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Challenge #54: Data Prep Address Parsing

A_Twa
8 - Asteroid

This one was a tough one for me - RegEx is not something I'm very proficient at (yet!).

MsBindy
8 - Asteroid

I parsed using the named groups with words Circle, Street, Road, etc.  For some reason had huge problems with Ave, Avenue, and Road...but eventually through trial and error got those words to work.

nick_ceneviva
11 - Bolide

Solution attached.  Couldn't seem to get the RegEx formula right to handle the street information, so I used a text input tool to replace the street (road, ave, etc) with a "|".  Then used RegEx match in the filter tool to handle the records with zip codes differently from the ones without.

Elena_Caric
8 - Asteroid

My Solution 

Natasha
9 - Comet

Here is my solution. City parsing works for this records, but I think it might be unreliable for other possible address combinations.

 

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jamielaird
14 - Magnetar

Here's my solution.

 

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patrick_digan
17 - Castor
17 - Castor
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I ended up using the Invisio Geocoder (which runs through Google) then the reverse geocoder (Alteryx macro) and then the parse address tool.
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marcreid
7 - Meteor

Solution

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dominiklz
8 - Asteroid
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RegEx: (^\d+) (\w+ \w+|\w+ \w+ \w+) (\w+|\w+ \w+) (\w{2})( \d{5}$|$)

took a lot of testing, but managed to get all information parsed out correctly using just one RegEx tool

samN
10 - Fireball

Simple Parsing.