> isn't range mean the different between the max and min
That is one meaning of "range". There are many. To see what R's definition is
type
? range
or
help("range")
Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
> Behalf
> Of frespider
> Sent: Saturday, November 24, 2012 4:58 AM
> To: r-help@r-project.org
> Subject: Re: [R] Summary statistics for matrix columns
>
>
>
> HI A.k,
>
> I need one more question, if you can answer it please
>
> M <- matrix(sample(1:8000),nrow=100)
> colnames(M)<- paste("Col",1:ncol(M),sep="")
> apply(M,2,function(x) c(Min=min(x),"1st Qu" =quantile(x, 0.25,names=FALSE),
> Range = range(x),
> Median = quantile(x, 0.5, names=FALSE),
> Mean= mean(x),Std=sd(x),
> "3rd Qu" = quantile(x,0.75,names=FALSE),
> IQR=IQR(x),Max = max(x)))
>
> why I get two range . isn't range mean the different between the max and min
>
>
> Thanks
> Date: Fri, 23 Nov 2012 16:08:12 -0800
> From: ml-node+s789695n4650613...@n4.nabble.com
> To: frespi...@hotmail.com
> Subject: Re: Summary statistics for matrix columns
>
>
>
> Hi,
>
> No problem.
>
>
> There are a couple of other libraries which deal with summary statistics:
>
> library(pastecs)
>
> ?stat.desc() #
>
>
> library(matrixStats)
>
> #Using the functions from package: matrixStats
>
> fun1<-function(x){
>
> res<-
> rbind(colMins(x),colQuantiles(x)[,2],colMedians(x),colMeans(x),colSds(x),colQuantiles(x)[
> ,4],colIQRs(x),colMaxs(x))
>
> row.names(res)<-c("Min.","1st Qu.","Median","Mean","sd","3rd
> Qu.","IQR","Max.")
>
> res}
>
>
> set.seed(125)
>
> x <- matrix(sample(1:80),nrow=8)
>
> colnames(x)<- paste("Col",1:ncol(x),sep="")
>
> fun1(x)
>
> # Col1 Col2 Col3 Col4 Col5 Col6 Col7
> Col8
>
> #Min. 10.00000 1.00000 17.00000 3.00000 18.00000 11.00000 13.00000
> 15.00000
>
> #1st Qu. 24.75000 29.50000 26.00000 7.75000 40.00000 17.25000 27.50000
> 34.75000
>
> #Median 34.00000 46.00000 42.50000 35.50000 49.50000 23.50000 51.50000
> 51.50000
>
> #Mean 42.50000 42.75000 41.75000 35.75000 44.87500 26.87500 44.75000
> 50.12500
>
> #sd 25.05993 27.77846 19.57221 28.40397 16.39196 16.60841 21.97239
> 25.51995
>
> #3rd Qu. 67.75000 58.50000 50.00000 63.25000 54.25000 30.25000 56.25000
> 70.50000
>
> #IQR 43.00000 29.00000 24.00000 55.50000 14.25000 13.00000 28.75000
> 35.75000
>
> #Max. 74.00000 77.00000 76.00000 70.00000 65.00000 63.00000 79.00000
> 80.00000
>
> # Col9 Col10
>
> #Min. 2.00000 6.00000
>
> #1st Qu. 24.50000 12.50000
>
> #Median 33.50000 48.00000
>
> #Mean 34.87500 40.75000
>
> #sd 24.39811 28.21727
>
> #3rd Qu. 45.25000 63.00000
>
> #IQR 20.75000 50.50000
>
> #Max. 71.00000 72.00000
>
>
> I thought this could be faster than the previous methods. But, it was the
> slowest.
>
>
> set.seed(125)
>
> x1 <- matrix(sample(1:800000),nrow=1000)
>
> colnames(x)<- paste("Col",1:ncol(x1),sep="")
>
>
> system.time(fun1(x1))
>
> # user system elapsed
>
> # 0.968 0.000 0.956
>
> A.K.
>
>
>
>
>
>
>
>
>
> ________________________________
>
> From: Fares Said <[hidden email]>
>
> To: arun <[hidden email]>
>
> Cc: Pete Brecknock <[hidden email]>; R help <[hidden email]>
>
> Sent: Friday, November 23, 2012 10:23 AM
>
> Subject: Re: [R] Summary statistics for matrix columns
>
>
> Thank you all
>
>
> Sent from my iPhone
>
>
> On 2012-11-23, at 10:19, "arun" <[hidden email]> wrote:
>
>
> > HI,
>
> > You are right.
>
> > It is slower when compared to Pete's solution:
>
> > set.seed(125)
>
> > x <- matrix(sample(1:800000),nrow=1000)
>
> > colnames(x)<- paste("Col",1:ncol(x),sep="")
>
> >
>
> > system.time({
>
> > res<-sapply(data.frame(x),function(x) c(summary(x),sd=sd(x),IQR=IQR(x)))
>
> > res1<-as.matrix(res)
>
> > res2<-res1[c(1:4,7,5,8,6),] })
>
> > # user system elapsed
>
> > # 0.596 0.000 0.597
>
> >
>
> > system.time({
>
> > res<-apply(x,2,function(x) c(Min=min(x),
>
> > "1st Qu" =quantile(x, 0.25,names=FALSE),
>
> > Median = quantile(x, 0.5, names=FALSE),
>
> > Mean= mean(x),
>
> > Sd=sd(x),
>
> > "3rd Qu" = quantile(x,0.75,names=FALSE),
>
> > IQR=IQR(x),
>
> > Max = max(x))) })
>
> > # user system elapsed
>
> > # 0.384 0.000 0.384
>
> >
>
> >
>
> > A.K.
>
> >
>
> >
>
> >
>
> > ----- Original Message -----
>
> > From: Pete Brecknock <[hidden email]>
>
> > To: [hidden email]
>
> > Cc:
>
> > Sent: Friday, November 23, 2012 8:42 AM
>
> > Subject: Re: [R] Summary statistics for matrix columns
>
> >
>
> > frespider wrote
>
> >> Hi,
>
> >>
>
> >> it is possible. but don't you think it will slow the code if you convert
>
> >> to data.frame?
>
> >>
>
> >> Thanks
>
> >>
>
> >> Date: Thu, 22 Nov 2012 18:31:35 -0800
>
> >> From:
>
> >
>
> >> ml-node+s789695n4650500h51@.nabble
>
> >
>
> >> To:
>
> >
>
> >> frespider@
>
> >
>
> >> Subject: RE: Summary statistics for matrix columns
>
> >>
>
> >>
>
> >>
>
> >> HI,
>
> >>
>
> >> Is it possible to use as.matrix()?
>
> >>
>
> >> res<-sapply(data.frame(x),function(x) c(summary(x),sd=sd(x),IQR=IQR(x)))
>
> >>
>
> >> res1<-as.matrix(res)
>
> >>
>
> >> is.matrix(res1)
>
> >>
>
> >> #[1] TRUE
>
> >>
>
> >> res1[c(1:4,7,5,8,6),]
>
> >>
>
> >> # Col1 Col2 Col3 Col4 Col5 Col6 Col7
>
> >> Col8
>
> >>
>
> >> #Min. 10.00000 1.00000 17.00000 3.00000 18.00000 11.00000 13.00000
>
> >> 15.00000
>
> >>
>
> >> #1st Qu. 24.75000 29.50000 26.00000 7.75000 40.00000 17.25000 27.50000
>
> >> 34.75000
>
> >>
>
> >> #Median 34.00000 46.00000 42.50000 35.50000 49.50000 23.50000 51.50000
>
> >> 51.50000
>
> >>
>
> >> #Mean 42.50000 42.75000 41.75000 35.75000 44.88000 26.88000 44.75000
>
> >> 50.12000
>
> >>
>
> >> #sd 25.05993 27.77846 19.57221 28.40397 16.39196 16.60841 21.97239
>
> >> 25.51995
>
> >>
>
> >> #3rd Qu. 67.75000 58.50000 50.00000 63.25000 54.25000 30.25000 56.25000
>
> >> 70.50000
>
> >>
>
> >> #IQR 43.00000 29.00000 24.00000 55.50000 14.25000 13.00000 28.75000
>
> >> 35.75000
>
> >>
>
> >> #Max. 74.00000 77.00000 76.00000 70.00000 65.00000 63.00000 79.00000
>
> >> 80.00000
>
> >>
>
> >> # Col9 Col10
>
> >>
>
> >> #Min. 2.00000 6.00000
>
> >>
>
> >> #1st Qu. 24.50000 12.50000
>
> >>
>
> >> #Median 33.50000 48.00000
>
> >>
>
> >> #Mean 34.88000 40.75000
>
> >>
>
> >> #sd 24.39811 28.21727
>
> >>
>
> >> #3rd Qu. 45.25000 63.00000
>
> >>
>
> >> #IQR 20.75000 50.50000
>
> >>
>
> >> #Max. 71.00000 72.00000
>
> >>
>
> [[elided Hotmail spam]]
>
> >>
>
> >> A.K.
>
> >>
>
> >>
>
> >>
>
> >>
>
> >>
>
> >>
>
> >>
>
> >>
>
> >>
>
> >>
>
> >>
>
> >>
>
> >>
>
> >>
>
> >> If you reply to this email, your message will be added to the
> >> discussion
>
> >> below:
>
> >>
>
> >> http://r.789695.n4.nabble.com/Summary-statistics-for-matrix-columns-
> tp4650489p4650500.html
> >>
>
> >>
>
> >>
>
> >> To unsubscribe from Summary statistics for matrix columns, click
> >> here.
>
> >>
>
> >> NAML
>
> >
>
> > Then maybe ....
>
> >
>
> > x <- matrix(sample(1:8000),nrow=100)
>
> > colnames(x)<- paste("Col",1:ncol(x),sep="")
>
> >
>
> > apply(x,2,function(x) c(Min=min(x),
>
> > "1st Qu" =quantile(x, 0.25,names=FALSE),
>
> > Median = quantile(x, 0.5, names=FALSE),
>
> > Mean= mean(x),
>
> > Sd=sd(x),
>
> > "3rd Qu" = quantile(x,0.75,names=FALSE),
>
> > IQR=IQR(x),
>
> > Max = max(x)))
>
> >
>
> > HTH
>
> >
>
> > Pete
>
> >
>
> >
>
> >
>
> > --
>
> > View this message in context:
> > http://r.789695.n4.nabble.com/Summary-statistics-for-
> matrix-columns-tp4650489p4650547.html
> > Sent from the R help mailing list archive at Nabble.com.
>
> >
>
> > ______________________________________________
>
> > [hidden email] 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.
>
> >
>
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> If you reply to this email, your message will be added to the
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>
> To unsubscribe from Summary statistics for matrix columns,
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>
> NAML
>
>
>
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/Summary-statistics-for-
> matrix-columns-tp4650489p4650643.html
> Sent from the R help mailing list archive at Nabble.com.
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