R help - Jul 2010 - Obtaining the unmerged cases from one of the two data set

Dear "R Gurus",

 

I am having two dummy csv data sets A and B containing 19 and 15
cases/observations respectively. From the two data set 13 cases are
intersection. From one of the two (any) data set, How do I then retrieve
the unmerged data ? let's take A for example, six cases must appear in
our results. See the R codes below.

 

Please assist.

 

Looking forward to hearing from the group sooner and thanking you in
advance

 

Kind regards

 

Mangalani Peter Makananisa

Statistical Analyst

South African Revenue Service (SARS)

Segmentation and Research : Data Modelling

Tel: +27 12 422 7357, Cell: +27 82 456 4669, Fax:+27 12 422 6579

E-Mail : pmakananisa at sars.gov.za <mailto:pmakananisa at sars.gov.za>   

 

 
> A = read.csv("C:/Documents and Settings/S1033067/Desktop/A.csv",
header = TRUE, dec =",", sep = ",")
> names(A)
[1] "NAME"   "SALARY"
> dim(A)[1]
[1] 19
> B = read.csv("C:/Documents and Settings/S1033067/Desktop/B.csv",
header = TRUE, dec =",", sep = ",")
> names(B)
[1] "NAME"     "B.SALARY"
> dim(B)[1]
[1] 15
> common = merge(A,B)
> names(common)
[1] "NAME"     "SALARY"   "B.SALARY"
> dim(common)[1]
[1] 13
> 
 


Please Note: This email and its contents are subject to our email legal notice
which can be viewed at http://www.sars.gov.za/Email_Disclaimer.pdf

On Jul 21, 2010, at 5:33 AM, Mangalani Peter Makananisa wrote:
> Dear "R Gurus",
I saw no reason to copy Rob Hyndman. I did not see that this involves  
any of the packages he maintains.
>
> I am having two dummy csv data sets A and B containing 19 and 15
> cases/observations respectively. From the two data set 13 cases are
> intersection. From one of the two (any) data set, How do I then  
> retrieve
> the unmerged data ? let's take A for example, six cases must appear in
> our results. See the R codes below.
>
?setdiff

Perhaps:

setdiff( (NAME(A), NAME(B) )

You can also do a merge that is an outer join that includes all the  
NAME information and then extract the records with SALARY  
and .B.SALARY data. Untested in absence of working example:

?merge
mer <- merge(A,B, all=TRUE)
mer[ mer$NAME %in% setdiff(NAME(A), NAME(B) ),  ]

-- 
David.
>
>
>
>> A = read.csv("C:/Documents and
Settings/S1033067/Desktop/A.csv",
> header = TRUE, dec =",", sep = ",")
>
>> names(A)
>
> [1] "NAME"   "SALARY"
>
>> dim(A)[1]
>
> [1] 19
>
>> B = read.csv("C:/Documents and
Settings/S1033067/Desktop/B.csv",
> header = TRUE, dec =",", sep = ",")
>
>> names(B)
>
> [1] "NAME"     "B.SALARY"
>
>> dim(B)[1]
>
> [1] 15
>
>> common = merge(A,B)
>
>> names(common)
>
> [1] "NAME"     "SALARY"   "B.SALARY"
>
>> dim(common)[1]
>
> [1] 13
>
>>
David Winsemius, MD
West Hartford, CT