Challenge #54: Data Prep Address Parsing

[derekbelyea]

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[JosephSerpis]

Challenge Completed

[TeePee]

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I found this one very tricky.  In the end, I had to use a bit of a hack by manually adding a couple of the cities to a master list of cities which I took from the census bureau website.  I've also added a double-check: if the data set increases and there are more cities which aren't present in the census bureau list, they will be marked as "unknown" so the Alteryx user can add the cities to the master list.  Not very elegant, but it works.

[dsmdavid]

Regex + Data Cleansing. For a larger dataset a lookup for streets, alleys, circles, etc. would be needed --for this one I thought it was ok to hardcode the couple present.

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[kcgreen]

Done!

I'm impressed that some people were able to do this with just one Regex tool.  I needed three.

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[lminors]

Had fun with this one. Walked through it with a class I was training so had to avoid using RegEx which made it interesting!

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Solution was a bit messy with loads of embedded Replace() functions.

[Ozzy_Campos]

Here's my solution, done manually and creating common street labels.  This could be really useful to fine tune for large sets of addresses

[CHarrison]

Had to brush up on some REGEX skills for this one... surprised I managed to get there in the end! 

[data_rachel]

Not as elegant as some others, but good RegEx practice and certainly made me think!

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[mascarenhas_lucas]

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