census 0.4

A wrapper for the US Census Bureau's API

======
census
======

A simple wrapper for the United States Census Bureau's API.

Provides access to both the ACS and SF1 data sets.


Requirements
============

* python 2.6 or 2.7
* requests
* us


Usage
=====

First, get yourself a `Census API key <http://www.census.gov/developers/>`_.

::

from census import Census
from us import states

c = Census("MY_API_KEY")
c.acs.get(('NAME', 'B25034_010E'), {'for': 'state:%s' % states.MD.fips})

The call above will return the name of the geographic area and the number of
homes that were built before 1939 for the state of Maryland. Helper methods have
been created to simplify common geometry calls::

c.acs.state(('NAME', 'B25034_010E'), states.MD.fips)

Full details on geometries and the states module can be found below.

The get method is the core data access method on both the ACS and SF1 data sets.
The first parameter is either a single string column or a tuple of columns. The
second parameter is a geoemtry dict with a `for` key and on option `in` key. The
`for` argument accepts a `"*"` wildcard character or `Census.ALL`. The wildcard
is not valid for the `in` parameter.

Valid columns by data set:

* `ACS <http://www.census.gov/developers/data/2010acs5_variables.xml>`_
* `SF1 <http://www.census.gov/developers/data/sf1.xml>`_

The default year is 2011. To access 2010 data, pass a year parameter to the
API call::

c.acs.state(('NAME', 'B25034_010E'), states.MD.fips, year=2010)


Geometries
==========

The API supports a wide range of geographic regions. The specification of these
can be quite complicated so a number of convenience methods are provided.

Full geometry specifications are available for `ACS <http://thedataweb.rm.census.gov/data/acs5geo.html>`_
and `SF1 <http://thedataweb.rm.census.gov/data/sf1geo.html>`_.

ACS Geometries
--------------

* state(fields, state_fips)
* state_county(fields, state_fips, county_fips)
* state_county_subdivision(fields, state_fips, county_fips, subdiv_fips)
* state_county_tract(fields, state_fips, county_fips, tract)
* state_place(fields, state_fips, place)
* state_district(fields, state_fips, district)
* us(fields)


SF1 Geometries
--------------

* state(fields, state_fips)
* state_county(fields, state_fips, county_fips)
* state_county_subdivision(fields, state_fips, county_fips, subdiv_fips)
* state_county_tract(fields, state_fips, county_fips, tract)
* state_place(fields, state_fips, place)
* state_district(fields, state_fips, district)
* state_msa(fields, state_fips, msa)
* state_csa(fields, state_fips, csa)
* state_district_place(fields, state_fips, district, place)
* state_zip(fields, state_fips, zip)


States
======

This package previously had a `census.states` module, but now uses the
*us* package. ::

>>> from us import states
>>> print states.MD.fips
u'24'

Convert FIPS to state abbreviation using `lookup()`: ::

>>> print states.lookup('24').abbr
u'MD'


Examples
========

The geographic name for all census tracts for county 170 in Alaska::

c.sf1.get('NAME', geo={'for': 'tract:*', 'in': 'state:%s county:170' % states.AK.fips})

The same call using the `state_county_tract` convenience method::

c.sf1.state_county_tract('NAME', states.AK.fips, '170', Census.ALL)

Total number of males age 5 - 9 for all states::

c.acs.get('B01001_004E', {'for': 'state:*'})

The same call using the state convenience method::

c.acs.state('B01001_004E', Census.ALL)