From Information Aesthetics (originally from boingboing): maps of San Francisco where different colors represent neighborhoods which are more or less expensive to rent in, from craigslist data. This is the work of Ethan Garner. The site appears to be overworked right now, so I can't actually check it out.
Anyway, I've been thinking that a map like this would be useful. However:
- as people have pointed out, the scale is relative, not absolute, so "yellow" on one map doesn't correspond to "yellow" on the other;
- I'd kind of like to see numbers. What I'd really want is a map that tells you "it'll probably cost you around $X per month to live here". The screenshot on boingboing is good enough that I can tell it's not there
- the implicit scale of .5 miles (the color for each point was determined by looking at places up to half a mile away) sounds too large, to me, at least for the city I know best (Philadelphia). There are plenty of neighborhoods I know which really shouldn't be lumped in with things which are half a mile away. Then again, there may be an issue of the sample size here; if you reduce that radius too much there's the possibility of wild fluctuations due to a few particularly expensive or particularly cheap apartments.
What I'd really like to see is something that separates out the various elements of the price of an apartment -- for example, how much more does a two-bedroom, two-bathroom apartment cost than a two-bedroom, one-bathroom? How much more does a place with central air cost than one without? How much is being a block closer to downtown, or to a subway station, worth? (This last one, I think, has probably been studied; I've heard a rule of thumb that people value their travel time at one-half of their hourly wage, so if you know where people living in a certain area tend to go, and how much money they make, you've got an answer.) I've developed various rules of thumb while looking for housing, but just when I think they work I find too many counterexamples. But I'm not sure if they're actually counterexamples or if the model is sound and some people just price weirdly, and I don't have enough data -- or enough statistical knowledge -- to go any further.
As for "why San Francisco?" I've seen a similar neighborhood map of San Francisco, which gets its data mostly from Craigslist housing posts, and I've never seen maps like this generated from actual data for any other city. Craigslist probably has better coverage of San Francisco than any other city. However, my instinct is that Craigslist is still a flawed source, because it overrepresents the sort of apartments in the sort of neighborhoods that young people who are on the Internet a lot like. I don't know of any better source, though.
I don't trust this "neighborhood project", though, for a very simple reason: craigslist housing posts come from landlords, and landlords will lie about properties that are near the border of two neighborhoods if one neighborhood is seen as significantly "better" than the other. (In Philadelphia, for example, I've seen places at 56th and Arch called "University City" when even the University City District doesn't get within three-quarters of a mile of there, and their definition is widely thought to be very generous.) My instinct is that the data coming from people looking for roommates is substantially different, because people are less likely to lie to people they have to live with than to people they're just going to take money from.
Also, neighborhood names change with time; Philadelphia's "Graduate Hospital" neighborhood didn't exist twenty years ago. (And it now seems like a really stupid name, because the hospital's not called that any more. Residents are probably likely to use the name that a neighborhood had when they moved in. Unfortunately it would be nearly impossible to create a map that said "this is where various neighborhood boundaries were in 1950; this is where they are today", because getting the data for where people thought neighborhoods were in 1950 would require combing through far too many old newspapers and such.