Category Archives: CA Sunnyvale

City Population Characteristics & Trends: 2010-2016

.. the change in U.S. city population from 2010 to 2016 ranged from growth of 345,647 in New York City to a decline of -38,293 in Detroit, MI. New York City is actually five counties; the next largest city growth was Houston, TX with a 197,857 population gain.  Examine how the population is changing in cities of interest using the interactive table and other tools described in this post.  Use the interactive table to view a selected city, all cities in a state, cities in a county, cities in a metro or cities in a peer group size class.  See related Web section for more details.

Use the U.S. by cities shapefile with your GIS projects. See details. Thematic pattern maps illustrating use of these resources are shown below.

The July 1, 2016 Census Bureau model-based estimates (see about these data) for the U.S. 19,510 incorporated cities show a total population of 203,314,546 compared to 192,174,578 as of Census 2010. These areas are incorporated cities as recognized by their corresponding state governments and granted certain governmental rights and responsibilities.

Patterns of City Percent Change in Population 2010-16
— Cities 10,000 Population & Over
Use the CV XE GIS software with cities GIS project to examine characteristics of city/place population, 2010-2016. The following view shows patterns of population percent change, 2010-16 for cities with 2016 population of 10,000 or more. Use the interactive table below to see that among cities with 2016 population of 10,000 and over that Buda, TX had the largest percent change (98.8%) while Avenal, CA experienced the largest percent decrease (-18.4).

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

Fastest Growing Cities in the Dallas, TX Metro
— Cities 10,000 Population & Over; create views like this for any metro/county
It is easy to see which cities are growing the fastest using the thematic pattern view below. It is also easy to see how the cities relate to each other geographically and in context of county boundaries. The following view shows patterns of population percent change, 2010-16 for cities with 2016 population of 10,000 or more in the Dallas metro area.

– View developed using the CV XE GIS software.

Drill-down — Fastest Growing Cities in the Dallas, TX Metro
— Cities 10,000 Population & Over
Zoom into the north Dallas metro area and label the cities with name. The following view shows patterns of population percent change, 2010-16 for cities with 2016 population of 10,000 or more in the Dallas metro area.

– View developed using the CV XE GIS software. Click graphic for larger view; expand browser window for best quality view.

City/Place Demographics in Context
State & Regional Demographic-Economic Characteristics & Patterns
.. individual state sections with analytical tools & data access to block level
Metropolitan Area Situation & Outlook
.. continuously updated characteristics, patterns & trends for each/all metros
Related City/Place Demographic-Economic Interactive Tables
ACS 2015 5-year estimates
.. General DemographicsSocialEconomicHousing Characteristics

Using the Interactive Table
Use the full interactive table to examine U.S. national scope cities by annual population and change 2010-2016. The following graphic illustrates use of the table to view the largest cities ranked on 2016 population. Use the tools/buttons below the table to create custom views.

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.

Relating ZIP Codes to City/Places

.. relating ZIP codes to cities .. 214 ZIP code areas intersect with New York city — what are these ZIP codes, their population and how many are completely within the city? What part of a ZIP code area of interest intersects with what city? Conversely, what ZIP code areas intersect with a city of interest? This section provides data and tools that can be used to answer these types of questions and gain insights into geospatial relationships. See more detailed information in the related full Web section.

The 2010 ZIP Code Tabulation Area (ZCTA) to City/Place relationship data provide a means to equivalence ZCTAs with Census 2010 cities/places. ZCTAs are geographic areas defined as sets of Census 2010 census blocks closely resembling USPS ZIP codes (lines, not areas). ZCTA boundaries are fixed for the intercensal period 2010 through 2020. Census 2010 vintage city/place areas are likewise defined as sets of Census 2010 census blocks. The ZCTA-City/place relationship data are developed through the use of the intersecting census block geography and associated Census 2010 Summary File 1 demographic data.

ZCTA-Place Relationships
The following graphic shows relationships between two selected ZCTAs (red boundaries) and related cities/places (blue fill pattern) in the Pima/Cochise County, AZ area. Relationships between these geographies are reviewed in examples shown below.

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

Using the ZCTA-Place Relationship Data
Two examples illustrating how to use the ZCTA-place relationship data are provided below. The examples are interconnected to the GIS project used to develop the map views, interactive table and data file described in this section. Example 1 describes how to use the data for a ZIP code area entirely located within one city/place. Example 2 describes how to use the data for a ZIP code area located in more than one city/place and area not located in any city/place.

ZCTA to Place Relationships: Example 1
In this example, ZCTA 85711, highlighted in red in the graphic shown below, falls wholly within place 77000, outlined in bold black below. As a result, there is only one corresponding record for ZCTA 85711 in the relationship file. The 2010 Census population for this relationship record is 41,251 (POPPT) which is equal to the 2010 Census population for ZCTA 85711 (ZPOP). See more details about this example.

ZCTA to Place Relationships: Example 2
In this example, ZCTA 85630, highlighted below in red in the graphic shown below, contains two places: all of place 62280 and part of place 05770, both are outlined in black below. As a result, there are two corresponding relationship records in the relationship file. For the first relationship record, the total 2010 Census population for ZCTA is 2,819 (ZPOP). See more details about this example.

Using the Interactive Table
Use the full interactive table to examine U.S. national scope ZCTA-city/place relationships. The following graphic illustrates how ZIP code can be displayed/examined for one city — Tucson, AZ. Each row summarizes characteristics of a ZIP code in Tucson. The last row in the graphic shows characteristics of ZIP code 85711 — the same ZIP code reviewed in Example 1 above.

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.

County 5-Year Trends: Income & Income Inequality

.. tools and data to examine how the U.S. by county household income and income inequality are changing … how is household income changing in counties of interest? What are the trends; what is causing the change? What are the characteristics of income inequality and how is it changing? How might this change impact your living environment and business?

This section provides access to tools and data to examine U.S. by county measures of household income and income inequality between two 5-year periods (2006-10 and 2011-2015). These data can provide insights into how household income and income inequality are changing for one county, a group of counties and the U.S. overall. Use the interactive table to view median household income and measures income inequality for all counties. See more detail about these topics here. Measures of income inequality can be estimates/examined using the Gini Index.

The Gini Index & Measuring Income Inequality
The Gini Index is a dimensionless statistic that can be used as a measure of income inequality. The Gini index varies from 0 to 1, with a 0 indicating perfect equality, where there is a proportional distribution of income. A Gini index of 1 indicates perfect inequality, where one household has all the income and all others have no income.

At the national level, the 2015 Gini index for U.S. was 0.482 (based on 2015 ACS 1-year estimates) was significantly higher than in the 2014 ACS Index of 0.480 (based on 2014 ACS 1-year estimates). This increase suggests that income inequality increased across the country.

Examining Household Income & Income Inequality Patterns & Change
The following two graphics show patterns of the GIni Index by county. The first view is based on the American Community Survey (ACS) 2010 5-year estimates and the second is based on the ACS 2015 5-year estimates. The ACS 2010 estimates are based on survey respondents during the period 2006 through 2010. The ACS 2015 estimates are based on survey respondents during the period 2011 through 2015. One view compared with the other show how patterns of income inequality has changed at the county/regional level between these two 5-year periods.

Following these Income Inequality views are two corresponding views of median household income; using data from ACS 2010 and ACS 2015. Use CV XE GIS software with the GIS project to create and examine alternative views.

Patterns of Income Inequality by County; ACS 2010
The following graphic shows the patterns of the Gini Index by county based on the American Community Survey 2010 5-year estimates (ACS1115). The legend in the lower left shows data intervals and color/pattern assignment

.. view developed with ProximityOne CV XE GIS and related GIS project.

Patterns of Income Inequality by County; ACS 2015
The following graphic shows the patterns of the Gini Index by county based on the American Community Survey 2015 5-year estimates (ACS1115). The legend in the lower left shows data intervals and color/pattern assignment

.. view developed with ProximityOne CV XE GIS and related GIS project.

Patterns of Economic Prosperity by County; ACS 2010
The following graphic shows the patterns of median household income ($MHI) by county based on the American Community Survey 2010 5-year estimates (ACS1115). The legend in the lower left shows data intervals and color/pattern assignment

.. view developed with ProximityOne CV XE GIS and related GIS project.

Patterns of Economic Prosperity by County; ACS 2015
The following graphic shows the patterns of median household income ($MHI) by county based on the American Community Survey 2015 5-year estimates (ACS1115). The legend in the lower left shows data intervals and color/pattern assignment

.. view developed with ProximityOne CV XE GIS and related GIS project.

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.

America’s Cities: Demographic-Economic Characteristics Annual Update

.. tools and data to interactively examine demographic-economic characteristics of America’s 29,321 cities/places .. understanding demographic-economic characteristics of cities and places is essential for business development, market analysis, planning, economic development, program management and general awareness of patterns and trends. This section provides access to data and tools to examine characteristics of all cities/places in the U.S. This annual update includes data for 29,321 cities/places based on ACS 2015 data.

Accessing the Data; Using Interactive Tables
Each of the four links below opens a new page providing access to U.S. by city/place interactive tables — by type of subject matter. Use tools and usage notes below table to select operations to perform queries, sort and select columns.
General Demographics
Social Characteristics
Economic Characteristics
Housing Characteristics

How the the Tables/Data Can be Used
The following table shows data derived from the Economic Characteristics table. The top 10 cities/places having the highest median household income ($MHI) are shown. The table also shows population, median family income ($MFI) and per capita income ($PCI). The $250,000 value is a cap; the actual value is $250,000 or higher. Use the interactive tables to create similar views for states of interest. Use the button below the table to select/view cities within a selected metro. Compare attributes of cities of interest to a peer group based on population size.

Visual Analysis of City/Place Population Patterns
Use GIS resources to visually examine city/place demographic-economic patterns. The following view shows patterns of population percent change by city in the Charlotte, NC-SC metro area.

… view developed using the CV XE GIS software.
… click map for larger view and details.

Related Data
Cities/Places Main Section
Citie Population Estimates & Trends, 2010-15

More About Using These Data
Using ACS 1-year and 5-year data

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.

Housing Value Appreciation by 3-Digit ZIP Code: 2015Q3-2016Q3

.. tools, data and methods to examine housing value appreciation from 2015Q3 to 2016Q3 by 3-digit ZIP code based on the Housing Price Index (HPI).  How is the housing value changing in areas of interest?  How does housing value appreciation compare among a set of ZIP codes? Which ZIP code areas have the highest and lowest housing value appreciation in a state, region custom defined areas of interest? The HPI is calculated in part using home sales price information from Fannie Mae- and Freddie Mac-acquired mortgages. The U.S. all transactions HPI rose 5.6 percent from the 3rd quarter of 2015 to the 3rd quarter of 2016. Rank, compare, evaluate quarterly or annual housing value change for the approximate 900 3-digit ZIP code areas using the interactive table.

3-Digit ZIP Codes with Highest Housing Value Appreciation
Derived from the interactive table below this table shows the ten 3-digit ZIP codes having the highest housing value appreciation over the year 2015Q3-2016Q3. The areas are ranked on percent HPI change (rightmost column).

Gaining Insights in Housing Prices, Conditions & Markets
.. data, tools and methods to assess characteristics, patterns & trends
.. weekly Housing Data Analytics Lab sessions

Patterns of Housing Value Change by 3-Digit ZIP Code
The following graphic shows housing value appreciation 2015Q3-2016Q3 by 3-digit ZIP code based on the HPI. Use related GIS tools to zoom-in, assign labels, show in context with other geography.

– view developed using CVGIS and related GIS project.
– Click graphic for larger view and details;

Examining Housing Appreciation by 3-Digit ZIP Code
Use the interactive table below to view/rank/compare the non-seasonally adjusted “all transactions” HPI for the most recent 5 quarters for all 3-digit ZIP codes. The ranking table shows the latest quarterly HPI data and preceding quarters for one year earlier. This table will be updated on February 24, 2017, with 4th quarter 2016 data and related prior quarterly estimates and re-computed quarterly change values (last column).

Using the Interactive Table
The following graphic illustrates use of the HPI by 3-digit ZIP code interactive table. HPI data are shown for the quarterly period 2015Q3 through 2016Q3. The state selection below the table has been used to select only California ZIP codes. The Group1 button below the table has been used to select ZIP codes with a 2016Q3 HPI value of 175 ore more. The table is then sorted on the rightmost column. The resulting view shows that among all California 3-digit ZIPs having an HPI of 175 or more in 2016Q3, ZIP code 948/Richmond CA had the highest housing value appreciation — a 10.6% increase over the year.

Use the interactive table to examine states or ZIP code groups 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.

National Children & Education Statistics Program Updates

.. NCES Program updates .. tools, data & methodology to examine national scope children & education .. school, school district & extended geographic-statistical data with drill-down to school and intersection level. See more about the NCES Program below.

New this Week
ACS 2015 school district demographic-economic interactive tables
– view, compare, analyze selected/all U.S. school districts
– more focused blog updates coming soon.

School Districts with Highest Median Household Income
Use the interactive table to examine economic characteristics of school districts. Below is a list of the 10 school districts having the highest median household income developed using the Economic Characteristics interactive table. Develop similar views for metros and states of interest.

– ranked on item E062 — median household income.
– click graphic for larger view.

Use GIS tools to develop thematic pattern maps such as the one shown below with NCES GIS projects. Select from hundreds of statistical measures. Create your own regional;/district views. Integrate other data.

Patterns of Economic Prosperity by School District
– median household income (item E062 in table)

– view developed with CVGIS software & related GIS project and data.
– click graphic for larger view.

See the School Districts Economic Characteristics Interactive Table.

About the National Children & Education Statistics Program
The National Children & Education Statistics (NCES) Program provides access to tools, data & methodology to examine national scope children’s demographics & education-related characteristics. These resources enable stakeholders to view and analyze detailed geographic and statistical data at the school, neighborhood, community, attendance zone, school district and higher level geography. Integrate these data with drill-down demographic-economic data to the census block and intersection levels. Examine characteristics of schools, school districts and education data with related and higher level geography including urban/rural, cities, counties, metros, state and the U.S.

See NCES Main Section.

Contents: Summary of NCES Program Resources
Click a link to view more detail on a selected topic.
Updates: New Resources, Events & Related Topics
Analytics, Blogs, Studies
Using Software Tools & Datasets
01 Mapping & Visual Analysis Tools
02 School District Annual Demographic-Economic Data Resources
03 Children’s Demographics & Living Environment by School District
04 School District Enrollment & Operational Characteristics
05 School District Finances: Sources & Uses of Funds
06 School District Geographic Size & Characteristics
07 School District-ZIP Code Area Relationship Table
08 K-12 Public Schools
09 K-12 Private Schools
10 K-12 Public School Attendance Zones
11 K-12 Public Schools by Urban/Rural Status
12 Census Tract Demographic-Economic Characteristics
13 Metropolitan Area Situation & Outlook Reports

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.

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.