{"id":38007,"date":"2026-01-16T11:27:05","date_gmt":"2026-01-16T10:27:05","guid":{"rendered":"https:\/\/www.graviton.at\/letterswaplibrary\/2-million-messy-%e2%86%92-clean-addresses-what-would-you-build-with-this\/"},"modified":"2026-01-16T11:27:05","modified_gmt":"2026-01-16T10:27:05","slug":"2-million-messy-%e2%86%92-clean-addresses-what-would-you-build-with-this","status":"publish","type":"post","link":"https:\/\/www.graviton.at\/letterswaplibrary\/2-million-messy-%e2%86%92-clean-addresses-what-would-you-build-with-this\/","title":{"rendered":"2 Million Messy \u2192 Clean Addresses. What Would You Build With This?"},"content":{"rendered":"<p><!-- SC_OFF --><\/p>\n<div class=\"md\">\n<p>Hello fellow developers,<\/p>\n<p>I have a dataset containing 2 million complete Brazilian addresses, manually typed by real users. These addresses include abbreviations, typos, inconsistent formatting, and other common real-world issues.<\/p>\n<p>For each raw address, I also have its fully corrected, standardized, and structured version.<\/p>\n<p>Does anyone have ideas on what kind of solutions or products could be built with this data to solve real-world problems?<\/p>\n<p>Thanks in advance for any insights!<\/p>\n<\/div>\n<p><!-- SC_ON -->   submitted by   <a href=\"https:\/\/www.reddit.com\/user\/Hour-Dirt-8505\"> \/u\/Hour-Dirt-8505 <\/a> <br \/> <span><a href=\"https:\/\/www.reddit.com\/r\/datasets\/comments\/1qec750\/2_million_messy_clean_addresses_what_would_you\/\">[link]<\/a><\/span>   <span><a href=\"https:\/\/www.reddit.com\/r\/datasets\/comments\/1qec750\/2_million_messy_clean_addresses_what_would_you\/\">[comments]<\/a><\/span><\/p><div class='watch-action'><div class='watch-position align-right'><div class='action-like'><a class='lbg-style1 like-38007 jlk' href='javascript:void(0)' data-task='like' data-post_id='38007' data-nonce='65e0e39b87' rel='nofollow'><img class='wti-pixel' src='https:\/\/www.graviton.at\/letterswaplibrary\/wp-content\/plugins\/wti-like-post\/images\/pixel.gif' title='Like' \/><span class='lc-38007 lc'>0<\/span><\/a><\/div><\/div> <div class='status-38007 status align-right'><\/div><\/div><div class='wti-clear'><\/div>","protected":false},"excerpt":{"rendered":"<p>Hello fellow developers, I have a dataset containing 2 million complete Brazilian addresses, manually typed by real&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[85],"tags":[],"class_list":["post-38007","post","type-post","status-publish","format-standard","hentry","category-datatards","wpcat-85-id"],"_links":{"self":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts\/38007","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/comments?post=38007"}],"version-history":[{"count":0,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/posts\/38007\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/media?parent=38007"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/categories?post=38007"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.graviton.at\/letterswaplibrary\/wp-json\/wp\/v2\/tags?post=38007"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}