[R] Summary statistics for matrix columns

[Fares Said]

Thank you all 

Sent from my iPhone

On 2012-11-23, at 10:19, "arun" <smartpink111 at yahoo.com> 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 <Peter.Brecknock at bp.com>
> To: r-help at r-project.org
> 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 at .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
>> 
>> Solves the order and the matrix output!
>> 
>> 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
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> 
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