Category Archives: Cities & Counties

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

Examining America’s 10 Largest Urban Areas

.. why it matters .. among other reasons, these 10 areas have 24% of the total U.S. population. Three have increased by more than 20% in the past 5 years.

More than 80-percent of America’s population is urban, but far more than 80-percent of America’s geography is rural. Census 2010 shows that America’s urban population increased by 12.1 percent from 2000 to 2010, compared to the national overall growth rate of 9.7 percent. Urban areas now account for 80.7 percent of the U.S. population, compared to 79.0 percent in 2000.

America’s 10 Largest Urbanized Areas
The following table shows the largest 10 Urbanized Areas (UAs) based on the American Community Survey 2011 and 2016 1-year estimates (ACS2016) and change over the period. UAs are sorted in descending order based on the 2016 population estimate. Note that Atlanta, Dallas and Houston moved up in rank.

Geodemographic relationships vary widely between the urbanized areas (UAs). Some, such as Miami, comprise most or all of the urban area within the corresponding metropolitan statistical area. Others, such as Philadelphia, are nested within a mix of adjacent urban areas interspersed with rural areas. Among other things, these different geodemographic structures reflect how planning, needs assessment and market development vary widely from associated metro-to-metro. These data show the importance and need to consider the urban/rural population distribution even in the largest metros.

Visual Analysis — Dallas Urbanized Area
The urbanized area (UA) of the corresponding metropolitan statistical area (MSA) generally occupies less than half of the MSA.
See the Dallas-Fort Worth-Arlington, TX MSA Situation and Outlook Report

… View developed using CV XE GIS.

Map Views for Each of the Largest 10 Urbanized Areas
Maps for each of the 10 largest UAs are shown at
http://proximityone.com/urbanareas_2016.htm.

Each graphic shows the designated urbanized area in a darker salmon color fill pattern, associated metropolitan statistical area with bold brown boundary, and other urban areas with a lighter shade of salmon fill color, counties black boundaries and yellow labels. The ACS 2016 UA population is shown as a white label under the UA name. The ACS 2016 estimates are the most recent data available and will update with 2017 estimates in late 2018.

More About Analyzing Urban/Rural Patterns and Characteristics
See the related section on America’s urban/rural population and geography:
http://proximityone.com/urbanpopulation.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

Creating Custom Demographic Datasets with API Tools

.. develop national scale spreadsheet files with virtually no learning time .. easy-to-use API operations to create national scope demographic-economic datasets based on American Community Survey 2016 1-year estimates .. custom subject matter selections. See more detail in related web sections ACS2016 and ACS2016_API.

Benefits and utility … how to acquire a spreadsheet showing the population of all cities with population estimates based on the ACS 2016 1-year data? … or, housing units, median household income, median housing value, etc.? Variations of this need frequently arise — what is the list of largest California counties sorted on total population: What are the 25 metros having the highest median household income? Which 10 congressional districts have the highest poverty incidence? Which urban areas have the highest educational attainment?

Use simple API calls described below to get answers to these types of questions — and more.  Create files that can be used for recurring applications. An example …

Urban Areas with 2016 Population 65,000+ Population
… results from using the API downloaded data … the following graphic shows urban areas with 65,000 or more 2016 population; zoom-in to Texas. The full national scope GIS project is available as described below; examine U.S. or any region. The file used to develop this view was created using the results of the API call reviewed below (requires integration of those data into the urban areas shapefile). Click graphic for larger view; expand browser window. Larger view shows urban areas labeled with name and mini profile for Dallas UA showing all subject matter items downloaded (via API) as described below.

… View developed using CV XE GIS.
… See more about Urban Population & Urban Areas.

Access ACS 2016 1-Year Data Using API Tools
Here are the API links … use these API calls to access/download selected items for selected geographies. See more about using API tools. Click a link and receive a return page with CSV-like structured data. See usage notes below. As these are ACS 2016 1 year estimates; geographies are only available for areas 65,000+ population.
Click a link:
• All U.S. cities/places
• All U.S. counties
• All U.S. CBSAs
• All U.S. Urban Areas
• All 115th Congressional Districts
• All U.S. states
• U.S. only

The following data retrieval operations are by state. These are examples using Arizona (FIPS state code 04).
• All [within state] Elementary School Districts
• All [within state] Secondary School Districts
• All [within state] Unified School Districts

API Call Returned Data Usage Notes
Clicking the All U.S. cities/places link above generates a new page with content very much like a CSV file. Try it .. click an above link.

See the related ACS2016_API web section for more details.

Items Retrieved in the API Calls
The sample header record above shows the subject matter item listed at the left in the following set of items. Modify API call and use other subject matter items. See full array of subject matter – xlsx file.
.. B01003_001E – Total population
Age
.. B01001_011E — Male: 25 to 29 years (illustrating age cohort access)
.. B01001_035E — Female: 25 to 29 years (illustrating age cohort access)
Race/Origin
.. B02001_002E – White alone
.. B02001_003E – Black or African American alone
.. B02001_004E – American Indian and Alaska Native alone
.. B02001_005E – Asian alone
.. B02001_006E – Native Hawaiian and Other Pacific Islander alone
.. B02001_007E – Some other race alone
.. B02001_008E – Two or more races
.. B03001_003E – Hispanic (of any race)
Income
.. B19013_001E – Median household income ($)
.. B19113_001E – Median family income ($)
Housing & Households
.. B25001_001E – Total housing units
.. B25002_002E – Occupied housing units (households)
.. B19001_017E — Households with household income $200,000 or more
.. B25003_002E — Owner Occupied housing units
.. B25075_025E — Housing units value $1,000,000 to $1,499,999
.. B25075_026E — Housing units with value $1,500,000 to $1,999,999
.. B25075_027E — Housing units with value $2,000,000 or more
.. B25002_003E – Vacant housing units
.. B25077_001E – Median housing value ($) – owner occupied units
.. B25064_001E – Median gross rent ($) – renter occupied units

The rightmost fields/columns in the rows/records contain the area name and geographic codes.

Using API Tools for 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 L

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.

Examining Appalachia City Characteristics & Trends

.. using tools and data to examine geographic, demographic, economic characteristics of the Appalachia Region .. Appalachia is a region that includes parts of 13 states, 420 counties, and has long been challenged with poverty. This section is part of a series focused on Appalachia.  See related more detailed Web section.

The Appalachia Region; Lay of the Land
The population of Appalachia increased from 25.1 million in 2010 to 25.5 million in 2016, an increase of 289,806. The following graphic shows how Appalachia region counties have gained population (blue and green) and lost population (orange and red) during the period 2010 to 2016. Click graphic for larger view; expand browser window for best quality view.

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

Cities in Appalachia
In 2016, there were 2,393 cities in Appalachia. Seven cities had population over 100,000; 16 cities had over 50,000 population and 213 cities had 10,000 or more population.

The following graphic shows cities (red markers) with 2016 population of 10,000 or more in the Appalachia region in context of counties (yellow fill pattern). Click graphic for larger view; expand browser window for best quality view. Larger view shows city names except where labels could overlap.

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

Growing Cities
The following view shows cities as green markers having 5,000+ 2016 population with growth of 500+ or more population, 2010-2016.

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

Cities & Metros in Appalachia
The following graphic shows Metropolitan Statistical Areas (green fill pattern) that intersect with Appalachia region counties. Note that some metros only partly intersect with Appalachia. County boundaries are shown as overlay on metros. For example, only northern counties of the Atlanta metro (see pointer) are Appalachia counties. “Edge” Appalachia metros create opportunities for nearby Appalachia counties. Cities within Appalachia and having 50,000+ 2016 population are shown with orange markers. Click graphic for larger view; expand browser window for best quality view.

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

Characteristics of Metros, Cities and School Districts
• Demographic-economic profiles for selected cities
Examples (click link above to view other cities; click links below for specific city profiles):
.. Cumberland, MD [2421325] (19,978)
.. Frostburg, MD [2430900] (8,676)
Access any/all U.S. city(s) — http://proximityone.com/places15dp1.htm
• Demographic-economic profiles for selected school districts
Examples (click link above to view other districts; click links below for specific district profiles):
.. Allegany County Public Schools, MD [2400030]
.. Pittsburgh School District, PA [4219170]
Access any/all U.S. school district(s) — http://proximityone.com/sd15dp1.htm
• S&O metro reports

Examining Characteristics of All Cities/Places
Use these resources to examine all U.S. cities/places.
• Cities/Places Main Section
• America’s Communities Program — city profiles
• All Cities/Places — 4 Web section/tables
• City Population Estimates & Trends 2010-2016 interactive table

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 Block Group Demographics

.. tools & data to analyze sub-census tract households, education, income, housing, more … Block Groups, subdivisions of census tracts, are the smallest geographic areas for which “richer demographics” are developed by the Census Bureau. Block group demographic-economic estimates, based on Census 2010 geography, are annually updated beginning with American Community Survey (ACS) 2010. The latest ACS estimates for these 217,740 areas covering U.S. wall-to-wall are from ACS 2015. The ACS 2016 update will be released in December 2017.  See the related Web section for more detail about accessing and using block group geography and demographic-economic data.

Patterns of Economic Prosperity by Block Group
The following graphic shows patterns of median household income by block group in the Houston, TX area. Markers show block groups with 10 or more housing units having value of $2 million or more. Markers are labeled with the number of housing units having value of $2 million or more in that block group. Click graphic for larger view, more detail and legend color/data intervals. This map illustrates the geographic level of detail available using block group demographics and the relative ease to gain insights using geospatial data analytics tools.

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

Block Group Demographic-Economic Data & Shapefiles
… selection of key demographic-economic attributes; annual update
… subject matter categories include:
  • Total population>
  • Population by gender iterated by age
  • Population by race/origin
  • Households by type of household
  • Educational attainment by detailed category
  • Household Income by detailed category
  • Housing units by owner/renter occupancy
  • Housing units by units in structure
  • Housing units by detailed value intervals

See the related Web section for a detailed list of items.

Use these Data on Your Computer
Use the above U.S. national scope dataset with your own software or in ready-to-use GIS projects with 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.