Where people are looking for homes

January 6, 2012  |  Mapping

Trulia search growth

In August 2006, real estate search site Trulia had 609,000 visitors. Five years later, there were 27 million. Trulia's most recent visualization shows this growth (bottom bar graph) and where people are searching for homes (map). Press play and watch it go. It's pretty much population density, but for me, the method is more interesting than the material in this case.

The grass aesthetic is kind of nice. It looks like you have a one pixel blade of grass for each zip code with a significant search count (If only there was something to provide scale...), and where there's more search there's more grass.

I also like the relatively simple tech behind the graphic. We usually see animated and interactive maps generating everything on the fly, but the maps and bar graphs for this are pre-generated for each month. Then each image is displayed one after the other chronologically like a flip book.

[Trulia via @shashashasha]

6 Comments

  • Interesting graphic, but because it mostly reflects population density, I’m not sure if it is useful. If the authors could have normalized the values, it might have yielded some insights.

    Also, this technology is mostly similar to the “Gapminder” motion charts adopted by Google for their Charts API.

    Gapminder: http://www.gapminder.org/world/
    Google Charts: http://code.google.com/apis/chart/interactive/docs/gallery/motionchart.html
    Google Charts Example: https://spreadsheets.google.com/pub?key=pCQbetd-CptE1ZQeQk8LoNw

  • I agree with Isaac’s first observation. Normalization by population would improve the information value a lot.

    What rubs me a bit the wrong way about this graphic is that the map itself seems to be in 2D space (i.e. in an orientation where we are looking ‘straight down’ onto it), while the “grass” has a pseudo-3D perspective (which it has to have in order to be of informative value at all; only at an angle you can actually perceive the height of the “grass”, the information-bearing variable in this case). This seeming mix of perspectives doesn’t work for me at all.
    Additionally, there are the typical occlusion effects e.g. in the northeast of U.S. where the “grass” is dense and tall.

    I don’t agree with your second observation, Isaac. How do you think they are similar? I can only see one shared characteristic, namely that above visualization and Gapminder visualizations are both animated. In all other aspects they differ a lot.

  • The trend from 2006 to 2011 tells you nothing about real estate trends. It only tells you about the growth of Trulia.

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