PropertyMaps Corporate Blog

Zip Code Polylines

14th July 2006 | Category: Maps

Here is an updated version of the previous polyline map - http://www.propertymaps.com/maps/polylines.php. I’ve added 5.8 million data points to cover about 50,000 zip codes in the United States, Puerto Rico, and the Virgin Islands. I’m also providing some useful statistics for each zip code such as population, average income, and average house value. This is a three way mashup based on the ZCTA data from the US Census Bureau. To read more about ZCTA, check out the FAQ at http://www.census.gov/geo/ZCTA/zctafaq.html.

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4 Comments so far

  1. John Coryat 2006 July 20th 8:23 am

    Just wondering what your source of the boundary maps data is. Did you extract them from the recent Tiger/Line dataset or find a source to download directly? If you did extract them yourself, what smoothing technique did you use to limit the number of points in the files? I noticed also that your xml file is pretty much the same format as mine, so you might have seen my site before…

    Thank you in advance for your attention.

    -John Coryat

  2. John Coryat 2006 July 20th 8:36 am

    Sorry to have bothered you. I see now that you are using the original 2000 version of the ZCTA data. There is an updated version in the Tiger/Line 2005SE dataset which is much improved over the 2000 data. It’s a bi*ch pulling it out, but it can be done… I’ve found there are just way more points in the new data vs. the old, so that’s why I had the question on smoothing.

    Nice implementation with the census data.

    -John Coryat

  3. beetle 2006 July 26th 4:42 pm

    I extracted the polyline data from the Tiger/Line dataset, but applied no method for smoothing - just plotting as is.

    I will have to update the info with the 2005SE dataset - how many datapoints are there? The 2000 data has about 5.8 million points…

  4. Darrin Clement 2008 January 4th 2:24 pm

    US Naviguide (maps.huge.info) has far more accurate data than the Census provides, as does Maponics. Essentially, anybody using data straight from the census will be dealing with old data and inaccuracies. The right way is to rejoin USPS data and rebuild them.

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