Metro 2016 Demographic-Economic Data Analytics: Social Characteristics

.. part one of four parts focused Metro 2016 Demographic-Economic Data Analytics.  This post is on Social Characteristics; ahead: general demographics, economic characteristics and housing characteristics. See related Web section.

Patterns of Educational Attainment by Metro
The following graphic shows patterns of educational attainment (percent college graduate) by Metropolitan Statistical Area (MSA). Legend shows color patterns associated with percent college graduate values.

– View developed using CV XE GIS software and associated GIS project.
– use these resources to develop similar views for any area.
– modify subjects, zoom, colors, labels, add your data.

A Selected Social Characteristic & How Metros Vary
In 2016, the U.S. percent college graduates was 31.3 percent (of the population ages 25 and over) while Metropolitan Statistical Areas (MSAs) ranged from 11.3% (Lake Havasu City-Kingman, AZ MSA) to 60.6% (Boulder, CO MSA). See item/column S067 in the interactive table to view, rank, compare, analyze metros based on this measure for 2016 … in context of related social characteristics. These data uniquely provide insights into many of the most important social characteristics.

Social Characteristics – Subject Matter Covered
– Households by Type
– Relationship
– Marital Status
– Fertility
– Grandparents
– School Enrollment
– Educational Attainment
– Veteran Status
– Disability Status
– Mobility; Residence 1 Year Ago
– Place of Birth
– Citizenship Status
– Year of Entry
– Region of Birth
– Language Spoken at Home
– Ancestry
– Computers & Internet Use

Metro Data Analytics
Use tools, resources and methods to access, integrate and analyze social characteristics for metropolitan areas or Core-Based Statistical Areas (CBSAs). The table includes data for 382 Metropolitan Statistical Areas (MSAs) and 129 Micropolitan Statistical Areas (MISAs). These data will update in September 2018.

Approximately 600 subject matter items from the American Community Survey ACS 2016 database (released September 2017) are included in these four pages/tables:
• General Demographics
• Social Characteristics — reviewed here
• Economic Characteristics
• Housing Characteristics
See related Metro Areas Population & Components of Change time series data.

Focusing on Specific Metros & Integrated Multi-sourced Data
While these data provide a good cross section of data on social characteristics, this access structure is a) for one time period and b) data sourced from one statistical program. Also, there is a lot going on in metros; these are typically large areas with many important and diverse smaller geographies such as cities, counties and neighborhoods among other others.

Use the Metropolitan Situation & Outlook (S&O) reports to develop extended insights. See this example of the Washington, DC MSA S&O Report. Examine trends and projections to 2030. Inegrate your own data.

Using the Interactive Table
The following example illustrates use of the metro social characteristics interactive table … try using it on areas of interest. This view, showing metros partly or entirely in Arizona, was first developed by using the state selection tool below the table Next the selected columns button the table is used to examine educational attainment columns/items. The final step was to click the header cell on the “S067” item to sort metros on percent college graduates. It is easy to determine that the Flagstaff metro has the highest percent college graduates (home to Northern Arizona University).

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.

Tools to Analyze County Demographic-Economic Characteristics

.. demographic-economic characteristics of counties are 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 these data for all counties in the U.S. This annual update includes geographic area characteristics based on ACS 2015 data.  The tools/data are organized into four related sections summarized below.

1. General Demographics
View interactive table at http://proximityone.com/us155dp1.htm
Patterns of School Age Population by County
Use GIS tools to visually examine county general demographics as illustrated below. The following view shows patterns of percent population ages 5 to 17 years of age by county — item D001-D004-D018 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

2. Social Characteristics
View interactive table at http://proximityone.com/us155dp2.htm 
Patterns of Educational Attainment by County
– percent college graduate
Use GIS tools to visually examine county social characteristics as illustrated below. The following view shows patterns of percent college graduate by county — item S067 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

3. Economic Characteristics
View interactive table at http://proximityone.com/us155dp3.htm 
Patterns of Median Household Income by County
Use GIS tools to visually examine county economic characteristics as illustrated below. The following view shows patterns median household income by county — item E062 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

4. Housing Characteristics
View interactive table at http://proximityone.com/us155dp4.htm 
Patterns of Median Housing Value by County
Use GIS tools to visually examine county housing characteristics as illustrated below. The following view shows patterns median housing value by county — item E062 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

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.

Linguistic Isolation Patterns by Block Group

Linguistic isolation inhibits the ability of people and households to integrate into neighborhoods, cities and living areas. Opportunities for advancement and participation in society are improved where linguistic isolation is minimal. This section describes tools and data resources to examine patterns of linguistic isolation for block group level geography.

Size and distribution data on speakers of languages other than English and on their English speaking ability are important for many reasons. These data help us understand where populations with special needs exist and how they are changing. The data are used in a wide-ranging legislative, policy, and research applications. Many legal, financial and marketing decisions involving language-based issues make use of data on language use and English-speaking ability.

Data used to analyze patterns of “household linguistic isolation” are based on the American Community Survey (ACS) 2014 5-year estimates at the block groupgeographic level. The same scope of subject matter is available for higher level geography. The following graphic shows patterns of linguistic isolation in Los Angeles County. Block groups colored in red have more than 40-percent of households where no household member age 14 years and over speaks English “very well”. Click graphic for larger view showing more detail and legend.

Patterns of Linguistic Isolation; Los Angeles County, CA

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

The next view shows a zoom-in to the vicinity of the pointer shown in the above map. This view shows block groups labeled with total population. Click graphic for larger view showing more detail and legend.

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

Language Spoken by Households – Tabular View
The table presented below shows data from ACS Table B16002 Households by Linguistic Isolation for block group 1 in census tract 212304 (also referred to as 2123.04) in Los Angeles County (037) California (06); geoid=060372123041. This block group is shown toward the center of the above view with population 1,894. Data for this block group are shown in the rightmost column of the table below. 47.2 percent of households (803) are linguistically isolated (317+0+62).

— “Language Spoken” categories are based on four major language groups.

More About Linguistic Isolation
One definition of a “linguistically isolated household” is a household in which all adults have substantial limitation in communicating English. In the ACS data, a household is classified as “linguistically isolated” if 1) no household member age 14 years and over spoke only English, and 2) no household member age 14 years and over who spoke another language spoke English “very well”.

Like many demographic measures, linguistic isolation tends to be “masked” when analyzing data for larger geographic areas, even census tracts, are used. Block group geography provides an ability to locate linguistic isolation in sub-neighborhood areas.

Using Block Group Geography/Data
Census Block Groups sit in a “mid-range” geography between census blocks and census tracts. All cover the U.S. wall-to-wall and nest together, census blocks being the lowest common denominator for each. Block Groups (BGs) are the smallest geographic area for which annually updated ACS 5-year estimates data are tabulated.

Advantages of using BG geodemographics include the maximum degree of geographic drill-down (using ACS data) … enabling the most micro-perspective of demographics for a neighborhood or part of study area. A disadvantages of using BG estimates is that typically the smaller area estimates have a relatively higher error of estimate.

Summary of Steps to Access and Use these Data
The ACS 2014 5-year Table B16002 data can be accessed for Los Angeles County using the following API call (paste the following text into a browser and press Enter). See more about using Census API operations.

http://api.census.gov/data/2014/acs5?get=NAME,B01001_001E,B16002_001E,B16002_002E,B16002_003E,B16002_004E,B16002_005E,B16002_006E,B16002_007E,B16002_008E,B16002_009E,B16002_010E,B16002_011E,B16002_012E,B16002_013E,B16002_014E&for=block+group:*&in=state:06+county:037

At the end of this string is the text “state:06+county:037”. Change the state and county to “state:36+county:061” to access the data for New York County, NY (Manhattan); and similarly for any any county.

The results of the API call are shown in this text file. These data are easily imported into an Excel file. The DBF version of the data were integrated into the Los Angeles County 2014 block group shapefile using the CV XE GIS software dBMerge feature. The Layer Editor was then used to develop the map legend/color intervals. Join me in aData Analytics Lab session to learn more about these steps/operations.

Weekly Data Analytics Lab Sessions
Join me in a Data Analytics Lab session to discuss more details about accessing block group demographics using API tools and integrating those data into analytical applications.  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.

Demographic-Economic Comparative Analysis

The Charlotte-Gastonia-Rock Hill NC-SC Metro and Austin-Round Rock-San Marcos TX Metro are roughly the same size based on total population. How do they compare based on educational attainment? percent population in poverty? homeownership rate? age distribution? migration? employment by industry? occupation? How do business opportunities compare? What about other metros? Choose from hundreds of measures in the state/metro demographic-economic interactive tables to compare and contrast states and metros based on side-by-side comparisons.

The U.S.-State-Metro Demographic-Economic interactive tables provide a useful resource to view/compare geographies when ranked on a specific subject matter column of interest. The interactive tables are also useful to view a selected set of geographic areas where subject matter fields are arrayed horizontally for each geographic area. The U.S.-State-Metro Demographic-Economic interactive tables are available in the following Web pages.
• General Demographics DP1 table
• Social Characteristics DP2 table
• Economic Characteristics DP3 table
• Housing Characteristics DP4 table
… side-by-side comparative analysis profiles can often add more to insights.

Comparative Analysis Profiles
Create “comparative analysis profiles” using data presented in the interactive tables. View demographic-economic attributes of selected geographic areas of interest in a side-by-side manner. Place the data in a spreadsheet for further analysis, linking with other data and/or printing or adding to a report.

Partial view of sample file (access full xls file here)

Steps to Create Comparative Analysis Profiles
Step-by-step instructions to create comparative analysis profiles are provided at http://proximityone.com/usstcbsa_dp.htm. Select states and/or metros of interest. Create spreadsheet files for immediate use; save for future applications.

Linguistic Isolation Patterns

  Size and distribution data on speakers of languages other than English and on their English speaking ability are important for many reasons. These data help us understand where populations with special needs exist and how they are changing. The data are used in a wide-ranging legislative, policy, and research applications. Many legal, financial and marketing decisions involving language-based issues make use of data on language use and English-speaking ability.

This post reviews data useful to analyze “household linguistic isolation” based on American Community Survey (ACS) 5-year estimates at the block group geographic level. The same scope of subject matter is available for higher level geography.  The following graphic shows patterns of linguistic isolation in Queens County, NY.  Block groups colored in red have more than 50-percent of households where no household member age 14 years and over speaks English “very well”.

Patterns of Linguistic Isolation; Queens County, NY

One definition of a “linguistically isolated household” is a household in which all adults have substantial limitation in communicating English. In the ACS data, a household is classified as “linguistically isolated” if 1) no household member age 14 years and over spoke only English, and 2) no household member age 14 years and over who spoke another language spoke English “very well”.

Like many demographic measures, linguistic isolation tends to be “masked” when analyzing data for larger geographic areas, even census tracts, are used. Block group geography provides an ability to locate linguistic isolation in sub-neighborhood areas.

Census Block Groups sit in a “mid-range” geography between census blocks and census tracts. All cover the U.S. wall-to-wall and nest together, census blocks being the lowest common denominator for each. Block Groups (BGs) are the smallest geographic area for which annually updated American Community Survey (BG) data are tabulated.

Advantages of using BG geodemographics include the maximum degree of geographic drill-down (using ACS data) … enabling the most micro-perspective of demographics for a neighborhood or part of study area. A disadvantages of using BG estimates is that typically the smaller area estimates have a relatively higher error of estimate.

Language Spoken by Households
The table presented below shows data from ACS Table B16002 Households by Linguistic Isolation for block group 1 in census tract 046300 in Queens County (081) New York (36); geoid=360810463001. This block group is shown in the above map at the pointer. Data for this block group are shown in the rightmost column of the table below. 62.8 percent of households (610) are linguistically isolated (232+60+91).

Table B16002. Household Language by Households
Item Code	Item Description	Households
B16002001	Total	610
B16002002	English only	12
B16002003	Spanish language	321
B16002004	No one 14 and over speaks English only or speaks English “very well”	232
B16002005	At least one person 14 and over speaks English only or speaks English “very well”	89
B16002006	Other Indo-European languages:	60
B16002007	No one 14 and over speaks English only or speaks English “very well”	60
B16002008	At least one person 14 and over speaks English only or speaks English “very well”	0
B16002009	Asian & Pacific Island languages:	217
B16002010	No one 14 and over speaks English only or speaks English “very well”	91
B16002011	At least one person 14 and over speaks English only or speaks English “very well”	126
B16002012	Other languages:	0
B16002013	No one 14 and over speaks English only or speaks English “very well”	0
B16002014	At least one person 14 and over speaks English only or speaks English “very well”	0

“Language Spoken” categories are based on four major language groups.

Next Steps
Use the CV APIGateway to access Table B16002 and related data for block groups in cities or counties of interest.  Join us in the upcoming December 17, 2013 one hour web session where we talk about using the ACS 2012 5-year demographics for small area analysis.  Those new data are scheduled to be released that day.