Tag Archives: CVXEGIS

Housing Price Index Updates & Trends

.. this past week we have updated Housing Price Index data and tools to examine patterns and trends for the U.S., states, metros and counties .. the Housing Price Index (HPI) is one of many measures useful to gain insights into the housing market. The HPI provides information on how housing value appreciation is changing for areas of interest. Use the interactive table to view, compare, sort metros/CBSAs based on annual HPI 2010-2017 and housing value appreciation during the period. These annual data, with a 2000 base index value of 100, provide insights into longer term patterns.  The HPI is alos updated quarterly for U.S./state/metro areas quarterly for analyses requiring more recent data.  These data are new as of February 2018.

Visual Analysis of Housing Price Appreciation
The following graphic shows housing value appreciation as of 2017 based on the HPI with 2000 base of 100 by county in the Charlotte, NC-SC metro area. See more about by HPI by county for the Charlotte metro.

– view developed using CV XE GIS and related GIS project.
– Click graphic for larger view and details.

See similar HPI 2017 patterns view for the Houston, TX metro.

Housing Price Appreciation 2010-2017 — Largest 10 Metros
This table, derived from the  interactive table, shows the largest 10 metros based on total population. the HPI 2010, HPI 2017, housing price appreciation 2010-2017 and total population are presented in the table. Click the CBSA code link to view HPI by county component for the metro and an extended series.

 Metro CBSA HPI2010 HPI2017 HPA1017 Pop2016
 New York   35620 159.53 172.76 8.29 20,153,634
 Los Angeles   31080 169.83 242.78 42.95 13,310,447
 Chicago   16980 117.48 124.58 6.04 9,512,999
 Dallas   19100 120.89 175.35 45.05 7,233,323
 Houston   26420 134.02 183.52 36.93 6,772,470
 Washington   47900 166.82 198.74 19.13 6,131,977
 PhiladelphiaA   37980 157.26 162.91 3.59 6,070,500
 Miami   33100 140.43 213.91 52.33 6,066,387
 Atlanta   12060 103.95 129.24 24.33 5,789,700
 Boston   14460 134.33 165.27 23.03 4,794,447

– Metro names abbreviated; use table to view full name and code.

Using the HPI Annual 2010-2017 Interactive Table
The following graphic illustrates use of the HPI Annual 2010-2017 interactive table. Click graphic for larger view. This view shows metros in the 250,000-300,000 population peer group. Set your own criteria using tools below the table. There are 23 metros in this group. The table has been sorted on housing price appreciation (HPA) from 2010-2017 (second column from right). It shows that the Merced, CA metro had the highest HPA — 82.13% di=uring this period.

Use the interactive table and examine areas of interest.

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

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

 

 

Examining Appalachia City Characteristics & Trends

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Using CVXEGIS dBase Script Tool

.. shapefiles are the most widely used type of vector-based geodata file type used Geographic Information Systems GIS. The shapefile structure, comprised of a .shp (geometry), .dbf (dBase-subject matter), ,shx (index file associating shp and dbf records) and .prj (projection), is in the public domain, well documented and used by many mapping GIS tools.

Persistent Need to Process & Restructure dBase Files
Many shapefiles, such as the wide ranging political, statistical and topographic Census Bureau TIGER/Line shapefiles, become available with no subject matter content or limited scope content. There is a persistent need to process the dBase files (.dbf) associated with shapefiles … adding data, computing data, linking data, updating data, etc.

dBase, or dBASE or dbf, files have wide ranging appeal and use well beyond mapping and GIS applications. The simple and transportable structure makes them ideal for any type of textual or statistical data that is of conventional text or numeric form associated with data records with associated ID fields (social security number, member number, customer number, geocode, and many others) — where the need to support queries or develop relational data files structures is great. Compared to Excel, dBase files provide a smaller footprint, can be processed faster with some dBase application software and can support a larger number of records.

This section briefly outlines use of the CVXEGIS Script feature. The Script feature includes the ability to develop programming-like code to process dBase files.

There is no fee for the basic version of the Script feature. It can be used with any dBase file. The learning curve is almost nil. Install CVXEGIS and start using the tool.

Script Tool User Interface
Create, manage code interactively; run the script as a batch file.
Top section shows code; lower section shows selected output.

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.