I have done a lot of work importing data for a direct marketing company. As they specialised in the entertainment field, particularly night clubs, much of the data that was captured was entered late at night whilst the punter had already had a few. I found that the best way to handle data such as phone number was to initially define what sort of numbers would be valid. If you are using them for a marketing campaign then extension numbers may not be of use and so could be binned, equally ones without an area code; on the other hand they may be valid - you need to define the rules first then code them. Cleaning data such as names, addresses, phone numbers is not a trivial task! I found the easiest way was to step through the number one character at a time and use ISDIGIT().
John Weller 01380 723235 07976 393631 > > I had to do this once for a data file of over 700k records. > The data import someone else had done hadn't worked as they > had planned and some phone numbers had wound up inside the > "Name" field. Obviously these needed shifting back to the > correct "Phone" field. Easiest and quickest way to find > these records was just to check each piece of the string by > breaking it up. I put all of this in a scan loop to do it back then. > _______________________________________________ Post Messages to: [email protected] Subscription Maintenance: http://leafe.com/mailman/listinfo/profox OT-free version of this list: http://leafe.com/mailman/listinfo/profoxtech Searchable Archive: http://leafe.com/archives/search/profox This message: http://leafe.com/archives/byMID/profox/fcc575e12a5648ddb3c981f88874a...@wessex1 ** All postings, unless explicitly stated otherwise, are the opinions of the author, and do not constitute legal or medical advice. This statement is added to the messages for those lawyers who are too stupid to see the obvious.
