Population Living Alone & Age 65 Years and Over

.. how many people are living alone in your community, neighborhood? How does this population impact the community? What are their special needs? How does this population vary by area and population group? There were 37.9 million one-person households, 29% of all U.S. households in 2022. In 1960, single-person households represented only 13% of all households. These estimates are based on the 2022 Current Population Survey (CPS). Moving forward, the number of one-person households, people living alone, will increase at the rate of one million or more per year. People in households exclude people living in group quarters. This post examines patterns of people living alone with focus on people living alone age 65 year and over and distribution by small area geography.

While the CPS data provide a current snapshot of the number of people living alone, we have to use data from the American Community Survey to obtain data for smaller area geography like counties and census tracts.

Population Living Alone by Census Tract –Visual Data Analytics
The four graphics below show patterns of the population living alone by census tract. These views have been developed using the Visual Data Analytics (VDA GIS) tools with integrated demographics. Develop variations on these views using the VDA Web GIS using only a web browser.

Patterns of Population Living Alone by Tract

.. click graphic for larger view.

Patterns of Population 65 and Over Living Alone by Tract

.. click graphic for larger view.

Patterns of Population Living Alone by Tract — Houston Metro Area

Patterns of Population 65 and Over Living Alone by Tract — Houston Metro Area

Examine the Data in More Detail
As noted in this related New York Times story, nearly 26 million Americans 50 or older now live alone, up from 15 million in 2000. Older people have always been more likely than others to live by themselves makes up a bigger share of the population than at any time in the nation’s history. The trend has also been driven by deep changes in attitudes surrounding gender and marriage. People 50-plus today are more likely than earlier generations to be divorced, separated or never married. Similar ACS data as used to develop the graphics shown above are available by race/origin. These data are based on the ACS 2020 data; the same scope of data will be available from ACS 2021 to be released in December 2022.

About VDA GIS
VDA Web GIS is a decision-making information resource designed to help stakeholders create and apply insight. Use VDA Web GIS with only a Web browser; nothing to install; GIS experience not required. VDA Web GIS has been developed and is maintained by Warren Glimpse, ProximityOne (Alexandria, VA) and Takashi Hamilton, Tsukasa Consulting (Osaka, Japan).

About the Author
Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and 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. Join Warren on LinkedIn.

Housing Price Index by ZIP Code – How Housing Markets are Trending

.. housing prices can impact residential investment and affect economic growth, business opportunities and the housing market. The Housing Price Index (HPI) is one measure of how housing prices are changing. The HPI by ZIP code, as reviewed here, is an index based on the year 2000=100. Changing trends in the HPI can used used the determine the relative costs of housing and change in housing valuation. Hosing prices, and the HPI, are only one part of determining how housing markets are trending. Other measures important to examine include building permits and new construction.

Examining Housing Price Trends
Use the VDA Web GIS tool to examine the Housing Price Index for ZIP Codes of interest. Create maps and tabular profiles such as the one shown below.

Video of Steps to Explore HPI by ZIP Code
Click graphic to view video showing how to use VDA Web GIS to access a ZIP Code profile.

About VDA Web GIS
VDA Web GIS is a decision-making information resource designed to help stakeholders create and apply insight. VDA Web GIS has been developed and is maintained by Warren Glimpse, ProximityOne (Alexandria, VA) and Takashi Hamilton, Tsukasa Consulting (Osaka, Japan).

About the Housing Price Index
The Housing Price Index used here is developed by the Federal Housing Fiance Agency (FHFA). The FHFA House Price Index is the nation’s only public, freely available house price indexes that measure changes in single-family home values based on data from all states that extend back to the mid-1970s.

About the Author
Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and 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. Join Warren on LinkedIn.

New Authorized Monthly Residential Construction by City

.. access/analyze monthly building permits data for any/all of 7,700 cities in a few minutes via a web browser. Building permits data, a leading economic indicator, are one of the few current indicators available at the city level to examine characteristics and trends. These data can provide insights into the type and value of housing that is being added. Use the VDA Web GIS to examine how the housing situation is changing for cities of interest.

The VDA Web GIS MetroDynamics city layer/dataset is updated with the most recent 6 months of the number of housing units by type and value. The current data provide monthly aggregated data for January 2022 through June 2022. The layer/dataset includes many other attributes (see details). Of the ~19,000 U.S. cities, ~7,700 issue monthly building permits and accessible via this resource.

Examining City Housing Characteristics & Trends
An example: cities in the Phoenix, AZ area labeled with the total building permits.

.. table under map view shows cities with largest number of building permits.
.. see steps to develop the above map and table.

Illustrative Profile for Surprise, AZ
.. selected items from MetroDynamics City layer/dataset
.. integrated subject matter from several sources
.. building permits most current

About VDA Web GIS
VDA Web GIS is a decision-making information resource designed to help stakeholders create and apply insight. VDA Web GIS has been developed and is maintained by Warren Glimpse, ProximityOne (Alexandria, VA) and Takashi Hamilton, Tsukasa Consulting (Osaka, Japan).

About Building Permits Data
Building permits data are collected monthly by the Census Bureau from permit issuing agencies. Monthly data are reported for access within one month of the reporting date. Data are collected on the number of new housing units authorized by type of units in building by value.

About the Author
Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and 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. Join Warren on LinkedIn.

Examine Neighborhood Demographics for any City

.. examine neighborhood demographics for any city (or county, school district ..) using the no fee, no registration new beta version of the Visual Data Analytics (VDA2) Web GIS. Nothing to install, access with any Web browser. Use this unique and powerful resource to make custom maps similar to the one shown below.

Patterns of Economic Prosperity by Neighborhood in Tampa, FL Area
Examine patterns of economic prosperity by neighborhood in context of a selected county, city or other geography. The following view shows patterns of median household income by census tract in Tampa, FL area. The bold black border shows the city boundary for Tampa; the thematic pattern shows colors associated with intervals of median household income ($MHI). The $MHI layer is set with a see through transparency enabling a view of the underlying topology. Create a view similar to this for any of the 19,500 cities in the U.S. See detailed steps to develop this view in the notes below the graphic.

Map Your Own Map View
Follow these stpe to create your own neighborhood by city map view.  Use other features of VDA2 to access demographic-economic data in a tabular or visual form.

More About VDA2 Web GIS
New in VDA2, not available in VDA1, are the table/query operations. View/analyze data for any layer in a spreadsheet/grid form.  Sort and perform queries on subject matter of interest. Click a button in the data grid to zoom to that geographic area in the map window.  The following graphic shows the VDA2 start-up view after clicking the Query/Table On/Off button. This button (shown below map window at right by pointer) toggles the table view on/off.

.. click graphic for larger view.

Learn more — Join me in the Situation & Outlook Web Sessions
Join me in a Situation & Outlook Web Session where we discuss topics relating to measuring and interpreting the where, what, when, how and how much demographic-economic change is occurring and it’s impact.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for national scope statistical programs and 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 – Examining Median Housing Value – 2020 Update

.. 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.

.. in this era of uncertainly, we ponder the risk and opportunity associated with changing housing value.  Median housing value by ZIP Code area is one metric of great interest to examine levels and change.  While only one measure useful to examine housing characteristics, it is part of a broader set of demographic-economic data that enable analysis of the housing infrastructure and change in a more wholistic manner. How is housing value trending at the neighborhood level in 2020 and beyond? See more about the Situation & Outlook.

.. 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.

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.

Relating ZIP Codes to City/Places

.. relating ZIP codes to cities .. 214 ZIP code areas intersect with New York city — what are these ZIP codes, their population and how many are completely within the city? What part of a ZIP code area of interest intersects with what city? Conversely, what ZIP code areas intersect with a city of interest? This section provides data and tools that can be used to answer these types of questions and gain insights into geospatial relationships. See more detailed information in the related full Web section.

The 2010 ZIP Code Tabulation Area (ZCTA) to City/Place relationship data provide a means to equivalence ZCTAs with Census 2010 cities/places. ZCTAs are geographic areas defined as sets of Census 2010 census blocks closely resembling USPS ZIP codes (lines, not areas). ZCTA boundaries are fixed for the intercensal period 2010 through 2020. Census 2010 vintage city/place areas are likewise defined as sets of Census 2010 census blocks. The ZCTA-City/place relationship data are developed through the use of the intersecting census block geography and associated Census 2010 Summary File 1 demographic data.

ZCTA-Place Relationships
The following graphic shows relationships between two selected ZCTAs (red boundaries) and related cities/places (blue fill pattern) in the Pima/Cochise County, AZ area. Relationships between these geographies are reviewed in examples shown below.

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

Using the ZCTA-Place Relationship Data
Two examples illustrating how to use the ZCTA-place relationship data are provided below. The examples are interconnected to the GIS project used to develop the map views, interactive table and data file described in this section. Example 1 describes how to use the data for a ZIP code area entirely located within one city/place. Example 2 describes how to use the data for a ZIP code area located in more than one city/place and area not located in any city/place.

ZCTA to Place Relationships: Example 1
In this example, ZCTA 85711, highlighted in red in the graphic shown below, falls wholly within place 77000, outlined in bold black below. As a result, there is only one corresponding record for ZCTA 85711 in the relationship file. The 2010 Census population for this relationship record is 41,251 (POPPT) which is equal to the 2010 Census population for ZCTA 85711 (ZPOP). See more details about this example.

ZCTA to Place Relationships: Example 2
In this example, ZCTA 85630, highlighted below in red in the graphic shown below, contains two places: all of place 62280 and part of place 05770, both are outlined in black below. As a result, there are two corresponding relationship records in the relationship file. For the first relationship record, the total 2010 Census population for ZCTA is 2,819 (ZPOP). See more details about this example.

Using the Interactive Table
Use the full interactive table to examine U.S. national scope ZCTA-city/place relationships. The following graphic illustrates how ZIP code can be displayed/examined for one city — Tucson, AZ. Each row summarizes characteristics of a ZIP code in Tucson. The last row in the graphic shows characteristics of ZIP code 85711 — the same ZIP code reviewed in Example 1 above.

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.

Making & Using Custom 115th Congressional District Maps

.. using GIS resources to create custom 115th Congressional District maps .. use the methods, data and tools described in this section to develop custom congressional district maps. View patterns of economic prosperity by neighborhood for one or all congressional districts. Flexibly associate a congressional district boundary with related geography and subject matter.  See related Web section for more details.

Join the Congressional District-State Legislative District (CDSLD) Group .. be a part of the community. .. click here to join .. there is no cost.

Coming up … mapping/analyzing school district finances in context of the 115th Congressional Districts (June 2017).

See the related section on Making/Using 113th Congressional District Maps.
.. view different congressional district vintages in same map.

115th Congressional Districts by Incumbent Party Affiliation
This view and related GIS project/data update when changes are made to the 115th Congressional Districts incumbents (last updated 5/10/17). Party affiliation shown in this view is also available in the related interactive table. Click graphic for larger view. Expand browser window for best quality view.

– View developed using CV XE GIS and related GIS project.
– see below in this section about using this GIS project.

Use the Geographic Information System (GIS) tools and data to view/show congressional district in context with roads, landmarks and other geography. Flexibly add labels. Create pattern views. Add your own data.

Patterns of Economic Prosperity by 115th Congressional District
The following graphic shows patterns of ACS 2015 median household income (MHI) by 115th Congressional District. Click graphic for larger view. Expand browser window for best quality view.

– View developed using CV XE GIS and related GIS project.
– use the GIS project and tools see below to create different views.

Examine Characteristics of any Congressional District
The following graphic shows patterns of ACS 2015 median household income (MHI) by census tract in context of 115th Congressional Districts in a region of North Carolina. CD 3712 (Charlotte area) is shown with bold boundary. It is easy to see which areas/tracts have different levels of economic prosperity.

– View developed using CV XE GIS and related GIS project.
– use the GIS project and tools see below to create different views; add other layers.

Creating congressional district maps is often specific to a particular analysis, zoom-view, labeling, combination of different geographies or other considerations. While there are no estimates of unemployment by congressional district, using GIS tools it is possible to view/geospatially analyze patterns of unemployment within congressional district by county, census tract, block group and other geography.

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 & Using Location Shapefiles

.. GIS tools and methods to develop and update location shapefiles .. location shapefiles are essential to most GIS applications. Location shapefiles, or point shapefiles, enable viewing/analyzing locations on a map and attributes of these locations such store or customer ID, street address, city, date updated, value, ZIP code and wide-ranging attributes about the location. This section reviews tools and methods to develop and use location shapefiles. See more detail about topics covered in this section in the related Web page.

Viewing/Analyzing Store Locations in the Dallas, TX Area
The following graphic illustrates how store locations can be shown in context of other geography and associated demographic-economic attributes. This view shows store locations (red markers) in context of Dallas city (blue cross-hatch pattern) and broader metro area. Markers shown in this view are based on a location shapefile created using steps described below. The identify tool is used to click on a location and show attributes in a mini-profile.

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

View the locations contextually with thematic patterns by tract or other geography. Combine views of store, customer, agent, competitor and other location shapefiles.
The following view shows patterns of median household income by census tract.

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

Development of location shapefiles often starts with a list of addresses. Locations are not always address-oriented; they might be geographically dispersed measurement or transaction locations — having no address assigned. In applications reviewed here, locations are organized as rows in a CSV file. Each CSV file contains like-structured attributes for each location. The example used in this section uses store locations located in the Dallas, TX area.

There are two basic methods used to create location shapefiles: 1) geocoding address-data contained in the source data file or 2) using the latitude-longitude of the location included in the source data file record. The focus here is on option 2 — using the latitude-longitude of the location already present in the source data file.

Creating a Location Shapefile
The process of creating a location shapefile uses the CV XE GIS Manage Location Shapefile feature. With CV running, the process is started with File>Tools>ManageLocationShapefile. The following form appears.

.. ManageLocationShapefile feature/operation in ProximityOne CV XE GIS.

CV XE GIS provides other ways to create location shapefiles:
• Tools>AddShapes>Points — click points on the map window canvas.
• Tools>FindAddress — creates a single point shapefile based on specified address.
• Tools>FindAddress (Batch) — creates a point shapefile based on specified file of address records.
See details in User Guide.

Steps to Create a Location Shapefile
The process of creating the shapefile “C:\cvxe\1\locations1pts.shp” can be viewed by clicking the Run button on the form (with CV running). Two input CSV structured files are required:
• data definition file
• source data file

There are two sets of illustration location input files included with the CV installer:
• locations1_dd.csv and locations1.csv (7 locations in Johnson County, KS)
• locations2_dd.csv and locations2.csv (252 locations in Dallas and Houston)
These files are located in the \1 (typically c:\cvxe\1) folder. The marker/location shapefile used in the map shown above was created using the lcoations2 input files.

Data Definition File
The Data Definition (DD) file is an ASCII/text file structured as a CSV file. It may created with any text editor. The DD file is specific to the source data file. But in the case of recurring source data files for different periods the same DD file might apply to many source data files. There are several rules and guidelines for development of the DD file:
• there is one line/record for each field in the source data file.
• each line/record must be structured in an exact form:
.. each line/record is comprised of exactly 4 elements separated by a comma:
.. 1 field name for subject matter item
– must consist of 1 to 10 characters and include no blanks or special characters
.. 2 field type: C for character, N for numeric
.. 3 field length: an integer specifying the maximum with of the field
.. 4 maximum number of decimals for field (value is 0 for character fields)
The DD File must include three final fields:
LATITUDE,n,12,6
LONGITUDE,n,12,6
GEOID,c,15,0
The structure of these three DD file records must be as shown above. The source data file, described below, must have the LATITUDE and LONGITUDE fields populated with accurate values. The GEOID field may populated with either an accurate value of placeholder value like 0.

Example. Data for each store for the default DD file name “C:\cvxe\1\locations1_dd.csv” include the following fields/attributes:
  NAME,C,45,0
STORE,c,15,0
ADDRESS,c,60,0
CITY,c,40,0
LATITUDE,n,12,6
LONGITUDE,n,12,6
GEOID,c,15,0

Optionally create a DD File using the Create DD File button on the form. Clicking this button will create a DD File containing attributes of the dBase file specified in the associated edit box. The DD File name is created from the dBase file name. If the dBase file name is “c:\cvxe\1\locations1pts.dbf”, the DD File will be named “c:\cvxe\1\locations1pts_dd.csv”.

About the GEOID
The GEOID is a 15 character code which defines the Census 2010 census block containing each location. The GEOID is generally assigned by the ManageLocationShapefile operation and is one of the important and distinctive features of this tool. The GEOID is used to uniquely determine, with the GIS application, any of the following: state, county, census tract, block group, or census block.

The GEOID, as used in this section, is the 15 character Census 2010 geocode for the census block. The GEOID value 481130002011012 (see in location profile in map at top of section) is structured as:
state FIPS code: 48 (2 chars)
county FIPS code: 113 (3 chars)
census tract code 000201 (6 chars)
census block code: 1012 (4 chars) (block group code: 1 — first of 4 characters)

About the Source Data File
The Source Data File is an ASCII/text file structured as a CSV file. It is typically developed by exporting/saving an Excel or dBase file in CSV structure. There are several rules and guidelines for development of the source data file:
• fields must be structured and arranged as defined in the DD File.
• character fields must not contain embedded commas.
• final items in record sequence must be:
.. LATITUDE – must have accurate decimal degree value; 6 digit precision suggested.
.. LONGITUDE- must have accurate decimal degree value; 6 digit precision suggested.
.. GEOID – this may be 0, not assigned or the accurately assigned GEOID value.
– optionally create/rewrite the GEOID used in the new shapefile.

Updates; Combining Vintages of Location Attributes
Location based data might update frequently, even daily. The recommended method to add, update and extend the scope of location-based data is to create new address shapefiles corresponding to different vintages or dates covered. The structure of the files must be the same so that they files can be used together or separately. Suppose there is one set of data covering year to date and a second set of data covering the following month. The ManagePointShapefile operation would be run once for each time period. Two shapefiles would be created. These shapefiles may be added to a GIS project and used separately or in combination to view/analyze patterns.

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.

ZIP Codes with Highest & Lowest Economic Prosperity

.. the latest data for ZIP Code Areas show that eleven had a median household income of $250,000 or more during the period 2011-15. More than 20 ZIP code areas had a median housing value of $2,000,000 or more. Contrast these ZIP code areas with higher economic prosperity with the more than 150 ZIP codes that had a median housing value of less than $30,000.  Use the interactive table in this related Web section to see which ZIPs meet these and other criteria.

ZIP Codes with MHI $100,000 or More; Dallas, TX Metro
Analyzing economic prosperity patterns using combined types of small area geography … the following graphic shows ZIP code areas a red markers with the median household income or $100,000 or more in context of median household income by census tract thematic pattern. Click graphic for larger view with more detail. Expand browser window for best quality view. Use CV XE GIS software and associated GIS project to develop variations of this view for your areas of interest. .

– view developed with CV XE GIS software.

This section reviews measures of economic prosperity for all ZIP code areas. These data were released in December 2016. This section updates with new data December 2017. See the list of all ZIP ccdes showing population, housing and economic characteristics in the interactive table shown below. Use the interactive table to view, rank, compare and query ZIP code attributes.

Examining demographic-economic characteristics by ZIP code is important for several reasons. We are familiar with our own ZIP codes as a geographic location. We tend to be interested in our area compared to other areas. ZIP codes provide an easy way to do that. Also, many secondary data resources are tabulated by ZIP code area; some important data are only available by ZIP code. See more about ZIP Code areas.

Resources & Methods to Examine Small Area Demographics
• See related ZIP Code Demographic-Economic Interactive Tables
  .. extended subject matter
• See related Census Tract Code Demographic-Economic Interactive Tables
• Examine ZIP Code Urban/Rural Characteristics
• Examine ZIP Code Business Establishment patterns
• Examine ZIP Code Housing Price Index patterns
• Join us in the weekly Data Analytics Lab Sessions
  .. reviewing applications using these and related data.

ZIP Code Areas with $MHI $100,000 or More
The following graphic shows ZIP code areas as red markers having median household income or $100,000 or more. Click graphic for larger view with more detail. Expand browser window for best quality view. Use CV XE GIS software and associated GIS project to develop variations of this view; integrate other data; select alternative ACS 2015 subject matter.

– view developed with CV XE GIS software. Click graphic for larger view.

ZIP Code Areas with $MHV Less than $30,000
The following graphic shows ZIP code areas as orange markers having median housing value of less than $30,000. Click graphic for larger view with more detail. Expand browser window for best quality view. Use CV XE GIS software and associated GIS project to develop variations of this view; integrate other data; select alternative ACS 2015 subject matter.

– view developed with CV XE GIS software. Click graphic for larger view.

ZIP Code Areas: Population & Economic Prosperity
  — Interactive Table –
Use the interactive table to view, rank, compare, query ZIP codes based on a selection of demographic-economic measures. The following graphic illustrates how the table can be used to examine patterns of the three digit ZIP code area (San Diego) by 5-digit ZIP code. Table operations are used to select ZIP codes in the 921 3-digit area (containing 39 5-digit ZIP codes). These 39 ZIP code are then ranked in descending order on median household income. See results in the table shown below. ZIP code 92145 has the highest $MHI in this group with $228.036.

– click graphic for larger view.

Try it yourself. Use the table to examine a set of ZIP codes 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.