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School District Data Analytics -- 2015 Housing Characteristics; Largest 1,016 School Districts
September 2016. The importance of understanding the demographic-economic make-up and trends for school districts 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. This section is focused on tools, resources and methods that you can use to access, integrate and analyze school district housing characteristics data. • Go to interactive table below in this section. The U.S. national scope ACS 2015 (released September 2016) School District Demographic-Economic Dataset contains approximately 600 subject matter items tabulated for each of the largest 1,016 school districts organized into four subject matter groups: • General Demographics • Social Characteristics • Economic Characteristics • Housing Characteristics -- this section (see similar ACS 2014 data) The largest school districts are those that have total population of 65,000 or more. See related tables for this same set of districts and data source: • Public & Private Enrollment by Grade Range These data provide information and insights not available by examining data on students and schools alone -- or any other data. See more about the importance of these data. Data reviewed in this section are based on the American Community Survey (ACS) 2015 1-year estimates for school districts defined as of the 2013-14 school year. See notes on importance of these data. See similar ranking tables for: Census Tracts | ZIP Codes | State, Metro & County. Largest School Districts 2015 This view shows school districts (red markers) having ACS 2015 population 65,000 or more. Click graphic for larger view. Expand browser window for best quality view. Larger view shows metros (MSAs) with semi-transparent fill pattern. See district locations in context of metros. Use related GIS project to examine patterns and gain insights into school district patterns using geospatial data analytics tools. View school districts as areas in context of other geography and your data. Zoom-in for regional views; label geography with names or attributes.  - View developed using CV XE GIS and related GIS project. 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.
HOUSING OCCUPANCY
H001 Total housing units H002 Occupied housing units H003 Vacant housing units H004 Homeowner vacancy rate H005 Rental vacancy rate UNITS IN STRUCTURE 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. YEAR STRUCTURE BUILT 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 ROOMS 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 BEDROOMS H038 Total housing units H039 No bedroom H040 1 bedroom H041 2 bedrooms H042 3 bedrooms H043 4 bedrooms H044 5 or more bedrooms HOUSING TENURE 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 YEAR HOUSEHOLDER MOVED INTO 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 VEHICLES AVAILABLE H057 Occupied housing units H058 No vehicles available H059 1 vehicle available H060 2 vehicles available H061 3 or more vehicles available HOUSE HEATING FUEL 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 SELECTED CHARACTERISTICS H072 Occupied housing units H073 Lacking complete plumbing facilities H074 Lacking complete kitchen facilities H075 No telephone service available OCCUPANTS PER ROOM H076 Occupied housing units H077 1.00 or less H078 1.01 to 1.50 H079 1.51 or more VALUE 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) MORTGAGE STATUS H090 Owner-occupied units H091 Housing units with a mortgage H092 Housing units without a mortgage SELECTED MONTHLY OWNER COSTS (SMOC) 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) SELECTED MONTHLY OWNER COSTS AS A PERCENTAGE OF HOUSEHOLD INCOME (SMOCAPI) 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 GROSS RENT 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 $3,000 or more H134 Median (dollars) H135 No rent paid GROSS RENT AS A PERCENTAGE OF HOUSEHOLD INCOME (GRAPI) H136 Occupied units paying rent (excluding units where GRAPI cannot be computed) H137 Less than 15.0 percent H138 15.0 to 19.9 percent H139 20.0 to 24.9 percent H140 25.0 to 29.9 percent H141 30.0 to 34.9 percent H142 35.0 percent or more H143 Not computed School District 2015 Housing Characteristics -- interactive table Click ShowAll button between Find/Queries. Use mouseover on column header to view column description. See usage notes below table. See related tables -- http://proximityone.com/rankingtables.htm. Usage Notes • If table not showing any rows; click ShowAll button below table. • Use vertical and horizontal scroll bars to navigate up/down or left/right. • Adjust column widths using column divider between header cells. • CBSA> button -- use to select districts in a specified metro/CBSA .. get metro 5-character code here .. paste the 5-character metro code in the edit box to right of CBSA> button. .. overwriting the value 19100. .. click the CBSA> button ... table refreshes with all districts in specified metro. • Find Name> button -- use to select district based on exact spelling of partial name in column 1. .. Key in exact up/low case spelling of partial name of district in the edit box to right of Find Name> button. .. overwriting the value Dallas. .. click the Find Name> button ... table refreshes with all districts with matched spelling in column 1. • Selected columns -- click the "Units.Occ.Vacant.%MdValue.$MdRent" button to show only these columns; .. click "All columns" button to restore view to all columns. • All items are estimates for 2015. • Click ShowAll button between specific area queries. • Cells with negative value could not be estimated (for this geography and this time frame). Selecting Districts within a Metro/CBSA Proceed with these steps to view districts within a selected metro/CBSA: • Click ShowAll button below table. • Click Units.Occ .. button below table. • Click the CBSA> button (using the default Dallas metro CBSA code 19100). • Click the H088 column header; click again to sort in other direction. Examine a metro of interest -- get metro 5-character code here .. • Click ShowAll button below table. • Click Units.Occ .. button below table. • Paste the 5-character metro code in the edit box to right of CBSA> button. .. overwriting the value 19100. • Click the CBSA> button. • Click the H088 column header; click again to sort in other direction. Use find codes/names to determine census tract, city/place, school district etc. geocode/area name based on address. Importance of School District Demographic-Economic Data The American Community Survey provides "richer" demographic-economic characteristics for national scope school districts. 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. ACS school district data are updated annually in December of each year for each/all school districts. ProximityOne User Group Join the ProximityOne User Group to keep up-to-date with new developments relating to metros and component geography decision-making information resources. Receive updates and access to tools and resources available only to members. Use this form to join the User Group. 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 www.twitter.com/proximityone. 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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