A few GeoJSON databases

These are GeoJSON files converted from .shp elsewhere, via GDAL's ogr2ogr tool. They can be used by my little Python/Shapely/Rtree geolocation code from here. Other libraries like D3 are good with geojson, too. (One easy way to visualize a file: convert to KML with ogr2ogr, then open in Google Earth.)

counties.tiger2010.json.gz -- Counties, or county-equivalents, in the USA, from tl_2010_us_county10.shp from the U.S. Census Bureau's TIGER/Line shapefiles. With the command:
```
    ogr2ogr -f GeoJSON counties.tiger2010.json tl_2010_us_county10.shp
  
```
Note that state and county identifiers are FIPS codes. There's a table out there that corresponds state FIPS codes to the more familiar postal codes; I made a Python version here. Warning: the full FIPS code for a county is five digits long (two for the state/territory, then three more digits for the county within it), so they look like zip codes, but they are NOT zip codes!

cbsa.tiger2013.json.gz -- CBSAs for the USA from here. Command was:

    ogr2ogr -f GeoJSON cbsa.tiger2013.json tl_2013_us_cbsa.shp

tm_world_borders-0.3.json -- from TM_WORLD_BORDERS-0.3.shp, the top of whose Readme.txt file reads:

    Provided by Bjorn Sandvik, thematicmapping.org

    Use this dataset with care, as several of the borders are disputed.

    The original shapefile (world_borders.zip, 3.2 MB) was downloaded from the Mapping Hacks website:
    http://www.mappinghacks.com/data/

    The dataset was derived by Schuyler Erle from public domain sources.
    Sean Gilles did some clean up and made some enhancements.

Converted with the command:

    ogr2ogr -f GeoJSON world.json TM_WORLD_BORDERS-0.3.shp TM_WORLD_BORDERS-0.3