All Of NYC's Affordable Housing through the Furman Center's Data Search Tool

Search all of New York City's affordable housing by name, owner, year built, location, financing or physical information (for example by # of building violations in 2010).  Or, you can research all sorts of demographic information from Crime to Education to employment to health to all sorts of housing informtion, to property tax to population, ethnic demographics and transportation.

Online Marketing Group Affordable Housing

The Furman Center for Real Estate and Urban Policy collects a broad array of data on demographics, neighborhood conditions, transportation, housing stock and other aspects of the New York City real estate market. We make our data directly available to the public through our new Data Search Tool, and publish comprehensive analyses of these data in our periodic reports.

The Data Search Tool is a new online application that provides direct access to New York City data collected by the Furman Center. Users can select from a range of variables to create customized maps, download tables, and track trends over time. Users are able to overlay never-before available information on privately-owned, publicly -subsidized housing programs collected through the Furman Center’s Subsidized Housing Information Project (SHIP). Information about how to use the Data Search Tool is available in our online guide.

Online Marketing Group Affordable Housing

From the Furman Center

When the Visualization Eclipses The Data...

In his 2003 novel Pattern Recognition, William Gibson created a character named Cayce Pollard with an unusual psychosomatic affliction: She was allergic to brands. Even the logos on clothing were enough to make her skin crawl, but her worst reactions were triggered by the Michelin Tire mascot, Bibendum.

Although it’s mildly satirical, I can relate to this condition, since I have a similar visceral reaction to word clouds, especially those produced as data visualization for stories.

If you are fortunate enough to have no idea what a word cloud is, here is some background. A word cloud represents word usage in a document by resizing individual words in said document proportionally to how frequently they are used, and then jumbling them into some vaguely artistic arrangement. This technique first originated online in the 1990s as tag clouds (famously described as “the mullets of the Internet“), which were used to display the popularity of keywords in bookmarks.

More recently, a site named Wordle has made it radically simpler to generate such word clouds, ensuring their accelerated use as filler visualization, much to my personal pain.

So what’s so wrong with word clouds, anyway? To understand that, it helps to understand the principles we strive for in data journalism. At The New York Times, we strongly believe that visualization is reporting, with many of the same elements that would make a traditional story effective: a narrative that pares away extraneous information to find a story in the data; context to help the reader understand the basics of the subject; interviewing the data to find its flaws and be sure of our conclusions. Prettiness is a bonus; if it obliterates the ability to read the story of the visualization, it’s not worth adding some wild new visualization style or strange interface.

Of course, word clouds throw all these principles out the window. Here’s an example to illustrate. About six months ago, I had the privilege of giving a talk about how we visualized civilian deaths in the WikiLeaks War Logs at a meeting of the New York City Hacks/Hackers. I wanted my talk to be more than “look what I did!” but also to touch on some key principles of good data journalism. What better way to illustrate these principles than with a foil, a Goofus to my Gallant?

And I found one: the word cloud. Please compare these two visualizations — derived from the same data set — and the differences should be apparent:

I’m sorry to harp on Fast Company in particular here, since I’ve seen this pattern across many news organizations: reporters sidestepping their limited knowledge of the subject material by peering for patterns in a word cloud — like reading tea leaves at the bottom of a cup. What you’re left with is a shoddy visualization that fails all the principles I hold dear.

Every time I see a word cloud presented as insight, I die a little inside.

For starters, word clouds support only the crudest sorts of textual analysis, much like figuring out a protein by getting a count only of its amino acids. This can be wildly misleading; I created a word cloud of Tea Party feelings about Obama, and the two largest words were implausibly “like” and “policy,” mainly because the importuned word “don’t” was automatically excluded. (Fair enough: Such stopwords would otherwise dominate the word clouds.) A phrase or thematic analysis would reach more accurate conclusions. When looking at the word cloud of the War Logs, does the equal sizing of the words “car” and “blast” indicate a large number of reports about car bombs or just many reports about cars or explosions? How do I compare the relative frequency of lesser-used words? Also, doesn’t focusing on the occurrence of specific words instead of concepts or themes miss the fact that different reports about truck bombs might be use the words “truck,” “vehicle,” or even “bongo” (since the Kia Bongo is very popular in Iraq)?

Of course, the biggest problem with word clouds is that they are often applied to situations where textual analysis is not appropriate. One could argue that word clouds make sense when the point is to specifically analyze word usage (though I’d still suggest alternatives), but it’s ludicrous to make sense of a complex topic like the Iraq War by looking only at the words used to describe the events. Don’t confuse signifiers with what they signify.

And what about the readers? Word clouds leave them to figure out the context of the data by themselves. How is the reader to know from this word cloud that LN is a “Local National” or COP is “Combat Outpost” (and not a police officer)? Most interesting data requires some form of translation or explanation to bring the reader quickly up to speed, word clouds provide nothing in that regard.

Visualization is reporting, with many of the same elements that would make a traditional story effective.

Furthermore, where is the narrative? For our visualization, we chose to focus on one narrative out of the many within the Iraq War Logs, and we displayed the data to make that clear. Word clouds, on the other hand, require the reader to squint at them like stereograms until a narrative pops into place. In this case, you can figure out that the Iraq occupation involved a lot of IEDs and explosions. Which is likely news to nobody.

As an example of how this might lead the reader astray, we initially thought we saw surprising and dramatic rise in sectarian violence after the Surge, because of the word “sect” was appearing in many more reports. We soon figured out that what we were seeing had less to do with violence levels and more to do with bureaucracy: the adoption of new Army requirements requiring the reporting of the sect of detainees. Of course, the horrific violence we visualized in Baghdad was sectarian, but this was not something indicated in the text of the reports at the time. If we had visualized the violence in Baghdad as a series of word clouds for each year, we might have thought that the violence was not sectarian at all.

In conclusion: Every time I see a word cloud presented as insight, I die a little inside. Hopefully, by now, you can understand why. But if you are still sadistically inclined enough to make a word cloud of this piece, don’t worry. I’ve got you covered.

This is an insightful and rather shrewd criticism of word clouds, and I think it applies to much of the infographic, data-visualizaion obsessed tech culture we live in.

I find myself fascinated by many of the new and innovative ways to graphically represent data. Yet, as Jacob Harris points out, many of these sleek new techniques (if they don't miss the point entirely) strip supposedly core ideas from the very context that lend them meaning... and we are left with a aesthetically pleasing series of pretty graphs and pie charts that convey very little actual information (see my post on the Infographic Idiom).

And even though CNN, Fox and other news networks are now embracing new visualization tools, tag clouds are ultimately useless measures of political sentiment, because concepts themselves really cannot be reduced to their most elemental articulation; in a word.

Global Pursuits of the American Dream

Check out the full infographic

American Hotspots According to Non-Americans

Are international house hunters looking for a piece of the American Dream in your city? Most likely if you live in the Sunshine State.

America is often called the land of opportunity, but these days, it might be more accurate to describe us as the land of dirt-cheap real estate. In the past 12 months, American home sellers cut about $24 billion from the homes they’ve listed on Trulia, of which a staggering $3 billion was slashed in Florida. Meanwhile, word on the street is – international buyers spent a whopping $41 billion last year to snap up U.S. homes left and right. Given this fun fact, we thought it’d be pretty fascinating to see where global house hunters are looking. The results will surprise you.

Florida, Not Just For American Retirees and Tourists
Right now, global house hunters make up about 5% of the window shopping that happens on Trulia. Aside from the usual suspects (e.g., Los Angeles, New York City and San Francisco), we saw a ton of interest in Florida … hmm?

What’s wrong with that you ask? Call us crazy, but it’s a bit shocking to see Naples and Kissimmee on the same list as Beverly Hills, Chicago and Honolulu.

In fact, 10 out of the 24 most popular American cities that have caught the eye of international homebuyers are in Florida – check it out for yourself. And yes, this list is based on popularity. That’s right, there’s more interest in Cape Coral than in Miami.

# Most Popular Florida Cities
1. Cape Coral, FL
2. Miami, FL
3. Fort Lauderdale, FL
4. Naples, FL
5. Fort Myers, FL
6. Miami Beach, FL
7. Kissimmee, FL
8. Orlando, FL
9. Jacksonville, FL
10. Tampa, FL

Reportedly, Canadians, Europeans and Brazilians spent about $13 billion on homes in Florida last year. But what gives – are the oranges really that good? We can’t say for sure, but what we do know is that the houses in Florida are being sold at a super discount. Oddly, this blue light special is also happening in Arizona, but last time we checked, the interest in Phoenix and Tucson is pretty tiny. Just to throw it out there, but maybe, just maybe, this is because Florida might be perceived as as being friendlier to non-citizens.

So who wants to move to Florida? With the exception of Brazil, let’s just say that most of these global window shoppers hail from the northern hemisphere and/or across the pond (as in Canada, the United Kingdom, France, Italy and Russia, Germany, Sweden and the Netherlands). Judging by our findings, this interest from abroad isn’t slowing down and may be the jolt that revives the Sunshine State’s struggling housing market.

America’s Next Top Expat Community
Now, let’s talk about the usual suspects. Of the 1.4 million global house hunters looking (on Trulia that is) to buy a piece of the American Dream, most are eyeing La La Land aka Los Angeles. Guess when it comes to “California dreamin,” everyone from the British and Australians to the Chinese and the Brazilians want to be part of Hollywood. More specifically, the British and the Australians would especially love a 90210 zip code since Beverly Hills is on each of their top 5 U.S. cities lists.

Another interesting, though hardly shocking, migration trend that we saw was in Mexico. Most of these house hunters currently living south of the border aren’t looking that far beyond the border with El Paso, San Diego and Chula Vista at the top of their list – no further commentary here.

One anomaly that we’re still scratching our heads about is Australia and Detroit. Right now, Detroit is #5 on Australia’s top 5 U.S. cities list. Aussies must really love Robocop (it’s rumored that they’re building a statue in honor of this 80s movie icon) or they must be really into techno (’cause as we all know, Detroit didn’t just give birth to Motown, they also gave us electronic music without words). Another theory that we’re toying with is that it’s also possible that the folks down under just love picking up homes for $40K a pop.

All in all, if our findings are any indication, America’s real estate market may be a driving force in either making us the world’s second home or an even more multicultural community.

Stunning Interactive Visualization of Migrant New Yorkers

via MapYourMoves


Map your moves – A visual exploration of where New Yorkers moved in the last decade


This map distills more than 4000 moves from over 1700 people, collected in an informal survey by WNYC, a New York based public radio station.

For generating the geo–coordinates from the entered ZIP codes, I used the free bulk geocoder at I did not check every single data row in detail, so a few of the moves might be misrepresented.


As most moves occurred from, to or within the New York area, this area displayed enlarged in the white circle at the center of the graphic. The rest of the world is mapped with a damped distance function, in order to fit everything into one screen without losing too to white-space.


Visual markers

Each circle corresponds to one zip code area. Its size indicates the number of moves to or from the area. legend colors Actually, it is consists of two overlaid circles: a red one for people moving out of the area, and a blue one for people moving to the area. So, a small purple circle with a thick blue outline indicates a place where people tend to move and stay, whereas a red outline indicates a less attractive place.


Click one of the circles to inspect only moves to or from this area. Or, to inspect a whole cluster of areas, drag to create a radial selection bubble. To clear your selection, click on the background. Moves to a selected place are indicated with a blue line, wheres moves from a selected place are drawn in red.



On the right, you can find some statistics on why and when people moved to the selected areas. legend bars You can directly compare the lengths of the red (for people moving away from the selected areas) and blue (for people moving to the selected areas) bars to spot trends and peculiarities. Moreover, you can compare these values to the baseline (overlaid in grey), which indicates the relative proportion when we consider at all moves. If, for instance, the blue bar for "landlord issues" is smaller than the red bar, this means that the selected area has a relatively low fraction of people moving away because of landlord issues.