Category Archives: CA Sunnyvale

Urban Area Demographic Trends 2010-15

.. tools and analytics to examine all urban areas with particular focus on Urbanized Areas and demographic change between 2010 and 2015 .. examining urban areas in context of metropolitan areas .. the four fastest growing Urbanized Areas (UAs) from 2010 to 2015 were in Texas. McKinney, TX UA led the nation with an increase of 27.5% in total population. View, rank, compare 2010 and 2015 demographic characteristics for UAs using the interactive table in this related section. Urban areas (Urbanized Areas and Urban Clusters) are important for many reasons. More than metros and cities, urban area geography better reflects how the urban and rural population is changing. Both metros and cities can change geographic boundary over the years. Urban areas are based on Census 2010 and unchanging between 2010 and 2020. Annual demographic updates are available from the American Community Survey (ACS 2015).

This section is focused on tools and analytics to examine all urban areas with particular focus on Urbanized Areas and demographic change between 2010 and 2015. Use the interactive table >in the related section to view, rank, query urban areas and demographic change for larger urban areas. Use the related GIS tools and data to develop related thematic and relationship maps. Perform geospatial analysis of geographic and demographic-economic characteristics using the resources we have developed. Gain insights into patterns that might affect you. Use these resources to collaborate on how, where, what, when and why of change.

McKinney TX Urbanized Area in Context of City
The McKinney, TX UA (bold orange pattern) is shown in context of McKinney city (cross-hatched area) and other urban areas (lighter orange pattern). It is easy to see that some parts of the city are rural and that the UA extends beyond the city in many areas. See more about the McKinney UA and in comparison to other urban areas using the interactive table.


– view created using CVGIS software and related GIS project.

Most Urbanized Areas (UAs, 435 of 487) have population 65,000 population or more resulting in the availability of annual demographic-economic estimates. Data are fresher than available for smaller urban areas (ACS 5-year estimates for areas under 65,000). This means more current data to assess more recent characteristics. As annual data are available UAs enabling analysis of change over time. The “2010s” marks the first time these refreshed, time series-like data have been available for urban areas. Businesses and those examining change performing market analysis benefit from the ability to examine characteristics or urban areas in combination with counties and metros.

Houston Urbanized Area in Context of Houston Metro
The Houston metro has a bold brown boundary. It is easy to see how the Houston UA (darker orange fill pattern) geographically relates to the metro. Other urban areas (all) are shown with a lighter orange fill pattern. It is easy to see the urban/pattern character of the general region. While the Houston UA is the largest, there are four UAs that intersect with Houston metro. Use the interactive table below to view their names and characteristics.


– view created using CVGIS software and related GIS project.

Urbanized Areas tend to be associated with metropolitan areas having a similar name. But very often there are multiple UAs within a metro; sometimes one is not dominant. Often there are several UAs in a metro having similar size. Use the interactive table below to view the relationship of UAs and metros (CBSAs).

Using Interactive Table
Use the interactive table to view, rank, compare, query urban areas based on a selection of demographic measures. The following graphic illustrates how the table can be used. Click graphic for larger view.

The graphic shows the urbanized areas ranked in descending order based on 2010-2015 population. The rightmost column shows the area percent change in population over the period.

Fastest Growing Urbanized Areas, 2010-15

Try it yourself. Use the table to examine urban area patterns and characteristics based on your selected criteria.

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.

ZIP Codes with Highest & Lowest Economic Prosperity

.. the latest data for ZIP Code Areas show that eleven had a median household income of $250,000 or more during the period 2011-15. More than 20 ZIP code areas had a median housing value of $2,000,000 or more. Contrast these ZIP code areas with higher economic prosperity with the more than 150 ZIP codes that had a median housing value of less than $30,000.  Use the interactive table in this related Web section to see which ZIPs meet these and other criteria.

ZIP Codes with MHI $100,000 or More; Dallas, TX Metro
Analyzing economic prosperity patterns using combined types of small area geography … the following graphic shows ZIP code areas a red markers with the median household income or $100,000 or more in context of median household income by census tract thematic pattern. Click graphic for larger view with more detail. Expand browser window for best quality view. Use CV XE GIS software and associated GIS project to develop variations of this view for your areas of interest. .

– view developed with CV XE GIS software.

This section reviews measures of economic prosperity for all ZIP code areas. These data were released in December 2016. This section updates with new data December 2017. See the list of all ZIP ccdes showing population, housing and economic characteristics in the interactive table shown below. Use the interactive table to view, rank, compare and query ZIP code attributes.

Examining demographic-economic characteristics by ZIP code is important for several reasons. We are familiar with our own ZIP codes as a geographic location. We tend to be interested in our area compared to other areas. ZIP codes provide an easy way to do that. Also, many secondary data resources are tabulated by ZIP code area; some important data are only available by ZIP code. See more about ZIP Code areas.

Resources & Methods to Examine Small Area Demographics
• See related ZIP Code Demographic-Economic Interactive Tables
  .. extended subject matter
• See related Census Tract Code Demographic-Economic Interactive Tables
• Examine ZIP Code Urban/Rural Characteristics
• Examine ZIP Code Business Establishment patterns
• Examine ZIP Code Housing Price Index patterns
• Join us in the weekly Data Analytics Lab Sessions
  .. reviewing applications using these and related data.

ZIP Code Areas with $MHI $100,000 or More
The following graphic shows ZIP code areas as red markers having median household income or $100,000 or more. Click graphic for larger view with more detail. Expand browser window for best quality view. Use CV XE GIS software and associated GIS project to develop variations of this view; integrate other data; select alternative ACS 2015 subject matter.

– view developed with CV XE GIS software. Click graphic for larger view.

ZIP Code Areas with $MHV Less than $30,000
The following graphic shows ZIP code areas as orange markers having median housing value of less than $30,000. Click graphic for larger view with more detail. Expand browser window for best quality view. Use CV XE GIS software and associated GIS project to develop variations of this view; integrate other data; select alternative ACS 2015 subject matter.

– view developed with CV XE GIS software. Click graphic for larger view.

ZIP Code Areas: Population & Economic Prosperity
  — Interactive Table –
Use the interactive table to view, rank, compare, query ZIP codes based on a selection of demographic-economic measures. The following graphic illustrates how the table can be used to examine patterns of the three digit ZIP code area (San Diego) by 5-digit ZIP code. Table operations are used to select ZIP codes in the 921 3-digit area (containing 39 5-digit ZIP codes). These 39 ZIP code are then ranked in descending order on median household income. See results in the table shown below. ZIP code 92145 has the highest $MHI in this group with $228.036.

– click graphic for larger view.

Try it yourself. Use the table to examine a set of ZIP codes on your selected criteria in for a state/area of interest.

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.

2016 Presidential Election – Voting & Citizen Voting Age Population by County

In 2015, the U.S. citizen voting age population (CVAP) was 227,019,486 of the total U.S. resident population of 321,418,821 (70.6%). 2016 CVAP data are not yet available. In the 2016 presidential election, 128,298,470 votes were cast — approximately 56% of the citizen voting age population. For individual counties the 2016 presidential election vote ranged from 16% of the CVAP to near 100%. Use the interactive table in this section to examine characteristics of the 2016 presidential election vote and citizen voting age population by county.

This section reviews access to tools to view/analyze characteristics of the U.S. voting population (ages 18 and older and citizen) and participation in the 2016 presidential election. Data are based on Census Bureau annual population estimates, American Community Survey 2010-14 5 year (ACS 2014) Citizen Voting Age Population (CVAP) special tabulation and 2016 presidential election results.

Visual Analysis of 2016 Presidential Election Vote by County
The following graphic shows the 2016 presidential vote as a percent of the citizen voting age population.

– Click graphic for larger view.
– View developed with CV XE GIS software.

U.S. Electorate Profile: Characteristics of the Citizen, 18 and Older Population

– based on 2015 American Community Survey 1-Year estimates
*Except where noted, “race” refers to people reporting only one race.
**Hispanic refers to the ethnicity category and may be of any race.
***Households with citizen householders.

U.S. by County Interactive Table Analysis 
Use the interactive table to examine characteristics of the 2016 presidential election vote and citizen voting age population by county. The following graphic illustrates how the table can be used to examine patterns in the Houston, TX metro by county. The Find in CBSA button is used below the table to select only counties in this CBSA/metro. The rightmost column header cell is clicked to rank counties on the voter participation rate for the 2016 presidential election.

– click graphic for larger view.

Try it yourself. Use the table to examine a set of counties in a metro or state of interest.

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.

Monthly Local Area Employment Situation; 2015-2016

.. this update on the monthly and over-the-year (August 2015-August 2016) change in the local area employment situation shows general improvement. Yet many areas continue to face challenges due to both oil prices, the energy situation and other factors.  This section provides access to interactive data and GIS/mapping tools that enable viewing and analysis of the monthly labor market characteristics and trends by county and metro for the U.S. See the related Web section for more detail. The civilian labor force, employment, unemployment and unemployment rate are estimated monthly with only a two month lag between the reference date and the data access date (e.g., August 2016 data are available in October 2016).

Unemployment Rate by County – August 2016
The following graphic shows the unemployment rate for each county.

— view created using CV XE GIS and associated LAES GIS Project
— click graphic for larger showing legend details.

As shown in the illustrative interactive table view below, seven of the ten MSAs having the highest August 2016 unemployment rate were in California. Use the table to examine characteristics of counties and metros in regions of interest. As apparent from the monthly patterns shown in the table, some areas are impacted by season factors, but others are not.

View Labor Market Characteristics section in the Metropolitan Area Situation & Outlook Reports, providing the same scope of data as in the table below integrated with other data. See example for the Dallas, TX MSA.

The LAES data and this section are updated monthly. The LAES data, and their their extension, are part of the ProximityOne Situation & Outlook database and information system. ProximityOne extends the LAES data in several ways including monthly update projections of the employment situation one year ahead.

Interactive Analysis
The following graphic shows an illustrative view of the interactive LAES table. Seven of the ten MSAs having the highest August 2016 unemployment rate were in California (ranked on far right column in descending order). Use the table to examine characteristics of counties and metros in regions of interest. Click graphic for larger view.

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.

Census Tract-City Relationship Table

.. what census tracts are located in cities of interest? What are their codes? Conversely, do you have census tract codes and need to know corresponding city(s)? Get answers here.

This section provides access to an interactive table useful to examine relationships among Census 2010 census tracts, cities/places, and counties. 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. Census tracts are important sub-county geography in data analytics. See the related section on census data analytics. See more about census tracts and data analytics below in this section.

Relating Census Tracts to Cities & Counties
Census tracts are sub-county areas and nest coterminously within counties. The 6-character tract code is unique within county. For cities 10,000 and larger, there are some number of whole census tracts within the city. But around the perimeter of cities, census tracts will often be partly within and partly outside of the city. The following graphic shows the relationship of tracts, cities and counties in the Plano city area (green fill pattern) located mostly in Collin County within the Dallas metro. 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.

Using the Interactive Relationship Table
A small part of Plano is located in Denton county (see north-south bold red-brown boundary). Tract 021627 (see pointer) is located in Denton County and includes a part of Plano. To determine what geography tract 021627 intersects, click the Tract> button below the interactive table shown below. See that the tract is contained in parts of 4 cities.

Census Tract to City/Place & County Equivalence Table
The following graphic illustrates use of the interactive table to view/examine the relationship between census tract 48121021627 (in Denton County, TX) and the city of Plano, TX. Click graphic for larger view.

The above view was developed using the interactive table:
– click the ShowAll button
– click the FindTract button (preset to locate this tract).

Click the ShowAll button and enter a city/place (case-sensitive) name of interest to view the set of intersecting tracts. See the table usage notes below the table in the related Web page. We review operation of the table in the Data Analytics Web sessions.

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.

Analyzing County Business Patterns by Type of Business

.. mapping and analyzing county business patterns by type of business … this section reviews use of tools and methods to develop custom U.S. by county business patterns data by type of business and develop mapping and related GIS applications. Steps illustrate how to develop a U.S. by county business patterns dataset for the supermarket  industry — NAICS type of business code 445100. Use the interactive table in this related section to examine supermarket business characteristics by county. Create map views such as shown below and perform wide-ranging business patterns data analytics using the tools. Develop similar applications for any type of business – see full list of NAICS/type of business categories. This section is focused on Census-sourced County Business Patterns released April 2016. There are additional data resources that can be used in a similar manner reviewed in main Web section.

Patterns of Supermarket Establishments by County
The following graphic shows patterns of the number of supermarket establishments by county for the Houston metro (bold boundary) region. Counties are labeled with the number of supermarkets and county name. Number of supermarkets shown by intervals/colors as depicted in legend panel at left of map window. Create custom maps similar to this view for your regions of interest depicting establishments, employment or payroll for your type of business selection(s). Click graphic for larger view with more detail; expand browser window for best quality view.

View developed with CV XE GIS software using GIS project.

See full Web section to access data, tools and more detail.

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.

Tip of the Day: Median Rent by Metro

.. 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 .. click Follow button at upper right.

.. the most recent estimate of median gross rent [for occupied housing units paying rent] for metropolitan areas (core-based statistical areas) is as of 2014. These data are based on the American Community Survey (ACS2014) 1-year estimates.

Option 1. Use the interactive table:
– go to http://proximityone.com/usstcbsa14dp4.htm
– median gross rent is item H132.
– scroll left on the table until H132 appears in the header column
– this column shows the 2014 ACS 1-year estimate for H132 for all CBSAs
    (and states)
– see usage notes below table.

Option 2. Use the API operation:
click this link to get H132 (median rent) using the API tool.
– a new page displays showing a line/row for each metro.
– median rent appears on the left, then metro name and code.
– optionally save this file and import the data into a preferred program.
– more about API tools.

Option 3. View the median rent in context of other attributes for a metro.
click a link in this table to select a metro of interest.
– when the metro profile displays, see section 5.2.

See this related section on metro rental markets.

This section is focused on median rent. Many other subject matter items will be apparent when these methods are used. Optionally adjust above details to view different subject matter for metros.

Join me in a Data Analytics Lab session to discuss more details about accessing demographic-economic data. Learn more about using these data and tools to meet specific interests.

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.