Good sources of messy addresses

[fgregg]

• The contributor's address from the illinois campaign finance data http://electionmoney.org/#receipts

[fgregg]

@waldoj, could you send us a sample of the addresses in the lobbying data you were working with?

[fgregg]

@jernsthausen, can you send us a sample of the addresses you were looking to parse?

[jernsthausen]

@fgregg give me a moment to find a dataset with some completely unparsed addresses.

[waldoj]

I have even more useful messy address data on hand, also from the state of Virginia. You can find it in most of the files at Virginia Businesses. I've taken all of the limited partnership addresses from their CSV file and posted it in a gist, which I hope you'll find helpful.

[fgregg]

Ooooh! Thanks!

On Wed, Sep 3, 2014 at 11:13 AM, Waldo Jaquith notifications@github.com
wrote:

I have even more useful messy address data on hand, also from the state of
Virginia. You can find it in most of the files at Virginia Businesses
http://business.openva.com/. I've taken all of the limited partnership
addresses from their CSV file http://business.openva.com/3_lp.csv and posted
it in a gist https://gist.github.com/waldoj/be5dca32a99835a9066f, which
I hope you'll find helpful.

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#16 (comment)
.

773.888.2718
2231 N. Monticello Ave
Chicago, IL 60647

[fgregg]

@jernsthausen, @waldoj Thanks for the very messy addresses. I think it's at a point where you guys might want to start playing with it.

Follow the instructions in the readme, and give it a spin. I think you'll get better results if you feed the data in column by column (i.e. don't concatenate address_1 and address_2 into a single string, but do each separately)

[waldoj]

Will do! Thank you, @fgregg!