avg(age::int4) OVER (partition by precinctid)

Political piece is here.

 precinctid | activeaverage | inactiveaverage | diffaverage
------------+---------------+-----------------+-------------
        268 |  53.6         |  36.1           |  17.5
        203 |  52.9         |  36.4           |  16.5
        139 |  45.9         |  30.6           |  15.4
        202 |  60.1         |  45.3           |  14.8
        167 |  53.9         |  39.2           |  14.7
        103 |  58.9         |  44.5           |  14.4
        205 |  50.7         |  36.4           |  14.3
        201 |  52.5         |  39.2           |  13.3
        144 |  49.6         |  36.6           |  13.1
        131 |  52.2         |  39.5           |  12.7
....

There are several new Postgres moves here for me. At this point, I expect my joins to become more sophisticated in the future.  Postgres syntax:

avg(age::int4) OVER (partition by precinctid)

allows a statistical slice of a factor similar to xtabs  (cross tabulation) in R.  Quite frankly, I think R does this with greater fluidity and less code.

SQL for comparing Active vs Inactive voters over time

/* 6:20 PM 9/23/2014 -RMF Political piece for this code is here.
I create query to dump out the various (voter history) databases I wish to compare to Postgres 'views'.  A 'view' in Postgres is essentially and 'in memory' table. There's more to than that but...:

Select * from voterdb where statuscode = 'I'; -- 'I' for 'inactive' 

The unique voter registration number isn't quite reliable as a primary key over time (in my humble opinion) so I use a 'unique tuple' (ARRAY[lastname,firstname,middlename]) of my own invention.
Something like ARRAY[lastname,firstname,middlename,registrationnumber::TEXT] would be even more unique.  You also need the 119 precincts of LD 42.
*/

SQL to query active vs. inactive voters, primary vs. general election participation

Postgres SQL code to query a Whatcom County Voter database to comapare previous and current elections for active vs. inactive voters, precincts vs. general election participation via ballotcounted and precinctid fields. Political piece is here.

Code to Parse PDC (financial disclosure) data for the State of WA

Quantile Regression for PDC Funding for the 42nd WA LD as of 09/01/2014. Republicans in Blue, Democrats in Red, All 42nd funding in grey

This is code to parse PDC data for candidates from a WA legislative district. See political piece here (link coming). Note: Updated 2:21 PM 9/6/2014 -RMF