Monthly Archives: March 2016

County Population Trends 2010-2015

.. examining the how and why of U.S. population change by county from 2010 to 2015. This section provides an overview of this topic and provides a summary of tools, interactive table and GIS project, to analyze population change by county using latest Census Bureau estimates data through 2015. These data are used by ProximityOne to develop/update annual county demographic-economic projections. See related Web section for more detail.

Patterns of Population Change by County, 2010-2015
The following graphic shows how counties have gained population (blue and green) and lost population (orange and red) during the period 2010 to 2015. Click graphic for larger view; expand browser window for best quality view.

.. view developed with ProximityOne CV XE GIS and related GIS project.
.. see related drill-down views of Texas by county

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

Interactive Analysis
Use the interactive table to view population trends and components of change for selected counties. The following graphic illustrates how the table can be used.
• Click the ShowAll button (below table)
• Click the Pop Min & Max button .. refreshes table
    to show only counties with 2015 population 250,000-300,000
• Click ChgCols button to show all 2010-15 change columns
• Click PopChg 2010-15 header column to sort.

Resulting view:
Among these counties, Horry County, SC has the largest 2010-15 population change. The peer group counties are shown in rank order.

– Click graphic for larger view.
– experiment with settings 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.

Metro Situation & Outlook Reports Updated

.. how are metros of interest changing? The Metro Situation & Outlook Reports provide the premier integrated, multi-sourced demographic-economic overview for individual metropolitan areas.

Largest 25 Metros Based on 2015 Population
Click graphic for larger view with names. Expand browser window for best view. Label shows metro rank among all 917 metros based on 2015 population.

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

The no fee report for each metro was updated today with the annually updated population and population components of change. Use this interactive table to view, query, rank metros. Examine total population annually 2010 to 2015 and rankings.

Click on a link in the interactive table to view the integrated, multi-sourced demographic-economic Situation & Outlook report for that metro. See this example for the Charlotte-Concord-Gastonia, NC-SC MSA. The metro report provides drill-down demographic-economic attributes of metro component areas including counties, cities and school districts.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Tip of the Day – Median Housing Value by ZIP Code

.. tip of the day .. a continuing weekly or more frequent tip on developing, integrating, accessing and using geographic, demographic, economic and statistical data. Join in .. tip of the day posts are added to the Data Analytics Blog on an irregular basis, normally weekly. Follow the blog to receive updates as they occur.

.. 5 ways to access/analyze the most recent estimates of median housing value and other subject matter by ZIP Code area .. based on the American Community Survey (ACS) 5-year estimates. See related Web section.

Option 1. View the data as a thematic pattern map
Option 1 is presented as Option 1A (using CV XE GIS) and Option 1B (using Visual Data Analytics VDA Mapserver). See more about GIS.

Option 1A. View $MHV as a thematic pattern map; using CV XE GIS:
— Median Housing Value by ZIP Code Area; Los Angeles Area
Click graphic for larger view with more detail.

Click graphic for larger view.
Use the Mapping ZIP Code Demographics resources to develop similar views anywhere in U.S.

Option 1B. View $MHV (ACS 2018) as a thematic pattern map; using VDA Mapserver:
— Median Housing Value by ZIP Code Area; Phoenix/Scottsdale, AZ area
Click graphic for larger view with more detail.

Click graphic for larger view. Expand window to full screen for best quality view. View features:
– profile of ZIP 85258 (blue crosshatch highlight) shown in Attributes panel at left
– values-colors shown in Legend panel at left
– transparency setting allows “see through” to view ground topology below.
Use VDA Mapserver: to develop similar views anywhere in U.S. using only a browser. Nothing to install.

Option 2. Use the interactive table:
– go to http://proximityone.com/zip18dp4.htm (5-year estimates)
– median housing value is item H089; see item list above interactive table.
– scroll left on the table until H089 appears in the header column.
– that column shows the 2018 ACS H089 estimate for for all ZIP codes.
– click column header to sort; click again to sort other direction.
– see usage notes below table.

Option 3. Use the API operation:
– develop file containing $MHV for all ZIP code areas in U.S.
– load into Excel, other software; link with other data.
– median housing value ($MHV) is item B25077_001E.
click this link to get B25077_001E ($MHV) using the API tool.
– this API call retrieves U.S. national scope data.
– a new page displays showing a line/row for each ZIP code.
– median housing value appears on the left, then ZIP code.
– optionally save this file and import the data into a preferred program.
– more about API tools.
Extending option 3 … accessing race, origin and $MHV for each ZIP code …
click on these example APIs to access data for all ZIP codes
.. get extended subject matter for all ZIP codes
.. get extended subject matter for two selected ZIP codes (64112 and 65201)

Items used in these API calls:
.. 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_023E — Housing units value $500,000 to $749,999
.. B25075_024E — Housing units with value $750,000 to $999,999
.. B25075_025E — Housing units with value $1,000,000 or more
.. B25002_003E – Vacant housing units
.. B25077_001E – Median housing value ($) – owner occupied units
.. B25064_001E – Median gross rent ($) – renter occupied units

View additional subject matter options.

Option 4. View the $MHV in context of other attributes for a ZIP code.
Using – ACS demographic-economic profiles. Example for ZIP 85258:
General Demographics ACS 2018 .. ACS 2017
Social Characteristics ACS 2018 .. ACS 2017
Economic Characteristics ACS 2018 .. ACS 2017
Housing Characteristics ACS 2018 .. ACS 2017 .. $MHV shown in this profile.

Option 5. View 5- and 10-mile circular area profile from ZIP center.
– profile for ZIP 80204 dynamically made using SiteReport tool.
– with SiteReport running, enter the ZIP code, radii and click Run.
– comparative analysis report is generated in HTML and Excel structure.
Click this link to view resulting profile.
– from the profile, site 2 is 1.9 times the population of site 1.
– Site 1 $MHV is $296,998 compared to Site 2 $MHV $269,734.
– GIS view with integrated radius shown below.

This section is focused on median housing value and ZIP code areas. Many other subject matter items will be apparent when these methods are used. Optionally adjust above details to view different subject matter for ZIP codes.

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.

Citizen Voting Age Population by Block Group

.. tools and resources to access and analyze citizen voting age population by block group … ideally analysts and stakeholders will examine patterns and characteristics of the citizen voting age population (CVAP) by block group. This is partly because of the extreme variability of CVAP within higher level geography — even at the census tract level. This becomes even more important in more densely populated areas. See about ACS 2014 CVAP block group demographics in this related Web section.

Patterns of ACS 2014 CVAP Population by Block Group
— Houston Area
See legend in lower right of graphic for interval/color correspondence. Click graphic for larger view; expand browser window for best quality view.

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

The size, characteristics and distribution of the citizen voting age population by block group is very important.
• Block groups are the most granular geography at which we can study these demographics.
• The size of the citizen voting age population ultimately determines election outcomes.

This section provides thematic pattern map views and analyses of selected metros. These applications can be replicated for any area. They serve as an “analytical basis” that can be augmented with other methods and data (e.g., voter registration, voter propensity, voter turnout, and other election factors) to gain insights into election outcomes under alternative scenarios. Equally important, this information can be used to better equip voters with the potential impact of improved voting activity for their own neighborhood and larger areas (e.g., even congressional districts).

Using these GIS Resources; Obtaining Custom Maps & Analyses
Contact us (or call 888.364.7656) for maps and analyses for areas of interest or to use the integrated, ready-to-use, national scope GIS software, GIS project and datasets. Add your own data; create custom views.

CVAP Block Group Thematic Pattern Map shown below for Selected Areas
• Atlanta
• Chicago
• Los Angeles
• Kansas City
• Washington, DC

Patterns of ACS 2014 CVAP Population by Block Group
— Atlanta Area
See legend in lower right of graphic for interval/color correspondence. Click graphic for larger view; expand browser window for best quality view.

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

Patterns of ACS 2014 CVAP Population by Block Group
— Chicago Area
See legend in upper right of graphic for interval/color correspondence. Click graphic for larger view; expand browser window for best quality view.

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

Patterns of ACS 2014 CVAP Population by Block Group
— Los Angeles Area
See legend in upper right of graphic for interval/color correspondence. Click graphic for larger view; expand browser window for best quality view.

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

Patterns of ACS 2014 CVAP Population by Block Group
— Kansas City Area
See legend in lower right of graphic for interval/color correspondence. Click graphic for larger view; expand browser window for best quality view.

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

Patterns of ACS 2014 CVAP Population by Block Group
— Washington, DC Area
See legend in lower right of graphic for interval/color correspondence. Click graphic for larger view; expand browser window for best quality view.

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

ACS 2014 CVAP Block Group Demographics
For the 217,479 block groups covering the U.S. wall-to-wall, the median citizen population value is 1,165 (291.8 million population) and the median citizen voting age population is 885 (220 million population). The median total population is 1,252 (314 million population). These data are based on the 2014 American Community Survey ACS 2014 CVAP special tabulation completed in early 2016. WHile the focus here is on the total population, the same scope of data is integrated into the shapefiles used here for 13 race/origin population groups. The 13 race/origin groups include:
  • American Indian or Alaska Native Alone
• Asian Alone
• Black Alone
• Native Hawaiian or Other Pacific Islander Alone
• White Alone
• American Indian or Alaska Native and White
• Asian and White
• Black and White
• American Indian or Alaska Native and Black
• Remainder of Two or More Races
• not Hispanic
• Hispanic (of any race)

Related CVAP Sections
Census Tracts; ACS 2009-13 special tabulation
Census Tracts; ACS 2009-13 special tabulation – Hispanic focus
Tracts & Congressional Districts; ACS 2009-13 special tabulation

See this blog post in this full, more detailed Web section.

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.

Developing & Using Map Graphics

.. steps to develop map graphics & visual analysis of market/study areas .. map graphics are an important part of most demographic-economic analyses and essential for many applications. Not only are are maps needed to show geographic boundaries and the relative location of geography within a broader area, they can come alive by showing patterns. A thematic pattern map of median household income by block group is a good example; higher and lower areas of economic prosperity by neighborhood can be immediately determined. Map graphics can improve our ability to communicate complex information. Convey information faster. Make more compelling presentations. Collaborate more effectively through the use of map graphics.  See related Web section for more details.

The focus of this section is on creating and using KML files to prepare map graphics for use in developing Market-Study Area Comparative Analysis Reports. These files and map graphics also have broader uses. Steps are reviewed to develop the KML circular area map graphics files, convert them to shapefile structure and integrate both files into mapping and GIS applications and put them into operational use. 

KML (Keyhole Markup Language) files are XML structured files useful for visualizing geographic objects (like circles) using Internet-based browsers, notably Google Earth. Why develop/use KML files? They are easy to create with precision, there is little to no learning curve, they can be used in many venues and they are free to develop. KML files can be used side-by-side with shapefiles. Shapefiles, structured very much unlike KML files, are the dominant vector-based file structure used in GIS applications involved in both viewing and geospatial analysis. 

Developing Circular KML Files & Map Graphics
An “objective view” of this section is shown in the following graphic. The graphic shows a study site location (red marker), 1-mile & 3-mile radius circles. The site location is a Starbucks located at 302 Nichols Road, Kansas City, MO 64112. The view shows a circular KML-based graphics in context of patterns of median household income by block group. Develop similar views for any area, any site circular configuration, using steps reviewed in this section.

– view developed using CV XE GIS

Creating the KML Circular Graphics File
Proceed through the next steps to develop a KML file used to create the graphic below on left — a Starbucks located at 302 Nichols Road, Kansas City, MO 64112. Graphic on the right is a Starbucks location in Paris, used to illustrate this process works globally. Both graphics include study area center point and 1-mile and 3-mile radius circles.

302 Nichols Road, Kansas City, MO 64112
23 Avenue de Wagram, 75001 Paris, France

Start the create KML file application
• Key in address 302 Nichols Road, Kansas City, MO 64112 to Google Maps
.. see the latitude-longitude (39.041548,-94.592965) in the URL bar.
• Open this web page to create the circles & save results as KML file.
• Refresh this page if making a new KML file.
• Set the colors and lines to medium, blank and clear.
• Enter coordinates — key in lat 39.041548 and lon -94.592965
.. these for for this example
.. enter the values for your location of interest
Add center point
• In the Radius Distance, key in 0.05 miles
• Click Draw Radius blue button (at right of longitude).
Add site 1 circle
• In the Radius Distance, key in 1.00 miles (use preferred radius for inner circle).
• Click Draw Radius blue button (at right of longitude).
Add site 2 circle
• In the Radius Distance, key in 3.00 miles (use preferred radius for inner circle).
• Click Draw Radius blue button (at right of longitude).
View study area geography
• Optionally navigate up to the map view and make the view similar to the graphic at the top of this page 
.. this step is not required but might be useful to verify the study area appearance.
Save KML file
• Navigate down the page to “Google Earth KML Output”. Click the blue button Generate KML.
• Click “Download KML file Here.” Save the file to a folder and make a note of the file path and name
.. save the file as c:\sitereport\302nichols.kml (this file and filename are used below).
Done
• The three part KML file has been created and saved to the local computer. 
• Finished using this browser application.

This same process may be used again to create similarly structured KML files of any radius about any point for any location in the world. 

Loading a KML file into Google Maps
Optionally create the objective map graphic using the following steps. Or, the KML file may be used with the CV XE GIS software (see below) enabling yet further analytical possibilities. 

 Click this link to start the Google MyMaps application.
• When the new page opens click create new map button
• Next click import button
• Enter the file path/name as created above (c:\sitereport\302nichols.kml), or any KML file.
• Edit the MyMaps rendering to achieve preferred view.
• Use preferred screen capture tool to save that part of the map view as a graphic for the study report.

Using the KML File with an Existing GIS Project and converting the KML file to shapefile structure

1. Add the KML file to an Existing CV XE GIS Project
• Start the CV XE GIS software and open the project file c:\cvxe\1\cvxe_us2.gis (distributed with installer).
.. uncheck Locations and $MHI x BG layers in legend panel.
• Click the AddLayer button (second button from left on toolbar)
• Select the KML file that was created above (c:\sitereport\302nichols.kml) .. circles appear in the map window.
• Use LayerEditor to adjust settings for KML layer (transparent, bold outline)
• Navigate to zoom-in view and smaller map window.
• Use Toolbar button Save to Image (button 7 from left) to save the map window view to a .jpg file.

Navigate to this view:

2. Converting a KML File to a Shapefile
This step requires the CV XE GIS Basic or higher level version. After the KML layer appears in the above sequence, proceed as follows:

• Click File>ExportShapefile.
• Select the KML layer name.
• Set Coordinate System edit box value to NAD83.
• Click OK button.
• On the Export Layer/FileSave dialog, select an output file path and name.
• The shapefile is generated and may be reused with any GIS project.

3. Editing attributes of the study area shapefile and project file
There are three shapes in the shapefile (center point, circle 1, circle 2). 
Modify the appearance of these shapes/objects by using the Select tool (mouse in Select mode).
• In legend panel click on circles layer; name turns blue indicating this is the active layer.
• In the map window, click in the circle; the profile/editor appears (pop-up)
• Initially all three shapes have the name “Polygon”.
.. change the object names successively to Point1 (the small circle), Circle1 and Circle2.
• The shapefile attributes have been permanently changed.
• When each shape/object has been renamed, use the LayerEditor to modify the appearance of each shape.
.. the changes modify the project file and not the shapefile.
.. optional save the project (overwriting the former version) or save the project with a new name.

Renaming a shape to “Point1”
Click for larger view

Using LayerEditor to set attributes of the study area layer
Click for larger view

View of final study area layer in context of broader project
Click for larger view

View as above with $MHI x BG checked on/visible
Click 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.

Low and Moderate Income Demographics by Block Group

.. tools and resources to access and use low and moderate income demographics by block group … the U.S. Department of Housing and Urban Development (HUD) sponsored development of the ACS 2006-10 “low and moderate income population (LMI) by block group” special tabulation released in 2015. This is an important data resource for HUD as well as others who need to examine characteristics of the LMI population by block group and related small area geography. See related Web section for more details on topics covered here data.

This section reviews tools to use these data on a national or local level:
1. Site analysis tools
2. GIS software and national scope LMISD BG GIS project
3. National scope BG-level interactive table
See the related Web section for more detailed information.

Patterns of LMI Population by Block Group
The following graphic shows block groups with 51% or more LMI population with orange fill pattern. See related zoom-in views. Click graphic for broader Chicago area view. Expand browser window for best quality view.

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

Block Groups & American Community Survey (ACS) Data
There are several features of block groups that make this an important geography for data analytics. Block groups average 1,200 population and are the the smallest geographic area for which the ACS data are tabulated. The approximate 220,000 block groups are subdivisions of census tracts and cover the U.S. wall-to-wall. Only ACS provides national scope demographic-economic data at the block group level.

Analytical Tools & the ACS LMI Block Group Data
Tools reviewed below make use of one specific block group (170317115002) in the Chicago area. The tools may be applied to any other block group (BG) or set of BGs. Block groups are uniquely identified by the 12 character BG geocode. The BG code 170317115002 refers to block group 2 in census tract 711500 in county 031 in state 17.

1. Study Area Comparative Analysis Reports
Examine characteristics of circular area reports based on block groups within those areas. The following graphic shows a partial view of a 1- and 3-mile radius report developed for lat-lon location (41.7324422, -87.6410861) BG 170317115002 internal lat-lon. Click graphic to view entire report. This type of report can be prepared for any address/location/lat-lon and area size from less that one mile to many miles. These reports include a much larger set of demographic-economic data than included in the HUD LMISD. The comparative analysis structure makes it easy to compare one site/location with another and their difference.

.. report developed with ProximityOne SiteReport.

2. Using GIS Resources
— LMI 51% or More; Chicago Area Block Groups

Block groups with 51% or more LMI population shown with orange fill pattern. Mini profile displayed for block group at pointer – 170317115002 – find in table below. LMI percent shown as 55.03%. LMI-BG layer shown in context with Public Use Microdata Area 03531. Develop custom estimates of the population for this PUMA using the ACS PUMS data. Integrate other types of geography and data. Click graphic for broader Chicago area view. Expand browser window for best quality view.

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

See more information here about using the GIS project used to develop maps in this section and more generally develop your own maps and perform geospatial analysis.

3. Using the Interactive Table
Use the interactive table to view, query, rank and analyze LMI demographics by block group. The following graphic illustrates one application. The state of Arizona is selected using the state selection tool below the table. The Low Income column header cell is dbl-clicked, sorting the table on the estimate of the Low Income population by block group. It is easy to see that BG 040270116002(blue highlighted) has the largest Low Income population among all BGs in Arizona.

Try using the interactive table for geography of interest. The interactive table is a very useful tool when used in combination with the GIS application.

What’s next is data integration. Upcoming posts will review similar, but different, updated block group demographics and their use with data reviewed here. See the main block group Web page.

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.

Characteristics of the U.S. Population & Housing

… examining demographic-economic characteristics and patterns of the United States … the United States median household income was $51,371 in 2012 and $53,657 in 2014 — a change of $2,286 (4.5%). These are the most recent estimates and based on the American Community Survey (ACS). What about other attributes? The population who spoke a language other than English “not very well” in 2012 was approximately 25 million — that number increased by approximately 500 thousand between 2012 and 2014 — an example of other subject matter. The table and data provided in this section provides much more detail. This section can be a handy reference. Bookmark the related full Web page.

ACS provides annual data. Data for 2012 and 2014 are used here as 1) the 2014 data are the most recent and 2) comparing change over two years might provide improved insights as compared to a 1-year change.

There are many statistical programs that provide wide-ranging measures of U.S. demographic-economic attributes. Among the many important features of the ACS data is this unique feature: the ACS data provides largely the same scope of subject matter at the national level down to the block group level. Block groups cover the U.S. wall-to-wall with detailed geographic granularity (217,000 areas). For example, compare the U.S. ACS 2012 or 2014 5-year estimates

The Census 2010 population of the United States was 308,745,538. The table shown below provides updated demographics developed by ProximityOne using data from ACS. For areas of 65,000 population or more, ACS 1-year estimates are tabulated, as shown in this table. For smaller population areas (and for all areas), ACS 5-year estimates are also tabulated. All ACS data are estimates and subject to errors of estimation and other errors. See more about comparing these data over time.

Corresponding tables for selected areas:
United States
United Statesxls — 1-year — 2012-2014 (same data as shown below)
United Statesxls — 5-year — 2012-2014
Texas
State of Texasxls — 1-year — 2012-2014
State of Texasxls — 5-year — 2012-2014
School Districts
Dallas ISDxls — 1-year — 2012-2014
Dallas ISDxls — 5-year — 2012-2014

United States Demographic-Economic Characteristics
Below is a graphic illustrating the table. Click graphic to view entire 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.

Tip of the Day – Median Household Income by School District

.. tip of the day .. a continuing weekly or more frequent tip on developing, integrating, accessing and using geographic, demographic, economic and statistical data. Join in .. tip of the day posts are added to the Data Analytics Blog on an irregular basis, normally weekly. Follow the blog to receive updates as they occur. Options and tools for accessing and using median household income by school district are outlined below.

Richmond & Henrico County, VA School Districts
  – patterns of median household income by census tract; an illustration.
  – often drill-down geography, like census tracts, is needed.
  – click graphic for larger view.
.. view developed with ProximityOne CV XE GIS and related GIS project.

Accessing/Using Median Household Income by School District
.. the most recent estimate of median household income for school districts is as of 2014. These data are based on the American Community Survey (ACS2014) 5-year and 1-year estimates. See details about other years and longitudinal data below in this section. The subject matter “median household income” is used here but other wide-ranging subject matter can be accessed/analyzed using options described below.

Number and Type of Schools Districts — ACS 2014 tabulation areas
– 2013-2014 school year; as of January 1, 2014

Geographic Areas 1-year estimates 5-year estimates
population of 65,000+ all areas
School District (Elementary) 74 2,181
School District (Secondary) 88 538
School District (Unified) 842 10,923
Total 1,004 13,012

Option 1. Use the interactive table:
– go to http://proximityone.com/sd14dp3.htm (5-year estimates)
– median household income is item E086.
– scroll left on the table until E086 appears in the header column
– this column shows the data for E086 for all school districts
– see usage notes below table.

Option 2. Use the API operation:
– 5-year estimates for unified school districts in Arizona …
– median houshold income (MHI) is item B19013_001E.
click this link to get B19013_001E (MHI) using the API tool.
.. this API must be used on a state-by-state basis.
.. the state FIPS code must be the last two characters in the URL.
– a new page displays showing a line/row for each school district.
– MHI appears on the left, then school district name and then codes.
– optionally save this file and import the data into a preferred program.
– more about API tools.
– more about using 1-year and 5-year estimates.

Option 3. View the median household income in context of other attributes for a school district.
click this link to select a school district of interest.
– click link to view school district report (request a district).
– when report displays, scroll down in table to the household income section.

See the related section on school district community.

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

Data for Other Years & Longitudinal Data
Annual data for median household income by school district are available from the American Community Survey as summarized below.

ACS Year School Year Boundary as of:
2009 2008-2009 January 1, 2008
2010 2009-2010 January 1, 2010
2011 2009-2010 January 1, 2010
2012 2011-2012 January 1, 2012
2013 2011-2012 January 1, 2012
2014 2013-2014 January 1, 2014

Join me in a Data Analytics Lab session to discuss more details about accessing and using children’s demographics, schools and school districts 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.