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A tool for collecting ACS and geospatial data from the Census API

Project description

autocensus

Python package for collecting American Community Survey (ACS) data from the Census API, along with associated geospatial points and boundaries, in a pandas dataframe.

Uses aiohttp to call Census endpoints with a series of concurrent requests, which saves a bit of time.

This package is under active development and breaking changes to its API are expected.

Installation

autocensus requires Python 3.7 or higher. Install as follows:

pip install autocensus

To run autocensus, you must specify a Census API key via either the census_api_key keyword argument (as shown in the example below) or by setting the environment variable CENSUS_API_KEY.

Example

from autocensus import Query

# Configure query
query = Query(
    estimate=5,
    years=[2014, 2015, 2016, 2017],
    variables=['B01002_001E', 'B03001_001E'],
    for_geo='tract:*',
    in_geo=['state:08', 'county:005'],
    # Fill in the following with your actual Census API key
    census_api_key='Your Census API key'
)

# Run query and collect output in dataframe
dataframe = query.run()

Output:

name geo_id year date variable_code variable_label variable_concept annotation value percent_change difference centroid internal_point geometry
Census Tract 151, Arapahoe County, Colorado 1400000US08005015100 2014 2014-12-31 B01002_001E Median age - Total Median Age by Sex 45.7 POINT (…) POINT (…) MULTIPOLYGON (…)
Census Tract 151, Arapahoe County, Colorado 1400000US08005015100 2015 2015-12-31 B01002_001E Median age - Total Median Age by Sex 45.2 -1.1 -0.5 POINT (…) POINT (…) MULTIPOLYGON (…)
Census Tract 151, Arapahoe County, Colorado 1400000US08005015100 2016 2016-12-31 B01002_001E Median age - Total Median Age by Sex 45.9 1.6 0.7 POINT (…) POINT (…) MULTIPOLYGON (…)
Census Tract 151, Arapahoe County, Colorado 1400000US08005015100 2017 2017-12-31 B01002_001E Median age - Total Median Age by Sex 45.7 -0.4 -0.2 POINT (…) POINT (…) MULTIPOLYGON (…)
Census Tract 49.51, Arapahoe County, Colorado 1400000US08005004951 2014 2018-12-31 B01002_001E Median age - Total Median Age by Sex 26.4 POINT (…) POINT (…) MULTIPOLYGON (…)

Other tables

By default, autocensus queries the detailed tables of the ACS. If your variables are located in other tables, use the table keyword argument:

query = Query(
    estimate=5,
    years=[2016, 2017],
    variables=['DP03_0025E'],
    for_geo='tract:*',
    in_geo=['state:17', 'county:031'],
    table='profile'
)

autocensus will map the following table codes to their associated Census API endpoints:

  • Detailed tables: detail
  • Data profiles: profile
  • Subject tables: subject
  • Comparison profiles: cprofile

Joining geospatial data

autocensus will automatically join geospatial data (centroids, representative points, and geometry) for the geography types state, county, zip code tabulation area, tract, and place for years 2013 and on. For queries spanning earlier years, these geometry fields will be populated with null values. (Census boundary shapefiles are not available for years prior to 2013.)

If you don't need geospatial data, set the keyword arg join_geography to False when initializing your query:

query = Query(
    estimate=5,
    years=[2011, 2012, 2013, 2014, 2015, 2016, 2017],
    variables=['B01002_001E', 'B03001_001E'],
    for_geo='tract:*',
    in_geo=['state:08', 'county:005'],
    join_geography=False
)

If join_geography is False, the centroid, internal_point, and geometry columns will not be included in your results.

Publishing to Socrata

If socrata-py is installed, you can publish query results directly to Socrata via the method Query.to_socrata.

Credentials

You must have a Socrata account with appropriate permissions on the domain to which you are publishing. By default, autocensus will look up your Socrata account credentials under the following pairs of common environment variables:

  • SOCRATA_KEY_ID, SOCRATA_KEY_SECRET
  • SOCRATA_USERNAME, SOCRATA_PASSWORD
  • MY_SOCRATA_USERNAME, MY_SOCRATA_PASSWORD
  • SODA_USERNAME, SODA_PASSWORD

Alternatively, you can supply credentials explicitly by way of the auth keyword argument:

auth = (os.environ['MY_SOCRATA_KEY'], os.environ['MY_SOCRATA_KEY_SECRET'])
query.to_socrata(
    'some-domain.data.socrata.com',
    auth=auth
)

Example: Create a new dataset

from autocensus import Query

# Configure query
query = Query(
    estimate=5,
    years=range(2013, 2018),
    variables=['DP03_0025E'],
    for_geo='county:*',
    in_geo=['state:08'],
    table='profile'
)

# Run query and publish results as a new dataset on Socrata domain
query.to_socrata(
    'some-domain.data.socrata.com',
    name='Average Commute Time by Colorado County, 2013–2017'  # Optional
)

Example: Replace rows in an existing dataset

# Run query and publish results to an existing dataset on Socrata domain
query.to_socrata(
    'some-domain.data.socrata.com',
    dataset_id='xxxx-xxxx'
)

Topics

autocensus is packaged with some pre-built lists of pertinent ACS variables around topics like race, education, and housing. These live within the autocensus.topics module:

import autocensus
from autocensus import Query

query = Query(
    estimate=5,
    years=[2013, 2014, 2015, 2016, 2017],
    # Housing variables: B25035_001E, B25064_001E, B25077_001E
    variables=autocensus.topics.housing,
    for_geo='tract:*',
    in_geo=['state:08', 'county:005']
)

Topics currently included with autocensus are population, race, education, income, and housing.

Known issues

SSL errors

Some users report errors like the following when querying the Census API:

SSL handshake failed on verifying the certificate
protocol: <asyncio.sslproto.SSLProtocol object at 0x11f805ac8>
transport: <_SelectorSocketTransport fd=11 read=polling write=<idle, bufsize=0>>

To disable SSL verification, specify verify_ssl=False when initializing your Query:

query = Query(
    estimate=5,
    years=[2014, 2015, 2016, 2017],
    variables=['B01002_001E', 'B03001_001E'],
    for_geo='tract:*',
    in_geo=['state:08', 'county:005'],
    verify_ssl=False
)

Tests

Use pytest to run the test suite:

pytest

Project details


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