Summary statistics for matrix columns

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.





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??? ??? 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



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