?aggregate should do it

aggregate(df$x,list(df$comn, df$mi), sd)

There are other ways of course

Using the reshape2 package 

library(reshape2)
x1 <- melt(df, id=c("comn", "mi"))
dcast(x1, comn + mi ~ variable, sd)




--- On Sun, 12/4/11, Aur?lien PHILIPPOT <aurelien.philippot at gmail.com>
wrote:
> From: Aur?lien PHILIPPOT <aurelien.philippot at gmail.com>
> Subject: [R] Group several variables and apply a function to the group
> To: R-help at r-project.org
> Received: Sunday, December 4, 2011, 3:32 PM
> Dear R-experts,
> I am struggling with the following problem, and I am
> looking for advice
> from more experienced R-users: I have a data frame with 2
> identifying
> variables (comn and mi), and an output variable (x). comn
> is a variable for
> a company and mi is a variable for a month.
> 
> comn<-c("abc", "abc", "abc",
"abc", "abc", "abc", "xyz",
> "xyz","xyz", "xyz")
> mi<- c("1", "1","1", "2",
"2", "2", "1", "1", "3",
"3")
> x<- c("-0.0031", "0.0009", "-0.007",
"0.1929","0.0087",
> "0.099","-0.089",
> "0.005", "-0.0078", "0.67" )
> df<- data.frame(comn=comn, mi=mi, x=x)
> 
> 
> For each company, within a particular month, I would like
> to compute the
> standard deviation of x: for example, for abc, I would like
> to compute the
> sd of x for month1 (when mi=1) and for month2 (when mi=2).
> 
> In other languages (Stata for instance), I would create a
> grouping variable
> (group comnn and mi) and then, apply the sd function for
> each group.
> 
> However, I don't find an elegant way to do the same in R:
> 
> I was thinking about the following: I could subset my data
> frame by mi and
> create one file per month, and then make a loop and in each
> file, use a
> "by" operator for each comn. I am sure it would work, but I
> feel that it
> would be like killing an ant with a tank.
> 
> I was wondering if anyone knew a more straightforward way
> to implement that
> kind of operation?
> 
> Thanks a lot,
> 
> Best,
> Aurelien
> 
> ??? [[alternative HTML version deleted]]
> 
> ______________________________________________
> 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.
>