Category Archives: CVGIS

Examining Health Care Infrastructure by ZIP Code

.. small area data providing information on sub-county and sub-city/place geographies are challenging to locate and use — particularly in context of demand for healthcare services and demographic attributes of associated neighborhoods. Develop insights into the healthcare infrastructure by ZIP code using the two related resources reviewed here — 1) individual ZIP code demographic-economic profiles and 2) ZIP code demographic-economic interactive tables. One way to examine the healthcare infrastructure for an area is to view/analyze the number and attributes (employment, earnings) of healthcare establishments by types of business/industry (such as physicians office or hospitals). Data and tools reviewed here provide insights into characteristics and patterns of national scope ZIP code areas — examine your ZIP codes of interest.

Option 1 — ZIP Code Profiles
.. examining the healthcare infrastructure in context of the related demographic-economic situation … the following graphic shows ZIP code 10514 (Westchester County, NY) with a bold red boundary.  Census tracts are shown with black boundaries with tract codes as white labels. See more about ZIP-Tract relationships. Cities/places are shown with blue cross-hatch pattern.

– view created with CV XE GIS software and related GIS project.

The above map graphic is part of a ZIP Code 10514 profile (click link to view complete profile). Section 3.1. of the profile shows the number healthcare establishments in the ZIP Code as partly shown in this graphic:

The portion of the table shows the NAICS/type of business code at left, followed by type of business description and the number of establishments at the right.

Examine other characteristics of this ZIP code profile and in context of others via this related Web section. These profiles update in May 2018.

Option 2 — ZIP Code Health Care Sector comparative analysis
.. examining the healthcare infrastructure for a set of ZIP codes in a state, metro, county or peer group … use the interactive table located here to view/rank/compare health care business establishments by type of business for a selected set of ZIP codes. This table shows a query placed on the table to show the total number of offices of physicians for ZIP codes in the vicinity of ZIP 10514. It shows that there are 14 offices of physicians establishments and 13 have 1-4 employees.

About These and Related ZIP Code Data
Data used to develop the tools/resources described above are based in part on the Census Bureau County Business Patterns program. These establishment data update annually.

ZIP code demographic-economic interactive tables
Use the following tables to examine a wide range of ZIP code demographic-economic conditions:
  • General Demographics
  • Social Characteristics
  • Economic Chacteristics
  • Housing CHaracteristics

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.

Congressional District/State Legislative District Data Analytics Sessions

.. join me in the Congressional District/State Legislative District Data Analytics Sessions .. http://proximityone.com/cdsld/cdsld_vasessions.htm .. face-to-face sessions in the Washington, DC area.

Legislative Districts & Patterns of Neighborhood Economic Prosperity
Census tracts labeled with median household income in context VA House District 11 (bold blue boundary) in Fairfax County, VA. Use the GIS project to examine any state legislative district.

— click for larger view
— view created using CV XE GIS & associated GIS project.

CDSLD Sessions These sessions are focused on tools, data and analytical methods relating to Congressional Districts (115th CDs) and State Legislative Districts (2016 cycle SLDs). We focus on national and Virginia CDs and SLDs in context of the total population, voting population, the Citizen Voting Age Population characteristics and patterns with drill down to census blockblock groupcensus tractelection precinctcity/placeZIP codecountymetro and other geography.

Program details as PDF: http://proximityone.com/cdsld/cdsld_vasessions.pdf.

Anyone may attend. There is no fee. There is no promotional content. Sessions are presented by Warren Glimpse an expert on the topics covered. Learn more about the potentials of using these tools, data and methods. Get answers to your questions to learn more about what data are available, options to access the data, how to integrate these data with other data and insights into how you can use and the data. Attend one or many sessions. While there are core topics, new related material and updates are covered in each session. Join in as a continuing program. Develop and extend data analytics skills.

Patterns of Economic Prosperity by VA Senate District
– Virginia Upper/Senate SLDs by Median Household Income

– click graphic for better quality view; districts labeled with district code

More About Congressional Districts & State Legislative Districts
See the related section for more information:
• 115th Congressional Districts ..
.. Main .. http://proximityone.com/cd115.htm
.. demographic-economic tables http://proximityone.com/cd161dp1.htm
• State Legislative Districts Main .. http://proximityone.com/sld2016.htm
.. with demographic-economic interactive table
• Virginia State Legislative Districts .. http://proximityone.com/sld_va.htm
.. interactive table with incumbency details

CDSLD Data Analytics Web Sessions
Unable to join the face-to-face session? Join me in a Data Analytics Web 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.

School District Demographic Trends: 2010-2016

.. while enrollment in many school districts is growing, for many it is declining — these include some of the largest districts. Declining enrollment in school districts can result in school closings that destabilize neighborhoods, cause layoffs of essential staff and concerns that the students who remain are some of the neediest and most difficult to educate. See related narrative.

Based on total population, the largest 10 school districts in 2016 (see table below), all experienced an increase in population over the period 2010-2016. Five of these districts had a decrease in school age population (ages 5-17 years). Five of these districts had a decrease in the number of related children in poverty in families ages 5-17 years.

See the related Web section that provides tools to analyze annual demographic data for each U.S. school district for the period 2010 through 2016. This post summarizes selected details. These data include Census Bureau official 2016 estimates available for all districts. Developed for use as inputs for the ESEA Title I allocation formula, the data have broader uses of interest to school district demographics stakeholders. The 2016 estimates were released in November 2016; 2017 estimates become available in late 2018. ProximityOne uses these data in combination with other data to develop school district current estimates and annual projections through 2022 with related drill-down demographic-economic subject matter. Use the interactive table in the Web section to view, rank, compare demographic characteristics of districts of interest.

Largest 10 School Districts based on 2016 Population Age 5-17

Patterns of 2016 School Age Population in Poverty by School District
The graphic below shows school districts with total 2016 population of 1,000 or more by poverty incidence. Markers show the population ages 5-17 in families in poverty as a percent of population ages 5-17. Salmon markers: 40-50%. Red markers: 50% or more.

– view developed with CVGIS software and related GIS project.

School District Demographic Trends Interactive Table
Use the interactive table to view, rank, compare demographic characteristics of districts of interest.

More About K-12 Education & Children’s Demographics
See the related section on School District Demographic Trends 2010-2016:
http://proximityone.com/sdtrends.htm.

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 L

State of the States: Demographic Economic Update

.. tools and resources to examine the demographic-economic state of the states .. in 2016, the U.S. median housing value was $205,000 while states ranged from $113,900 (Mississippi) to $592,000 (Hawaii). See item/column H089 in the interactive table to view, rank, compare, analyze state based on this measure … in context of related housing characteristics. These data uniquely provide insights into many of the most important housing characteristics.

Use new tools, data and methods to access, integrate and analyze demographic-economic conditions for the U.S. and states. 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
• Economic Characteristics
• Housing Characteristics

GIS, Data Integration & Visual Data Analysis
Use data extracted from these tables in a ready-to-use GIS project. These ACS sourced data (from the four tables listed above) have been integrated with population estimates trend data, components of change and personal income quarterly trend data. See details in this section.

Examining Characteristics & Trends
Below are four thematic pattern maps extracted from the main sections listed above. Click a map graphic for a larger view. Use the GIS project to create variations of these views.

Patterns of Median Age by State
Yellow label shows the state USPS abbreviation; white label shows median age. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column D017 in the interactive table to view, rank, compare, analyze state based on median age.

Patterns of Educational Attainment by State
Yellow label shows the state USPS abbreviation; white label shows % college graduates. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column S067 in the interactive table to view, rank, compare, analyze state based on percent college graduates.

Patterns of Economic Prosperity by State
Yellow label shows the state USPS abbreviation; white label shows $MHI. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column E062 in the interactive table to view, rank, compare, analyze state based on median household income.

Patterns of Median Housing Value by State
Yellow label shows the state USPS abbreviation; white label shows $MHV. Legend shows color patterns associated with percent population change 2010-2016.

– View developed using CV XE GIS software and associated GIS project.
– See item/column H089 in the interactive table to view, rank, compare, analyze state based on median housing value.

Examining Characteristics & Trends; Using Data Analytics
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.

Low & Moderate Income Census Tracts; 2017 Update

..  data and tools to analyze characteristics and patterns of census tract geography with a focus on low and moderate income.   See related Web page for more detail.

Of the total 75,883 census tracts for which low and moderate income data were tabulated in the HMDA 2017 data, 6,023 (8.7%) were low income, 16,873 (24.5%) were moderate income, 32,509 (47.1%) were middle income and 19,159 (27.8%) were upper income. See more about these classifications. Find out about your tracts/neighborhoods of interest and how they compare to others using data and tools provided in this section.

Analysis of the low, moderate, middle, and upper income of the population and households by small area geography is important to housing market stakeholders, lenders, investors, cities/neighborhoods and others. Low and moderate income data by block group and census tract are used for compliance, eligibility determination and program performance in many Federal programs and agencies.

• Use the interactive table below to view, query, compare, sort census tracts.
• Use tract estimates & projections to examine changing characteristics.
– extended demographic-economic measures, annual 2010-2022

Low & Moderate Income by Census Tract
The following view shows census tracts designated as low and moderate income (orange fill pattern) in the the Houston, TX MSA (bold brown boundary) area. These are tracts having income level with codes 1 and 2 in the interactive table. A wide range of market insights can be created zoom-in views for counties, cities and neighborhoods and linking these with other data. Make variations of this view using ProximityOne data and tools described in this section.

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

View similar maps for these areas:
.. Atlanta metro
.. Chicago, IL metro
.. Dallas, TX metro
.. Knoxville, TN metro
.. with drill-down views for Knoxville city
.. Los Angeles, CA metro
.. San Francisco, CA metro

Using the Interactive Table
  – Examining LMI Tracts in Your Metro

Use the interactive table to view, query, sort compare tracts based on various demographic and LMI characteristitcs. The following graphic illustrates how the table can be used to view low and moderate income tracts for the Charlotte, NC-SC metro.
– click ShowAll button below table.
– enter a CBSA code in the edit box at right of Find CBSA LMI>.
– click the Find CBSA LMI button.
Resulting display of Charlotte metro LMI tracts only.

– 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.

Metro Population & Components of Change Trends 2010-2016

.. tools and data to examine how the U.S. by metro population is changing. Is the population moving away or into metros of interest? What are the trends; what is causing the change? What are the characteristics of the population moving in and out? How might this impact your living environment and business?

This section provides information on how and why the population is changing by metro from 2010 to 2016 in terms of components of change: births, deaths and migration. It provides a summary of tools, interactive table and GIS project, to analyze population change by metro using latest Census Bureau estimates through 2016. These data are used by ProximityOne to develop/update annual demographic-economic projections.  See related Web page to access full interactive table and more detail.

Patterns of Population Change by Metro, 2010-2016
The following graphic shows how metros (MSAs – Metropolitan Statisticsl Areas) changed from 2010 to 2016 based on percent population change. Click graphic for larger view; expand browser window for best quality view.

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

Narrative Analysis of Metro Demographic Change in Context
A narrative summary and analysis of metro demographic characteristics and change, contextually with other data and geography, is provided for each metro in the Situation & Outlook Reports. See more about the wide-ranging subject matter that are knitted together in the schedule of updates. Examine metro dynamics in context of the U.S. overall and related states and counties.

The nation’s 382 Metropolitan Statistical Areas (MSAs) had a population of 277.1 million in 2016 (86% of the total population). MSAs increased by 2.3 million people from 2015. The nation’s 551 Micropolitan Statistical Areas (MISAs) had a population of 27.7 million in 2016 (9% of the total population). MISAs increased by 16,000 people from 2015. See more highlights below

MSAs and MISAs together, or metro areas, comprised the set of Core-Based Statistical Areas (CBSAs). Each metro/CBSA is defined as a set of one or more contiguous counties.

Related Sections
• Metros Main
• Situation & Outlook Reports
• City/Place Population Trends
• County Population Trends
• County Population Projections to 2060
• ProximityOne Data Service

Examining Population Components of Change
Population change can be examined in terms of components of change. There are three components of change: births, deaths, and migration. The change in the population from births and deaths is often combined and referred to as natural increase or natural change. Populations grow or shrink depending on if they gain people faster than they lose them. Examining a county’s unique combination of natural change and migration provides insights into why its population is changing and how quickly the change is occurring.

See more about these topics below:
• Natural Increase/Change; birth & deaths
• Migration; net international, net domestic, net migration

Using the Interactive Table – Peer Group Analysis
Use the full interactive table to examine U.S. national scope metros by population and components of change. Consider an application where you want to study metros having a 2016 population between 250,000 and 300,000. Use the tools below the interactive table to select these metros as illustrated in the graphic shown below. The graphic shows these metros ranked on the overall U.S. metro rank (percent population change 2010-2016). As shown in the graphic, the Greeley, CO metro was ranked 11th among all metros and the fastest growing metro in this group. 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.

U.S. State Capital City Demographic-Economic Characteristics

.. tools and data to examine demographic-economic characteristics of each U.S. State capital city. The profiles are part of the America’s Communities Program. The profiles help stakeholders know “where we are”, how things are changing where and by how much, and how things might change in the future. See related web section for more detail.

State Capital Cities
The following graphic shows state capital city locations as markers. This view was developed using GIS tools enabling creation of similar views in context of other geography and subject matter. Orange markers are cities with less than 65,000 population; blue markers are cities with more than 65,000 population. based on percent population change. Click graphic for larger view. Larger view shows city names and urban areas. Expand browser window for best quality view.

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

State Capital City Demographic-Economic Profiles
State capital cities are listed below organized by state. Click the link within the brackets to view a demographic-economic profile for that city. The 2016 total population is shown in parentheses.

Alabama
• Montgomery, AL [0151000] (200,022)
Alaska
• Juneau, AK [0236400] (32,468)
Arizona
• Phoenix, AZ [0455000] (1,615,017)
Arkansas
• Little Rock, AR [0541000] (198,541)
California
• Sacramento, CA [0664000] (495,234)
Colorado
• Denver, CO [0820000] (693,060)
Connecticut
• Hartford, CT [0937000] (123,243)
Delaware
• Dover, DE [1021200] (37,786)
District of Columbia
• Washington, DC [1150000] (681,170)
Florida
• Tallahassee, FL [1270600] (190,894)
Georgia
• Atlanta, GA [1304000] (472,522)
Hawaii
• Honolulu, HI [1571550] (351,792)
Idaho
• Boise City, ID [1608830] (223,154)
Illinois
• Springfield, IL [1772000] (115,715)
Indiana
• Indianapolis, IN [1836003] (855,164)
Iowa
• Des Moines, IA [1921000] (215,472)
Kansas
• Topeka, KS [2071000] (126,808)
Kentucky
• Frankfort, KY [2128900] (27,885)
Louisiana
• Baton Rouge, LA [2205000] (227,715)
Maine
• Augusta, ME [2302100] (18,494)
Maryland
• Annapolis, MD [2401600] (39,418)
Massachusetts
• Boston, MA [2507000] (673,184)
Michigan
• Lansing, MI [2646000] (116,020)
Minnesota
• St. Paul, MN [2758000] (302,398)
Mississippi
• Jackson, MS [2836000] (169,148)
Missouri
• Jefferson City, MO [2937000] (43,013)
Montana
• Helena, MT [3035600] (31,169)
Nebraska
• Lincoln, NE [3128000] (280,364)
Nevada
• Carson City, NV [3209700] (54,742)
New Hampshire
• Concord, NH [3314200] (42,904)
New Jersey
• Trenton, NJ [3474000] (84,056)
New Mexico
• Santa Fe, NM [3570500] (83,875)
New York
• Albany, NY [3601000] (98,111)
North Carolina
• Raleigh, NC [3755000] (458,880)
North Dakota
• Bismarck, ND [3807200] (72,417)
Ohio
• Columbus, OH [3918000] (860,090)
Oklahoma
• Oklahoma City, OK [4055000] (638,367)
Oregon
• Salem, OR [4164900] (167,419)
Pennsylvania
• Harrisburg, PA [4232800] (48,904)
Rhode Island
• Providence, RI [4459000] (179,219)
South Carolina
• Columbia, SC [4516000] (134,309)
South Dakota
• Pierre, SD [4649600] (14,008)
Tennessee
• Nashville, TN [4752006] (660,388)
Texas
• Austin, TX [4805000] (947,890)
Utah
• Salt Lake City, UT [4967000] (193,744)
Vermont
• Montpelier, VT [5046000] (7,535)
Virginia
• Richmond, VA [5167000] (223,170)
Washington
• Olympia, WA [5351300] (51,202)
West Virginia
• Charleston, WV [5414600] (49,138)
Wisconsin
• Madison, WI [5548000] (252,551)
Wyoming
• Cheyenne, WY [5613900] (64,019)

Related Demographic-Economic Interactive Tables
Use the national scope demographic-economic interactive tables to view, rank, compare selected or all cities/places (approximately 29,500 places) using an extended set of data as used in the community profiles. The data are based the American Community Survey 2015 5-year estimates and organized into four subject matter groups:
General Demographics
Social Characteristics
Economic Characteristics
Housing Characteristics

See the related city population trends 2010-2016 interactive table to view, query, rank compare each cities are changing over time.

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.