Tag Archives: Los Angeles Census Tracts

Tip of the Day — Census Tract Data Analytics

.. tip of the day .. a continuing weekly or more frequent tip on developing, integrating, accessing and using geographic, demographic, economic and statistical data. Join in .. tip of the day posts are added to the Data Analytics Blog on an irregular basis, normally weekly. Follow the blog to receive updates as they occur.

This section is focused on tools and methods to access and use census tract demographic-economic measures. Median household income ($MHI), median housing value ($MHV) and other selected items are used to illustrate operations and options.

This section illustrates use of census tract data from the 2014 American Community Survey (ACS1014) 5-year estimates. These are the most comprehensive demographic-economic data from the Census Bureau at the census tract level. These “5-year estimates” are centric to mid-2012. See more about 2010-2021 annual estimates and projections.

Methods described here apply to many other geographies; see related tip sections. See related section on ZIP code applications.

Five data access and use options are reviewed. Each method illustrates how $$MHI, $MHV and other data can be analyzed/used in different contexts.

Option 1 – View the data as a thematic pattern map.
Option 2 – View, compare, rank query data in interactive tables.
Option 3 – Access data using API Tools; create datasets.
Option 4 – View $MHI in structured profile in context of related data.
Option 5 – Site analysis – view circular area profile from a location.

Related sections:
Census tracts main section
Evolution of Census Tracts: 1970-2010
Demographic-Economic Estimates & Projections
Census tract and ZIP code equivalencing
Using census tracts versus ZIP code areas
Single year of age demographics

Option 1. View the data as a thematic pattern map; use the GIS tools:
Patterns of Economic Prosperity ($MHI) by Census Tract … the following graphic shows $MHI for a portion of the Los Angeles metro. Accommodating different demographic-economic thresholds/patterns, different legend color/data intervals are used. The pattern layer is set to 80% transparency enabling a view of earth features. Click graphic for larger view, more detail and legend color/data intervals; expand browser window for best quality view.

– View developed using CV XE GIS and related GIS project.

See details about each option in the related Web page.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Importance of Census Tracts in Data Analytics

census tracts are important for many reasons. It is easy to misidentify or misunderstand patterns and characteristics within cities, counties and metros which become obfuscated using these higher level, more aggregate, geographies. Many cities and counties that might be experiencing demographic-economic decline will often have bright spots that are groups of a few or many census tracts.

Patterns of Percent Population with Bachelor’s Degree
— by Census Tract; Los Angeles Metro
The following graphic shows percent population age 25 years and over with bachelor’s degree by census tract based on ACS 2014 5 year estimates for a portion of the Los Angeles metro. Accommodating different demographic-economic thresholds/patterns, different legend color/data intervals are used. The pattern layer is set to 80% transparency enabling a view of earth features. Click graphic for larger view, more detail and legend color/data intervals. This map illustrates the geographic level of detail available using census tract demographics and the relative ease to gain insights using geospatial data analytics tools.

– View developed using CV XE GIS and related GIS project.

Get a Custom Map for Your Area of Interest
Use this form to request a no fee map graphic similar to the one shown above for a county of interest. Enter the request with county name and state in the text section; e.g., “Requesting social characteristics tract map for Cook County, IL.”

This section reviews reasons for the importance of census tracts in data analyyics. See related Web sections on tools, resources and methods that you can use to access, integrate and analyze U.S. by census tract general demographics data. The U.S. national scope Census Tracts Demographic-Economic Dataset contains approximately 600 subject matter items tabulated for each census tract organized into four subject matter groups:
General Demographics
Social Characteristics
Economic Characteristics
Housing Characteristics

Importance of Census Tracts for Data Analytics
Census tracts are important for many reasons.  A partial list of reasons is provided below.
• Covering the U.S. wall-to-wall, census tracts are the preferred “small area” geography for superior data analytics.
• The Census Bureau now produces annual tract demographic-economic data from the American Community Survey;  there is an evolving time-series at the tract level creating new analytical opportunities.
• Originally developed to equivalence neighborhoods, many still do.
• Defined by the Census Bureau in collaboration with local groups, tracts typically reflect boundaries meaningful for local area analysis.
• Defined generally for use with each new decennial census, most tract boundaries are stable and non-changing for ten years and many much longer.
• Designed to average 4,000 population, there are more than twice as many census tracts (73,056) than ZIP code areas (33,129).
• Tract boundaries are well-defined; unlike ZIP code areas which are subject to multi-sourced geographic definitions.
• Many data developers (e.g., epidemiologists) use census tract geography to tabulate their own small area data enabling more effective use of those data with Census Bureau census tract data.
• As a statistical geographic area (in contrast to politically defined areas, census tracts are coterminous with counties; data at the census tract level can be aggregated to the county level.
• Small area estimates for tracts are typically more reliable than for block groups.
.. census tracts are comprised on one or more coterminous block groups.
.. on average, a census tract is comprised of three block groups.
• Census tracts are used by many Federal, state and local governments for compliance and program management.

The annually updated American Community Survey provides “richer” demographic-economic characteristics for national scope census tracts. While Census 2010 provides data similar to those items in the General Demographics section, only ACS sourced data provide details on topics such as income and poverty, labor force and employment, housing value and costs, educational participation and attainment, language spoken at home, among many related items. The approximate 600 items accessible via the tract dataset are supplemented by a wide range of additional subject matter. ACS census tract data are updated annually in December of each year.

Weekly Data Analytics Lab Sessions
Join me in a Data Analytics Lab session to discuss more details about using census tract geography and demographic-economic data.  Learn more about integrating these data with other geography, your data and use of data analytics that apply to your situation.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.