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 C-B C-C C-D C-E D-A D-B D-C D-D D-E E-A E-B E-C E-D E-E WHERE CASE IS THE COUPLE OF ELEMENTS CONSIDEREDM AND DIFF IS THE computed DIFFERENCE between their values. Could you give me suggestions? Alessandro Carletti
Try this: data.frame(ID = apply(expand.grid(x$ID, x$ID), 1, paste, collapse '-'), diff = c(outer(x$val, x$val, '-'))) On Mon, Sep 21, 2009 at 9:39 AM, alessandro carletti <alxmilton at yahoo.it> 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 > C-B > C-C > C-D > C-E > D-A > D-B > D-C > D-D > D-E > E-A > E-B > E-C > E-D > E-E > > WHERE CASE IS THE COUPLE OF ELEMENTS CONSIDEREDM AND DIFF IS THE computed DIFFERENCE between their values. > > Could you give me suggestions? > > Alessandro Carletti > > > > > ______________________________________________ > 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. >-- Henrique Dallazuanna Curitiba-Paran?-Brasil 25? 25' 40" S 49? 16' 22" O
Here is an approach...probably there are more elegant ways
mydata=data.frame(ID=c("A","B","C","D","E"),val=c(.3,1.2,3.4,2.2,2.0))
index=expand.grid(1:nrow(mydata),1:nrow(mydata))
dif=data.frame(difference=mydata$val[index$Var2]-mydata$val[index$Var1])
rownames(dif)=paste(mydata$ID[index$Var2],"-",mydata$ID[index$Var1])
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
> C-B
> C-C
> C-D
> C-E
> D-A
> D-B
> D-C
> D-D
> D-E
> E-A
> E-B
> E-C
> E-D
> E-E
>
> WHERE CASE IS THE COUPLE OF ELEMENTS CONSIDEREDM AND DIFF IS THE computed
DIFFERENCE between their values.
>
> Could you give me suggestions?
>
> Alessandro Carletti
>
>
>
>
> ______________________________________________
> 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.
>
--
Julian Mariano Burgos
Hafranns?knastofnunin/Marine Research Institute
Sk?lagata 4, 121 Reykjav?k, Iceland
S?mi/Telephone : +354-5752037
Br?fs?mi/Telefax: +354-5752001
Netfang/Email: julian at hafro.is, jmburgos at u.washington.edu
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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