I am trying to parse out addresses and i am able to parse the addresses when it hits a digit but some addresses are PO Box's and i am having trouble parsing PO Box Address out.
Example:
Jeff Adams Po Box 123 | Jeff Adams | Po Box 123 |
Betty Jean 508 South River Bend | Betty Jean | 508 South River Bend |
Hi @lbolin ,
One way to do that is by using RegEx
So in that regular expression, you keep everything before a digit or Po Box appears, and then whatever comes after that digit or Po Box in a separate column. Hope that helps.
Regards,
Angelos
Thank you very much this took me in the right direction. I ended up using (.*?) ([\d+\s.|Po].*) for it to parse correctly I am now having a problem if a word starts with a p or an o it parses it as well.
Example:
Address | Address Extras | Parsed Address |
98 Oak Street | 98 | Oak Street |
1252 Wild wood place | 1252 Wild Wood | place |
Tom Onel 3805 N Michigan Ave | Tom | Onel 3805 N Michigan ave |
Correct Answer:
Address | address Extras | parse Address |
98 Oak Street | 98 Oak Street | |
1252 Wild Wood Place | 1252 Wild Wood Place | |
Tom Onel 3805 N Michigan Ave | Tom Onel | 3805 N Michigan Ave |
Hi @lbolin ,
You can make it case sensitive and the use a formula tool to feed the address to the second field.
Would that work for your whole dataset?
Cheers,
Angelos
could you share your workflow?
Thank you so much. I do have one more question, how might i alter the regex to take into consideration if the address line starts with Po Box.
This is what it is currently doing:
Po Box 23456 | Po Box | 23456 |