Re: outer join in Gnumeric




For this kind of thing, I would use awk. There is also sqlite which
might be ported to your OS, you didn't specify, and this supports outer
joins.

I am not aware of a matrix operation that will sort/uniq muliple ranges
of data which would be neat.

Attached is a simple vlookup based approach you might use. You just need
to be able to have a complete set of student ids for the result sheet.

I am not sure how to get that complete set of student ids inside
gnumeric, but in the unix shell it is very simple.

Suppose you have 2 csv files of exam results, both with the first column
containing student ids.

cut -d, -f1 exam1.csv exam2.csv | sort -u > studentids.csv



On Fri, 2005-09-09 at 20:47 -0400, Alexander Kirillov wrote:
Hi guys: 
maybe one of the experts here can provide some advice...

I have two spreadsheets containing grades for two different exams
(midterm 1, midterm2) for  the same class. For simplicity, we can
assume that each contains the following filed:
ID Name Grade 

I need to merge them creating a single spreadsheet with all grades for
all students who took at least one of the exams. If the list of
students was the same, I could just copy-and-paste a column. However,
the lists are slightly different: some students missed one midterm,
others the second midterm, some dropped the class, etc.

Is there any simple way of merging them, short of manually matching
(there are about 900 students)? Of course, if using a database - such
as MySQL - it would be exactly one command [AFAIK, it is called "full
outer join"]. But I do not know MySQL, and learning it, converting the
data, and then converting back seems too much of a hassle for such a
simple thing.

Is there any way to do it in Gnumeric? Or in OpenOffice.org? In Excel
if there is no other way? [BTW: Microsoft Access database doesn't
support outer join. Typical for point-and-click products)

Thanks,
Sasha

PS: I know the right way would be to keep all the data in a single
spreadsheet, avoiding this problem. However, for reasons you do not
want to know, it was impossible - and it is too late now, anyway.
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