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School District Housing Data Analytics
  -- ACS 2017 Housing Units, Age, Tenure, Occupancy, Rates, Value, Rent, more
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January 2019. Based on ACS 2017 estimates, the U.S. median housing value was $193,500 while school districts ranged from $18,700 (Shannon County School District, SD -- among districts having 1,000 or more population) to $2,000,000+ (Palo Alto Unified, CA -- 15 districts were at or above this top-coded value). See item/column H089 in the interactive table below to view, rank, compare, analyze states based on this measure in context of related housing characteristics. These data uniquely provide insights into many of the most important housing characteristics for all school districts in the U.S. See about how to view/rank/compare districts below in this section. Create comparative analysis profiles for districts of interest.

Approximately 600 subject matter items from the American Community Survey ACS 2017 database (released December 2018) are included in these sections:
  • General Demographics
  • Social Characteristics
  • Economic Characteristics
  • Housing Characteristics -- this section

Visual Analysis of Patterns of Median Housing Value by School District
The following map shows patterns of median housing value ($MHV) by school district in the San Antonio, TX MSA (bold brown boundary) area based on the ACS 2017 5-year estimates. Create a similar map for any area in the U.S. and/or variations of this view using the associated GIS project with the CV XE GIS software. Add your own data.

- larger view showing San Antonio city (cross-hatch pattern)
- view developed with CV XE GIS software .. click graphic for larger view.

Additional views: (opens in new page)
  • Wichita, KS MSA area

Analytzing the School & School District Community
ProximityOne works with schools, school districts and K-12 education stakeholders to develop, integrate and analyze demographic-economic data for planning, evaluation and policy analysis. Use our custom estimates and projections to better understand trends, what might change when and where -- and how it might impact you.

Using the Interactive Table
Use the interactive table below to view, query, rank, compare housing characteristics of the population, households and families for these areas. The scroll box shown below lists each of the subject matter items available for each area via the ranking table. In the subject matter items scroll box, subject matter items are organized into to mini-tables with related items. The number at the left of the subject matter item is also used as the short name for the subject matter item in the column header in the ranking table.

Housing Characteristics Items
.. a few item names and numbers changed from previous year data/table.
  H001     Total housing units
  H002 Occupied housing units
  H003 Vacant housing units
  H004 Homeowner vacancy rate
  H005 Rental vacancy rate
  H006     Total housing units
  H007 1-unit, detached
  H008 1-unit, attached
  H009 2 units
  H010 3 or 4 units
  H011 5 to 9 units
  H012 10 to 19 units
  H013 20 or more units
  H014 Mobile home
  H015 Boat, RV, van, etc.
  H016     Total housing units
  H017 Built 2014 or later
  H018 Built 2010 or 2013
  H019 Built 2000 to 2009
  H020 Built 1990 to 1999
  H021 Built 1980 to 1989
  H022 Built 1970 to 1979
  H023 Built 1960 to 1969
  H024 Built 1950 to 1959
  H025 Built 1940 to 1949
  H026 Built 1939 or earlier
  H027     Total housing units
  H028 1 room
  H029 2 rooms
  H030 3 rooms
  H031 4 rooms
  H032 5 rooms
  H033 6 rooms
  H034 7 rooms
  H035 8 rooms
  H036 9 rooms or more
  H037 Median rooms
  H038     Total housing units
  H039 No bedroom
  H040 1 bedroom
  H041 2 bedrooms
  H042 3 bedrooms
  H043 4 bedrooms
  H044 5 or more bedrooms
  H045     Occupied housing units
  H046 Owner-occupied
  H047 Renter-occupied
  H048 Average household size of owner-occupied unit
  H049 Average household size of renter-occupied unit
  H050     Occupied housing units
  H051 Moved in 2015 or later
  H052 Moved in 2010 to 2014
  H053 Moved in 2000 to 2009
  H054 Moved in 1990 to 1999
  H055 Moved in 1980 to 1989
  H056 Moved in 1979 or earlier
  H057     Occupied housing units
  H058 No vehicles available
  H059 1 vehicle available
  H060 2 vehicles available
  H061 3 or more vehicles available
  H062     Occupied housing units
  H063 Utility gas
  H064 Bottled, tank, or LP gas
  H065 Electricity
  H066 Fuel oil, kerosene, etc.
  H067 Coal or coke
  H068 Wood
  H069 Solar energy
  H070 Other fuel
  H071 No fuel used
  H072     Occupied housing units
  H073 Lacking complete plumbing facilities
  H074 Lacking complete kitchen facilities
  H075 No telephone service available
  H076     Occupied housing units
  H077 1.00 or less
  H078 1.01 to 1.50
  H079 1.51 or more
  H080     Owner-occupied units
  H081 Less than $50,000
  H082 $50,000 to $99,999
  H083 $100,000 to $149,999
  H084 $150,000 to $199,999
  H085 $200,000 to $299,999
  H086 $300,000 to $499,999
  H087 $500,000 to $999,999
  H088 $1,000,000 or more
  H089 Median (dollars)
  H090     Owner-occupied units
  H091 Housing units with a mortgage
  H092 Housing units without a mortgage
  H093     Housing units with a mortgage
  H094 Less than $500
  H095 $500 to $999
  H096 $1,000 to $1,499
  H097 $1,500 to $1,999
  H098 $2,000 to $2,499
  H099 $2,500 to $2,999
  H100 $3,000 or more
  H101 Median (dollars)
  H102     Housing units without a mortgage
  H103 Less than $250
  H104 $250 to $399
  H105 $400 to $599
  H106 $600 to $799
  H107 $800 to $999
  H108 $1,000 or more
  H109 Median (dollars)
  H110     Housing units with a mortgage (excluding units where SMOCAPI cannot be computed)
  H111 Less than 20.0 percent
  H112 20.0 to 24.9 percent
  H113 25.0 to 29.9 percent
  H114 30.0 to 34.9 percent
  H115 35.0 percent or more
  H116 Not computed
  H117     Housing unit without a mortgage (excluding units where SMOCAPI cannot be computed)
  H118 Less than 10.0 percent
  H119 10.0 to 14.9 percent
  H120 15.0 to 19.9 percent
  H121 20.0 to 24.9 percent
  H122 25.0 to 29.9 percent
  H123 30.0 to 34.9 percent
  H124 35.0 percent or more
  H125 Not computed
  H126     Occupied units paying rent
  H127 Less than $500
  H128 $500 to $999
  H129 $1,000 to $1,499
  H130 $1,500 to $1,999
  H131 $2,000 to $2,499
  H132 $2,500 to $2,999
  H133 $3,000 or more
  H134 Median (dollars)
  H135 No rent paid
  H136     Occupied units paying rent (excluding units where GRAPI cannot be computed)
  H137 Less than 15.0 percent
  H138 15.0 to 19.9 percent
  H139 20.0 to 24.9 percent
  H140 25.0 to 29.9 percent
  H141 30.0 to 34.9 percent
  H142 35.0 percent or more
  H143 Not computed

School District ACS2017 Housing Characteristics .. interactive table .. goto top
  Districts initially sorted on state by name; click any column header cell to sort on that column/attribute.
  Example: click H002 header cell twice to sort on
    "Total Occupied Housing Units (Households)" in descending order.
  Click ShowAll button between Find/Queries. Use mouseover on column header to view column description.
  See usage notes below table. See related interactive tables.

Usage Notes
  • If table not showing any rows; click ShowAll button below table.
  • Use vertical and horizontal scroll bars to navigate up/down or left/right.
  • Adjust column widths using column divider between header cells.
  • Find CBSA> button -- use to select CBSA/Metro based on exact CBSA 5 character code in column 3.
    .. CBSA/metro codes may be found in the table at
    .. after entering the code click the Find CBSA> button ... table refreshes with all districts in this CBSA.
    .. example .. clicking 1) the ShowAll button, then 2) the Find CBSA button with default 41700 value.
      shows the 39 districts of this size in the San Antonio metro
      that can now be further examined as this specific set of districts.
  • Find Name> button -- use to select district based on exact spelling of partial name in column 1.
    .. Key in exact up/low case spelling of partial name of district in the edit box to right of Find Name> button.
    .. click the Find Name> button ... table refreshes with all districts with matched spelling in column 1.
  • Selected columns -- click the "Units.Occ.Vacant.%MdValue.$MdRent" button to show only these columns;
    .. click "All columns" button to restore view to all columns.

  • All items are estimates for the 5 year period 2013-2017 (centric to 2015).
  • Click ShowAll button between specific area queries.
  • Cells with negative value could not be estimated (for this geography and this time frame).

Use school district code/area name based on address.

Create a School District Profile .. goto top
The interactive table above shows attributes for each school district as a row. To transpose the items into a downloadable profile, follow these steps.
  • Open DP4 XLS -- Housing Characteristics -- requires Excel
  • Select a district from interactive table above.
    .. click a row; it turns blue.
    .. right click and click copy.
  • Paste (CTRL-v) in column D1 in spreadhseet.
  • Right click D1 and Copy (all cells pasted in above step)
  • Right click D4 and Paste Special

The D column is now populated with with items in the districts selected from interactive table.
  • Optionally save to local XLS file on your computer.
  • Optionally select another district and repeat paste steps into column E1.

Completed example:
  • Housing Characteristics - San Antonio ISD, TX

Optionally create four types of profiles for any district.
  • General Demographics
  • Social Charactersitics
  • Economic Characteristics
  • Housing Characteristics

About these Demographic-Economic Data
Data used in this section are estimates developed from the American Community Survey (ACS2017). These data differ from administratively reported data (enrollment, etc.).

Data are for the total resident population in the district. Data are not shown separately for charter schools as charter schools have no defined boundaries. If a charter school located in district X has students from district Y, attributes of those students and households are shown in data for district Y.

The importance of understanding the demographic-economic make-up and trends can hardly be overstated. Community and educational challenges and opportunities are shaped by demographic-economic dynamics. Only by knowing "where we are" can we develop the most effective plans for improvement.

The American Community Survey provides "richer" demographic-economic characteristics for national scope wide-ranging geographic areas. While Census 2010 provides data similar to those items in the General Demographics section, only ACS sourced data provide details on topics such as income and poverty, labor force and employment, housing value and costs, educational participation and attainment, language spoken at home, among many related items. The approximate 600 items accessible via the dataset are supplemented by a wide range of additional subject matter. These data are updated annually in December of each year for each/all political/statistical areas, including census tracts, ZIP code areas and block groups..

FAQS & Related Notes .. goto top

How to view/rank/compare largest districts based on total population
  • Use the General Demographics section/table.
  • Click the D001 (total population) table header cell.
    .. the table refreshes sorted on D001 in one direction; click again to sort in other direction.

How to view/rank/compare enrollment
  • Use the Social Characteristics section/table.
  • Click the button School Enrollment below the table.
    .. the table refreshes with the school enrollment columns.

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Support Using these Resources
Learn more about accessing and using demographic-economic data and related analytical tools. Join us in a Data Analytics Lab session. There is no fee for these one-hour Web sessions. Each informal session is focused on a specific topic. The open structure also provides for Q&A and discussion of application issues of interest to participants.

Additional Information
ProximityOne develops geodemographic-economic data and analytical tools and helps organizations knit together and use diverse data in a decision-making and analytical framework. We develop custom demographic/economic estimates and projections, develop geographic and geocoded address files, and assist with impact and geospatial analyses. Wide-ranging organizations use our tools (software, data, methodologies) to analyze their own data integrated with other data. Follow ProximityOne on Twitter at Contact us (888-364-7656) with questions about data covered in this section or to discuss custom estimates, projections or analyses for your areas of interest.

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