[R] compute differences

[jude.ryan at ubs.com]

Thanks Petr! It is good to see multiple solutions to the same problem.

Best,

Jude

-----Original Message-----
From: Petr PIKAL [mailto:petr.pikal at precheza.cz] 
Sent: Wednesday, September 23, 2009 10:59 AM
To: Ryan, Jude
Cc: alxmilton at yahoo.it; r-help at r-project.org
Subject: Re: [R] compute differences

Hi

You can use outer. If your data are in data frame test then

DIFF <- as.vector(t(outer(test$val, test$val, "-")))

returns a vector, You just need to add suitable names to rows.

CASE <- as.vector(t(outer(test$ID, test$ID, paste, sep="-")))

data.frame(CASE, DIFF)

will put it together.

Regards
Petr


r-help-bounces at r-project.org napsal dne 23.09.2009 16:42:45:

> Alessandro Carletti wrote:
> 
> 
> 
> Hi,
> 
> I have a problem.
> 
> I have a data frame looking like:
> 
> 
> 
> ID val
> 
> 
> 
> A? .3
> 
> B? 1.2
> 
> C? 3.4
> 
> D? 2.2
> 
> E? 2.0
> 
> 
> 
> I need to CREATE the following TABLE:
> 
> 
> 
> CASE?? DIFF
> 
> 
> 
> A-A??? 0
> 
> A-B??? -0.9
> 
> A-C??? -3.1
> 
> A-D??? -1.9
> 
> A-E??? -1.7
> 
> B-A??? ...
> 
> B-B??? ...
> 
> B-C
> 
> B-D
> 
> B-E
> 
> C-A
> 
> ...
> 
> 
> 
> WHERE CASE IS THE COUPLE OF ELEMENTS CONSIDEREDM AND DIFF IS THE
> computed DIFFERENCE between their values.
> 
> 
> 
> Could you give me suggestions?
> 
> 
> 
> Solution:
> 
> Besides the suggestions given by others, you can use the sqldf package
> to do this (leveraging knowledge in SQL if you know SQL). If you join
> your data frame with itself, without a join condition, you will get
the
> Cartesian product of the two data frames, which seems to be exactly
what
> you need. A warning is in order. Generally when you join 2 (or more)
> data frames you DO NOT want the Cartesian product by want to join the
> data frames by some key. The solution to your particular problem,
> however, can be implemented easily using the Cartesian product.
> 
> 
> 
> mydata <- data.frame(id=rep(c('A','B','C','D','E'), each=2),
> val=sample(1:5, 10, replace=T))
> 
> mydata
> 
> library(sqldf)
> 
> # merge data frame with itself to create a Cartesian Product - this is
> normally NOT what you want.
> 
> # Note 'case' is a key word in SQL so I use cases for the variable
name.
> Likewise diff is a used in R so I use diffr
> 
> mydata2 <- sqldf("select a.id as id1, a.val as val1, b.id as id2,
b.val
> as val2, a.id || ' - ' || b.id as cases,
> 
>                  a.val - b.val as diffr from mydata a, mydata b")
> 
> dim(mydata2) # check dimensions of the merged dataset
> 
> head(mydata2) # examine the first 6 records
> 
> # if you want only the columns casses and diffr, then use this SQL
code
> 
> mydata3 <- sqldf("select a.id || ' - ' || b.id as cases, a.val - b.val
> as diffr from mydata a, mydata b")
> 
> dim(mydata3) # check dimensions of the merged dataset
> 
> head(mydata3) # examine the first 6 records
> 
> 
> 
> Hope this helps.
> 
> 
> 
> Jude
> 
> ___________________________________________
> Jude Ryan
> Director, Client Analytical Services
> Strategy & Business Development
> UBS Financial Services Inc.
> 1200 Harbor Boulevard, 4th Floor
> Weehawken, NJ 07086-6791
> Tel. 201-352-1935
> Fax 201-272-2914
> Email: jude.ryan at ubs.com
> 
> 
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Because the information contained in this message may be privileged, 
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please notify us immediately by replying to this message and 
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UBS reserves the right to retain all messages. Messages are protected
and accessed only in legally justified cases.