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A Week of Mining Seattle’s Craigslist Apartment Pricing

62 点作者 racketracer大约 10 年前

5 条评论

alexyang21大约 10 年前
Pretty cool analysis! Scrapy is great but if you&#x27;re looking to extend this further, I recommend checking out the 3taps API. 3taps is the only API I&#x27;ve seen that breaks down the different components of a Craigslist post (e.g. heading, price, number of bedrooms) and makes it available for scraping. Using 3taps will also make it easy for you to extend the analysis to new cities (you literally change a single parameter). And you should set up a cron job (or Heroku scheduler task if a web app) so you don&#x27;t have to run the scraper manually every day :-)<p>If you want to check out an example of automated Craigslist scraping, you can check out a search tool I built (craigslist-scraper.herokuapp.com) and the accompanying tutorial (baserails.com&#x2F;apiscraper). Both are best viewed via laptop.
OrwellianChild大约 10 年前
I like the varied analysis! Though, if you want to build a prediction model, it&#x27;s probably best to avoid variables that can be gamed, e.g. # of pictures in a listing... For the larger zip codes, a heat-map of prices might help cut them down to more consistent behavior for prediction. Keep iterating - would love to see your progress over time!
dreen大约 10 年前
Did you do anything to avoid an IP ban for the crawler?
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masonhensley大约 10 年前
That&#x27;s really neat.<p>Fun fact - many apartments run by management companies &#x2F; owned by institutional investors dynamically price their units on a daily basis based on the number of phone inquiries, walk ins to the leasing office, occupancy rates in the neighborhood, and many other factors.<p>Ex: <a href="http:&#x2F;&#x2F;www.realpage.com&#x2F;yieldstar&#x2F;" rel="nofollow">http:&#x2F;&#x2F;www.realpage.com&#x2F;yieldstar&#x2F;</a>
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timtk大约 10 年前
Insightful read. Your mention of text mining in &quot;Future Look&quot; reminds me of Levitt&#x27;s findings regarding sales correlations with keywords in real estate listings.<p><a href="http:&#x2F;&#x2F;www.nber.org&#x2F;papers&#x2F;w11053.pdf" rel="nofollow">http:&#x2F;&#x2F;www.nber.org&#x2F;papers&#x2F;w11053.pdf</a><p><a href="http:&#x2F;&#x2F;freakonomics.com&#x2F;books&#x2F;freakonomics&#x2F;chapter-excerpts&#x2F;chapter-2&#x2F;" rel="nofollow">http:&#x2F;&#x2F;freakonomics.com&#x2F;books&#x2F;freakonomics&#x2F;chapter-excerpts&#x2F;...</a>