Good to hear that's it's working for you now, @lolabelittle
Some notes about datasets and importing them into SkecthUp ... as Chris pointed out, the data for Los Angeles is referenced to a western origin somewhere near Santa Rosa Island and a southern one near the tip of Long Beach. If you are planning on importing a number of different buildings from the same dataset, you should probably import them all first and then scale/relocate them as needed. This will insure that they align relative to each other.
If you are trying to match a set of buildings to a satellite photo, keep in mind that some of the datasets are "uncorrected" and will line up with a Google Earth satellite view. Some of them are "corrected" and will line up with a Google Maps satellite view (they are not the same). Most of the datasets do not have a building height associated with them in the database. Also, for those that do, no attempt is made to determine what units they are using ... they could be specified in cubits or fathoms or whatever. Los Angeles provides a second data height ("ELEV") that is the elevation of the building roof above sea level. A more correct approach would be to create the building footprint at elevation and then extend it downwards to the ground using the "HEIGHT" value (a possible future feature).
The only input to override the native numbers is the scale value. For some datasets, the distance between two points in a building polygon is below the 0.001" (0.0254mm) threshold for creating geometry in SketchUp (what I refer to as "the tiny edge problem"). This will cause the program to fail when it tries to use two points that are too close together. For some datasets, I had to scale the nominal numbers by only 100 or so. For others I needed 200,000 or more.
For Los Angeles and New York City, I created some models and placed them in the 3D Warehouse. There are also some random building footprints in Liechtenstein. Not in the Warehouse are Delaware, Arizona, Hawaii, Dresden, and several others that I used to test the importer. Due to the wide variety of purposes that utilize the collected data, there is sometimes useful information in the database and sometimes not (some of them only have a building ID number).
I appreciate @john_drivenupthewall and @ChrisDizon helping you to figure out why it wasn't working (I don't have a Mac to test things with). I have some changes that were suggested by a couple of the coding gurus that should prevent these problems down the road, but I haven't gotten around to implementing them yet. If you have any further problems or ideas on how this could be changed to make it better for your purposes, please let me know.