Category Archives: Social Characteristics

Tools to Analyze County Demographic-Economic Characteristics

.. demographic-economic characteristics of counties are essential for business development, market analysis, planning, economic development, program management and general awareness of patterns and trends. This section provides access to data and tools to examine these data for all counties in the U.S. This annual update includes geographic area characteristics based on ACS 2015 data.  The tools/data are organized into four related sections summarized below.

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

… view developed using the CV XE GIS software.

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

… view developed using the CV XE GIS software.

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

… view developed using the CV XE GIS software.

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

… view developed using the CV XE GIS software.

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

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

America’s Cities: Demographic-Economic Characteristics Annual Update

.. tools and data to interactively examine demographic-economic characteristics of America’s 29,321 cities/places .. understanding demographic-economic characteristics of cities and places is essential for business development, market analysis, planning, economic development, program management and general awareness of patterns and trends. This section provides access to data and tools to examine characteristics of all cities/places in the U.S. This annual update includes data for 29,321 cities/places based on ACS 2015 data.

Accessing the Data; Using Interactive Tables
Each of the four links below opens a new page providing access to U.S. by city/place interactive tables — by type of subject matter. Use tools and usage notes below table to select operations to perform queries, sort and select columns.
General Demographics
Social Characteristics
Economic Characteristics
Housing Characteristics

How the the Tables/Data Can be Used
The following table shows data derived from the Economic Characteristics table. The top 10 cities/places having the highest median household income ($MHI) are shown. The table also shows population, median family income ($MFI) and per capita income ($PCI). The $250,000 value is a cap; the actual value is $250,000 or higher. Use the interactive tables to create similar views for states of interest. Use the button below the table to select/view cities within a selected metro. Compare attributes of cities of interest to a peer group based on population size.

Visual Analysis of City/Place Population Patterns
Use GIS resources to visually examine city/place demographic-economic patterns. The following view shows patterns of population percent change by city in the Charlotte, NC-SC metro area.

… view developed using the CV XE GIS software.
… click map for larger view and details.

Related Data
Cities/Places Main Section
Citie Population Estimates & Trends, 2010-15

More About Using These Data
Using ACS 1-year and 5-year data

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

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

State and Regional Decision-Making Information

Organized on a state-by-state basis, use tools and geographic, demographic and economic data resources in these sections to facilitate planning and analysis. Updated frequently, these sections provide a unique means to access to multi-sourced data to develop insights into patterns, characteristics and trends on wide-ranging issues. Bookmark the related main Web page; keep up-to-date.

Using these Resources
Knowing “where we are” and “how things have changed” are key factors in knowing about the where, when and how of future change — and how that change might impact you. There are many sources of this knowledge. Often the required data do not knit together in an ideal manner. Key data are available for different types of geography, become available at different points in time and are often not the perfect subject matter. These sections provide access to relevant data and a means to consume the data more effectively than might otherwise be possible. Use these data, tools and resources in combination with other data to perform wide-ranging data analytics. See examples.

Select a State/Area

Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
D.C.
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming

Topics for each State — with drill-down to census block
Visual pattern analysis tools … using GIS resources
Digital Map Database
Situation & Outlook
Metropolitan Areas
Congressional Districts
Counties
Cities/Places
Census Tracts
ZIP Code Areas
K-12 Education, Schools & School Districts
Block Groups
Census Blocks

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.

Local Education Agencies by Type & State

.. the number and structure of school districts by state varies widely. Does this have an impact on educational outcomes and opportunities from state to state? In 1952, Texas had approximately 2,500 school districts (see in related section; today there are 1,027 school districts in Texas (see full table). School districts are now part of a more broadly structured set of Local Education Agencies (LEAs) which include state, regional and independent charter agencies offering elementary/secondary education. This section provides data on the count and type of LEAs by state for the 2014-15 school year.

Use the interactive table to view, rank, compare school districts/LEAs by state by type for the 2014-15 school year. These summary data are based on our processing of individual LEA data provided by individual state education agencies. Additional detail by LEA will be available later in 2016.

2014-15 LEAs by State
States labeled with total LEAs as of the 2014-15 school year. Click graphic for larger, more detailed view. Expand browser window for best quality view.

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

2014-15 Independent Charter Agencies by State
States labeled with Independent Charter Agency (ICA) LEAs as of the 2014-15 school year (3,056). States with no ICAs not labeled. Red markers show locations of all ICAs. Click graphic for larger, more detailed view. Expand browser window for best quality view.

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

Additional views – click to view graphic; expand browser window for best quality view:
Houston area zoom-in showing ICAs with name as label
Houston area zoom-in showing charter schools (green markers)
– black boundary shows Houston ISD school district
– yellow label: total enrollment; white label: total free & reduced lunch fee

Kansas City area zoom-in showing ICAs with name as label
– black boundary shows Kansas City, MO school district
Kansas City area zoom-in showing charter schools (green markers)
– black boundary shows Kansas City, MO school district
– yellow label: total enrollment; white label: total free & reduced lunch fee

Related School District Data
See about related demographic-economic datasets, interactive tables & GIS resources: General Demographics .. Social Characteristics .. Economic Characteristics .. Housing Characteristics

States Ranked by Total LEAs
The following graphic shows states ranked by total LEAs using the interactive table — the 10 states having the largest number of LEAs. Click graphic for larger view.

Join me in a Data Analytics Lab session to discuss more details about analyzing LEA characteristics and pattern and use of data analytics to develop further detail related to your interests.

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.

Crime Data Analytics

Goto ProximityOne .. examining crime incidence and socioeconomic patterns and analyzing small-area and location-based data.

.. what are the crime patterns in neighborhoods or areas of interest? It is challenging to get useful answers to this type of question. Crime incidence data by location/address are often difficult or not possible to obtain. Even where the location-based crime data are available, the data must be geocoded, e.g., assigned a census block code to each address. Separately demographic-economic must be organized to examine contextually with the crime data.

Integrating Crimes by Location & Patterns of Economic Prosperity
– View developed using CV XE GIS and related GIS project.

Crime Data Analytics. Use the Crime Incidence and Socioeconomic Patterns GIS project and associated datasets to explore relationships between crime and small area demographic-economic characteristics. Follow the steps described below to study patterns and relationships in Kansas City and/or use this framework to develop similar data analytics for other areas.

Framework for a case study. 409 of Missouri’s 4,506 block groups are within the jurisdiction of the Kansas City police department (KCPD) and had one or more crimes in 2014 (latest fully reported year). There were approximately 10,400 crimes recorded by the KCPD in 2014, in the city area spanning four counties. In this section tools and data are used to examine crime patterns in Kansas City, MO. Crime data are included as markers/locations in a GIS project. Crime data are also aggregated to the census block level and examined as summary data (aggregate crimes by census block). Crime data are related to American Community Survey (ACS) 2014 5-year demographic-economic data at the block group geographic level.

To perform these types of analyses, it is important to start with location-based crime data that have been attributed with type of offense (offense code). Ideally, each crime incidence data record includes minimally the offense code and address of the crime. Such location-based crime incidence data have been acquired from the KCPD. These data are used to develop a shapefile that can be included in a GIS project.

Patterns of Crime Incidence in Kansas City, MO
The following graphic shows patterns of crime incidence by census block for the “Plaza Area” within Kansas city. This view shows all types of crimes aggregated to the census block level. Crimes committed where a handgun was involved are shown as black/red circular markers. Click the graphic for a larger view that shows legend and more detail.
– View developed using CV XE GIS and related GIS project.

Related views (click link to view graphic in new window):
Use the GIS project to develop variations of these views. Optionally add your own data.
Lay of the land: Kansas City city (cross hatched) in context of metro
All crimes as markers in Kansas City in 2014

Patterns of Economic Prosperity & Crime Incidence
The following graphic shows patterns of economic prosperity (median household income $MHI) by block group for the same general area as above. This view illustrates how two types of crimes (burglary blue triangle markers and homicide (red/black square markers) can be examined in context. Click the graphic for a larger view that shows legend and more detail.

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

Related views (click link to view graphic in new window):
Use the GIS project to develop variations of these views.
View similar to above, without $MHI layer

Data used to analyze patterns of economic prosperity/$MHI are based on the American Community Survey (ACS) 2014 5-year estimates at the block group geographic level. The same scope of subject matter is available for higher level geography. The GIS project/datasets includes many types of demographic-economic subject matter that can be used to display/analyze different socioeconomic patterns.

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

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

Crime Incidence and Socioeconomic Patterns GIS Project/Datasets
1. Install the ProximityOne CV XE GIS
… omit this step if CV XE GIS software already installed.
… run the CV XE GIS installer
… take all defaults during installation
2. Download the CISP GIS Project fileset
… requires ProximityOne User Group ID (join now)
… unzip CISP GIS project files to local folder c:\crime
3. Open the kcmo_crimes_2014.gis project
… after completing the above steps, click File>Open>Dialog
… open the file named C:\crime\kcmo_crimes_2014.gis
4. Done .. the start-up view shows the crime patterns.

Weekly Data Analytics Lab Sessions
Join me in a Data Analytics Lab session to discuss more details about accessing location-based data and block group demographics and integrating those data into analytical applications.  Learn more about integrating these data with other geography, your data and use of data analytics that apply to your situation.

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

Staying Ahead of the Data in 2016

.. effective use of information in anticipation of data releases .. The Federal statistical system uses scheduled release dates for wide-ranging statistical data. Anticipation of the implications of the data by users builds ahead of the actual release date. This section reviews major statistical release dates to help stakeholders “stay ahead of the data” and be prepared to make better use of the data. The continuously updated Statistical Release Dates for 2016 table can be a useful reference throughout the year.

Anticipation of Data Releases & Implications of the Data
Each month, stakeholders around the world watch for news about the Jobs Report, the Employment Situation, data developed by the Bureau of Labor Statistics. The Employment Situation is one of many key economic measures used to assess the strength and direction of the U.S. economy.

For the November 2015 Jobs Report, released December 4, 2015, the New York Times December 2nd story reflected “In the United States, most of the focus will be on the November jobs report, to be released Friday. Expectations are high.”

Many, convinced that the November data would be good news, took action in advance of the actual data release. The New York Times December 4th story “The U.S. economy created 211,000 jobs in November … The numbers did not disappoint … U.S. stocks jumped more than 2 percent … Stocks rallied in a sign investors are taking their cue from economic performance …” The Jobs Report is but one of many with monthly implications for planning and decision-making.

Staying Ahead of the Data
Planning in advance of the statistical release dates can often be as important as taking action based on what the numbers actually say. Upon the actual data release, a CEO might ask, “what do these data mean for our company and what might be the impact on us?” Good opportunities might have passed by that time. And, in the face of less positive news, the opportunity to take action might have passed.

Statistical Release Dates for 2016
See the full 2016 calendar. The graphic below shows a partial view of the 2016 data release dates. Items include selected key Federal and other demographic-economic statistics and related geographic data. The list builds on the list of “Principal Federal Economic Indicators” prepared by OMB. That list was developed in part to prevent early access to information that may affect financial and commodity markets and preserve the distinction between the policy-neutral release of data by statistical agencies and their interpretation by policy officials.


– click graphic to view full table.

Each row in the table shows dates for data releases. The table will update throughout 2016 and knits together with the ProximityOne calendar. The “Staying Ahead of the Data” section in the Metropolitan Area Situation & Outlook Reportsreviews upcoming data releases and anticipates the possible effects on that metropolitan area.

Join me in a Data Analytics Lab session to discuss accessing, integrating and using these data with other data that relate to your situation.

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

Examining Neighborhood Diversity Patterns

Population race/ethnic diversity varies widely by neighborhood in the United States. This section reviews use of tools that you can use to examine patterns of neighborhood race/ethnic diversity for anywhere in the United States. There are many types of neighborhood diversity (economic, age, etc.); we examine just one here — diversity based on race/ethnicity. Using the tools and resources described in this section, you can also examine many other types of neighborhood diversity, or simply sub-county demographic-economic characteristics.

Dallas, TX Area Diversity Patterns by Neighborhood/Census Tract
Census tracts are colored based on value of the diversity index. See color patterns assigned based on diversity index values as shown in legend at left of the map. Blue tracts are most diverse; red tracts are least diverse. Tracts shown with black cross-hatched pattern are tracts with 50-percent or more Hispanic population.

Click graphic for larger view.

Click Link to View Neighborhood Diversity Patterns for Selected Metro Areas:
  • Atlanta, GA
  • Austin, TX
  • Charlotte, NC
  • Chicago, IL
  • Houston, TX
  • Los Angeles, TX
  • New York, NY
  • San Diego, CA
  • Washington, DC

Neighborhood Diversity Index
The diversity index measures the degree of racial and ethnic diversity of the population. The percentage of each race (White, Black, American Indian/Alaska Native, Asian, Native Hawaiian) and Hispanic origin/ethnicity are used to calculate the chance that any two people are from different groups. The index ranges from 0 (no diversity) to 100 (highest diversity). The diversity index is computed for each census tract using data from Census 2010 Summary File 1 Table P5.

Variation in Neighborhood Diversity
Census tract 06001437701 in Alameda County, CA has the highest diversity index (88). Of the approximate 73,000 census tracts, there are more than 800 tracts with a diversity index above 80 (highly diverse). There are more than 8,000 tracts with a diversity index below 10 (little diversity).

Visual Patterns of Neighborhood Diversity
We illustrate use of CV XE GIS with associated GIS project to visually examine patterns of diversity by census tract. We extracted the Census 2010 Table 5 data using the Demographic Economic Data Extraction API tool and then integrated those data into a U.S. by census tract shapefile. See more about the GIS project.

Relating Visual to Tabular Data
The graphic below shows diversity patterns by census tract in the Alexandria, VA area. The view of Alexandria shows census tracts with black boundary and labeled with the diversity index.

Illustrative Table P5 Mini-Profile
Census 2010 Summary File 1 Table P5 items for census tract 51-510-200900 are shown in the table below. Table P5 contains 17 data items for each tract, P0050001 through P0050017. As shown here, the total Census 2010 population of this tract was 4,693. The total non-Hispanic population was 4,534. The relatively low size of the Hispanic population suggests that this tract will have less diversity than others.

Using the GIS Resources
The Geographic Information System GIS project/files and software used to develop views shown in this section are available at no fee to members of the ProximityOne User Group. Zoom to you own areas of interest. Change labeling/colors/appearance. Add other geography. Select from other wide-ranging demographic-economic data. Join now; no fees to participate.

See more about analyzing neighborhood diversity patterns in this related Web section.