Category Archives: TIGER/Line

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.

Developing Geographic Relationship Data

.. tools and methods to build and use geographic relationship files … which census blocks or block groups intersect with one or a set of school attendance zones (SAZ)? How to determine which counties are touched by a metropolitan area? Which are contained within a metropolitan area? Which pipelines having selected attributes pass through water in a designated geographic extent? This section reviews use of the Shp2Shp tool and methods to develop a geographic relationship file by relating any two separate otherwise unrelated shapefiles. See relasted Web page for a more detiled review of using Shp2Shp.

As an example, use Shp2Shp to view/determine block groups intersecting with custom defined study/market/service area(s) … the only practical method of obtaining these codes for demographic-economic analysis.

– the custom defined polygon was created using the CV XE GIS AddShapes tool.

Many geodemographic analyses require knowing how geometries geospatially relate to other geometries. Examples include congressional/legislative redistricting, sales/service territory management and school district attendance zones.

The CV XE GIS Shape-to-Shape (Shp2Shp) relational analysis feature provides many geospatial processing operations useful to meet these needs. Shp2Shp determines geographic/spatial relationships of shapes in two shapefiles and provides information to the user about these relationships. Shp2Shp uses the DE-9IM topological model and provides an extended array of geographic and subject matter for the spatially related geometries. Sh2Shp helps users extend visual analysis of geographically based subject matter. Examples:
• county(s) that touch (are adjacent to) a specified county.
• block groups(s) that touch (are adjacent to) a specified block group.
• census blocks correspond to a specified school attendance zone.
• attributes of block groups crossed by a delivery route.

Block Groups that Touch a Selected Block Group
The following graphic illustrates the results of using the Shp2Shp tool to determine which block groups touch block group 48-85-030530-2 — a block group located within McKinney, TX. Shp2Shp determines which block groups touch this block group, then selects/depicts (crosshatch pattern) these block groups in the corresponding GIS map view.

Geographic Reference File
In the process, Shp2Shp creates a geographic relationship file as illustrated below. There are six block groups touching the specified block group. As shown in the above view, one of these block groups touches only at one point. The table below (derived from the XLS file output by Shp2Shp) shows six rows corresponding to the six touching block groups. The table contains two columns; column one corresponds to the field GEOID from Layer 1 (the output field as specified in edit box 1.2 in above graphic) and column 2 corresponds to the field GEOID from Layer 2 (the output field as specified in edit box 2.2 in above graphic). The Layer 1 column has a constant value because a query was set (geoid=’480850305302′) as shown in edit box 1.3. in the above graphic. Any field in the layer dataset could have been chosen. The GEOID may be used more often for subsequent steps using the GRF and further described below. It is coincidental that both layers/shapefiles have the field named “GEOID”.

Layer 1 Layer 2
480850305302 480850305272
480850305302 480850305281
480850305302 480850305301
480850305302 480850305311
480850305302 480850305271
480850305302 480850305312

Note that in the above example, only the geocodes are output for each geography/shape meeting the type of geospatial relationship. Any filed within either shapefile may be selected for output (e.g., name, demographic-economic field value, etc.)

How it Works — Shp2Shp Operations
The following graphic shows the settings used to develop the map view shown above.

See related section providing details on using the Shp2Shp tool.

Geographic Relationships Supported
The Select Relationships dropdown shown in the above graphic is used to determine what type of spatial relationship is to be used. Options include:
• Equality
• Disjoint
• Intersect
• Touch
• Overlap
• Cross
• Within
• Contains
See more about the DE-9IM topological model used by Shp2Shp.

Try it Yourself

See full details on how you can use any version, including the no fee versin, of CV XE GIS to use the Shp2Shp tools. Here are two examples what you can d. Use any of the geospatial relatoinships. Apply your own queries.

Using Touch Operation
Select the type of geographic operation as Touch. Click Find Matches button. The map view now shows as:

Using Contains Operation
Click RevertAll button. Select the type of geographic operation as Contains. Click Find Matches button. The map view now shows as:

Relating Census Block and School Attendance Zones
The graphic shown below illustrates census blocks intersecting with Joyner Elementary School attendance zone located in Guilford County Schools, NC (see district profile). The attendance zone is shown with bold blue boundary. Joyner ES SAZ intersecting blocks are shown with black boundaries and labeled with Census 2010 total population (item P0010001 as described in table below graphic). Joyner ES is shown with red marker in lower right.


– view developed using CV XE GIS and related GIS project; click graphic for larger view

See more about this application in this related 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.

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

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

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

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

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

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

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

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

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

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

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

National Children & Education Statistics Program Updates

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

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

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

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

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

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

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

See the School Districts Economic Characteristics Interactive Table.

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

See NCES Main Section.

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

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

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

Creating Maps & GIS Projects

.. follow these steps to create custom maps & GIS projects .. while maps are “everywhere,” there is a continuing need to make new maps. Reasons for this include changing underlying geography, new features (like stores or customers to be viewed), visually examining geographic relationships not available elsewhere (e.g., census tracts and ZIP codes), different geographic depictions for an area (smoothed versus precise vertices) and other reasons. A map can provide view(s) that relate to geospatial analysis; map visualization can be indispensable (showing road features adjacent to selected properties).

View of Initial Map Objective — University Park, TX; Dallas Metro area
Census tracts (black boundary) shown with census tract code as label.

— view developed using CV XE GIS software

Follow steps in this section to make a map like above for any area in the U.S. This section provides an overview of how to use the CVGIS software to quickly build a map. It is actually more than a map, it is the process of building a GIS project. A map is one rendering that can be displayed, and optionally published, using a GIS project. Map/GIS project development steps reviewed here can be performed using the no fee CVGIS software and no fee data resources, CVGIS Levels 1 and higher can save the GIS project and have additional geography available. With geographic extension, the process illustrated here can work for any place in the world. A GIS project is a file itself that contains references to map files (shapefiles) located on your computer. Once a GIS project has been created and saved, it can be immediately opened with CVGIS using the File>Open operation. After turning your computer off, and restarting it, the GIS project can be re-opened to display the same view as saved in an earlier session.

No Previous GIS/Mapping Experience Required
This section is designed for use by anyone including those with no previous GIS/mapping experience. Requirements are a Windows computer and Internet access. This section is a part of a module used in the Certificate in Data Analytics and the CVGIS Certification Programs. Developers can also benefit from this and related tutorials to learn more about how GIS can be integrated with other data analytics tools and methods.

Making Maps Steps
The objective of this session is to develop a map (and GIS project) to view characteristics of census tract “48113019301”. The first step in making a map (GIS project) is to have a clear objective. This 11 character geocode uniquely identifies this Census 2010 census tract among all other 73,057 tracts in the U.S. See more about census tract geography and geocodes. While this application shows a process for adding only two layers, it could be extended by adding more. Similarly, while this application uses a census tract boundary files (shapefile), alternatives are census blocks, block groups, ZIP code areas, among others.

These steps should take an inexperienced user 10-15 minutes to develop a new CVGIS project view. If anything becomes confused, close the program and start over.
Step 1. Install CVGIS (1/1/2017 or later version)
Step 2. Open Base Project
Step 3. Get Census Tract Shapefile
Step 4. Get Roads Shapefile
Step 5. Modify Map View
Step 6. Optionally Save GIS Project

The view should now be similar to the view at the top of this section.

Next Steps
Try the process yourself with geography of interest to you. View/use other “Creating Maps & GIS Projects” tutorials to learn about:
• integrating subject matter
• developing and using thematic maps
• creating site profiles

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.

State Population & Components of Change: 2010-2016

.. data and tools to examine how state demographics are changing 2010-2016 … using the new 2016 population and components of changes estimates. The U.S. population changed from 308,758,105 (2010) to 323,127,513 (2016), a change of 14,369,408 (4.7%). Only three states lost population. See the growth rates for DC and the remaining states in this table. Highest growth rates were in D.C., North Dakota, Texas, Utah and Colorado.

Patterns of Population Change, 2010-2016, by State
The following graphic shows the percent population change by state with labels showing the rank among all states based on the percent change in population, 2010-16.

View created with CVGIS and related GIS project. Click graphic for larger view.

Resources to Analyze these Data
Use our tools to view and analyze annual population estimates, 2010 to 2016, rankings and components of change for the U.S., regions and states. Use the interactive table below in this section to view, rank, compare these data. Use the GIS tools and ready-to use project described below in this section to create maps for states and regions of interest. Create thematic maps for any of the fields/measures shown in the interactive table. Change color patterns and labels. Integrate your own data.

Using Interactive Table
Use the interactive table to view, rank, compare, query states based on a selection of demographic measures. The following graphic illustrates how the table can be used. Click graphic for larger view.

The graphic shows the largest 10 states ranked in descending order based on 2016 population. The column “PopChg Rank 10b16” (second from right) shows the rank of this state, among all states, based on the population change from 2010 to 2016. The rightmost column shows the state’s rank for the period based on percent change in population over the period.

Largest 10 States based on 2016 Population

Try it yourself. Use the table to examine state patterns and characteristics based on your selected criteria.

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

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

School District Demographic Trends: 2010-2015

.. data and tools to examine how school districts of interest are changing … based on total population, the largest 10 school districts in 2015, all experienced an increase in total population over the period 2010-2015. Five of these districts had a decrease in school age population (ages 5-17 years). Four of these districts had a decrease in the number of related children in families ages 5-17 years. See characteristics of districts in this interactive table. See the related Web section for more details.

School Districts with 2015 Population 100,000 or More
More than 600 of the total 13,245 school districts have a total 2015 population of 100,000 or more (red markers).

– view developed with CVGIS software and related GIS project.

Using New 2015 Estimates Released December 2016
– for use in 2017 ESEA Title I Allocations
Analyze annual demographic data for each U.S. school district for the period 2010 through 2015. These data include the Federal official 2015 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. Use the interactive table in this section to view, rank, compare, query demographic characteristics of districts of interest.

The annual estimates for each school district include:
• total population
• number of children ages 5 to 17
• number of related children ages 5 to 17 in families in poverty

Using Interactive Data Tools
Use the interactive table to view, rank, compare, query ZIP codes based on a selection of demographic measures. The following graphics illustrate how the table can be used. Click graphic for larger view.

Total Population — 10 districts with largest change 2010-15
– ranked descending on rightmost column

– click graphic for larger view.

School Age Population — 10 districts with largest change 2010-15
– ranked descending on rightmost column

– click graphic for larger view.

Related Children Ages 5-17 in Poverty
– 10 districts with largest change 2010-15
– ranked descending on rightmost column

– click graphic for larger view.

Try it yourself. Use the table to examine a set of districts on your selected criteria in for a state/area 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.