get san diego & DC data from census with `variables.csv`

Working notes

1. most of the variables in in the sf3, not the sf1. So, this means the connections are to cenpy.base.Connection('2000sf3') and cenpy.base.Connection('DecennialSF31990'), not 2000sf1 or DecennialSF11990
2. the ACS table column codes are not the SF3 column codes. So, B03001_004E doesn’t exist in the sf3. This means we must match by “category,” called concept in the census API.
3. sf3 for 2000 from the API only goes down to block groups, not blocks.

currently, this means building up analogue columns by querying into the pandas dataframe, connection.variables:

import cenpy
c2000sf3 = cenpy.base.Connection('2000sf3')
has_ancestry = c2000sf3.variables['concept'].str.lower().apply(lambda x: 'ancestry' in x)
c2000sf3.variables[has_ancestry]['concept'] 

So, if we can get the column names that correspond, then:

c2000sf3.query(columns=columns, geo_unit='block group', 
               geo_filter=dict(state='06',county='073', tract='*'))

should work.

[knaaptime]

http://www.geolytics.com/pdf/Appendix-E.pdf

[knaaptime]

the necessary data are now distributed through quilt