On Sun, Feb 1, 2009 at 11:15 AM, Ken Kixmoeller/fh
<[email protected]> wrote:
> Hey -  -- ---
>
> Anybody else working this AM?
>
> I am working on some data conversion, and I'm looking to see if
> anyone has a more clever technique than mine for resolving
> differences among duplicate records. What I mean is this: I have a
> lot of records where obviously-same people (for example) have
> different values populated. So I have 2, 3, 4, 5 records variously
> populated:
>
> person          phone         fax             email            (many
> more fields..)
> Sally Jones    222-333-4444   222-333-4445
> Sally Jones                   222-333-4445
> Sally Jones    222-333-4444                   [email protected]
>
> Of course, I want them all to end up:
> Sally Jones    222-333-4444   222-333-4445   [email protected]
------------------------------------------

Have you considered normalizing this instead?

PersonID, ContatTypeID, Value.





> My technique essentially has always been:
>  - scan the "like" ones
>  - scatter the first one
>  - apply a bunch of if !empty() statements to populate the variables
>  - use SQL or "replaces" to repopulate them with the populated values.
>
> This is one of those situations where I keep thinking "there *has* to
> be a more clever way to do this." The problem is that I use the time-
> tested (or shop-worn) technique of flattening out the data, so there
> are a *lot* of fields that could be variously populated and some not
> to be evaluated like this, where the data in multiple rows are
> supposed to be different.
>
> Anybody do it differently?
>
> I am actually running the conversion in VFP9, so On-Topic!
>
> Ken
>
[excessive quoting removed by server]

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