61 datasets found
  1. National Neighborhood Data Archive (NaNDA): Neighborhood-School Gap by...

    • icpsr.umich.edu
    • archive.icpsr.umich.edu
    ascii, delimited, r +3
    Updated Nov 14, 2022
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    Gomez-Lopez, Iris; Kim, Min Hee; Li, Mao; Sylvers, Dominique; Esposito, Michael; Clarke, Philippa; Chenoweth, Megan (2022). National Neighborhood Data Archive (NaNDA): Neighborhood-School Gap by Census Tract and ZIP Code Tabulation Area, United States, 2009-2010 and 2015-2016 [Dataset]. http://doi.org/10.3886/ICPSR38579.v2
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    r, sas, delimited, spss, stata, asciiAvailable download formats
    Dataset updated
    Nov 14, 2022
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Gomez-Lopez, Iris; Kim, Min Hee; Li, Mao; Sylvers, Dominique; Esposito, Michael; Clarke, Philippa; Chenoweth, Megan
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/38579/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38579/terms

    Time period covered
    2009 - 2010
    Area covered
    United States
    Description

    This study contains measures of neighborhood-school gap for 2009-2010 and 2015-2016. Neighborhood-school gap (NS gap) refers to the discrepancy between the demographics of a public school and its surrounding community. For example, if 60 percent of a school's student body is Black, but 30 percent of the neighborhood population is Black, the school has a positive Black neighborhood-school gap. These datasets measure gaps in race and poverty between elementary school student populations and the census tracts and ZIP code tabulation areas (ZCTAs) that those elementary schools serve. Data is at the census tract and ZCTA level. Supplemental data containing component variables used to calculate NS gap at the school and block group level is also available.

  2. National Neighborhood Data Archive (NaNDA): School District Characteristics...

    • icpsr.umich.edu
    • archive.icpsr.umich.edu
    ascii, delimited, r +3
    Updated Oct 10, 2022
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    Kim, Min Hee; Li, Mao; Sylvers, Dominique; Esposito, Michael; Gomez-Lopez, Iris; Clarke, Philippa; Chenoweth, Megan (2022). National Neighborhood Data Archive (NaNDA): School District Characteristics and School Counts by Census Tract, ZIP Code Tabulation Area, and School District, 2000-2018 [Dataset]. http://doi.org/10.3886/ICPSR38569.v1
    Explore at:
    ascii, delimited, sas, stata, spss, rAvailable download formats
    Dataset updated
    Oct 10, 2022
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Kim, Min Hee; Li, Mao; Sylvers, Dominique; Esposito, Michael; Gomez-Lopez, Iris; Clarke, Philippa; Chenoweth, Megan
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/38569/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38569/terms

    Time period covered
    2000 - 2018
    Area covered
    United States
    Description

    This study contains counts of schools per United States census tract, ZIP code tabulation area (ZCTA), and school district from 2000 through 2018. Counts are broken down by type of school (public, charter, magnet, or private) and grade level (elementary, middle, or high). At the school district level, additional data are available on school characteristics such as district-level enrollment by race and ethnicity; numbers of teachers and counselors; teacher-student ratios; and expenditures and revenue, including per-pupil revenue.

  3. z

    School Enrollment By Detailed Level Of School

    • zipatlas.com
    Updated Dec 18, 2023
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    Zip Atlas Inc (2023). School Enrollment By Detailed Level Of School [Dataset]. https://zipatlas.com/zip-code-database-premium.htm
    Explore at:
    Dataset updated
    Dec 18, 2023
    Dataset authored and provided by
    Zip Atlas Inc
    License

    https://zipatlas.com/zip-code-database-download.htm#licensehttps://zipatlas.com/zip-code-database-download.htm#license

    Description

    School Enrollment By Detailed Level Of School Report based on US Census and American Community Survey Data.

  4. f

    School Enrollment (by Zip Code) 2017

    • gisdata.fultoncountyga.gov
    Updated Jun 25, 2019
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    Georgia Association of Regional Commissions (2019). School Enrollment (by Zip Code) 2017 [Dataset]. https://gisdata.fultoncountyga.gov/datasets/GARC::school-enrollment-by-zip-code-2017/data
    Explore at:
    Dataset updated
    Jun 25, 2019
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show counts and percentages for school enrollment by education level by Zip Code Tabulation Area in the Atlanta region.

    The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

    The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

    For further explanation of ACS estimates and margin of error, visit Census ACS website.

    Naming conventions:

    Prefixes:

    None

    Count

    p

    Percent

    r

    Rate

    m

    Median

    a

    Mean (average)

    t

    Aggregate (total)

    ch

    Change in absolute terms (value in t2 - value in t1)

    pch

    Percent change ((value in t2 - value in t1) / value in t1)

    chp

    Change in percent (percent in t2 - percent in t1)

    Suffixes:

    None

    Change over two periods

    _e

    Estimate from most recent ACS

    _m

    Margin of Error from most recent ACS

    _00

    Decennial 2000

    Attributes:

    SumLevel

    Summary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)

    GEOID

    Census tract Federal Information Processing Series (FIPS) code

    NAME

    Name of geographic unit

    Planning_Region

    Planning region designation for ARC purposes

    Acres

    Total area within the tract (in acres)

    SqMi

    Total area within the tract (in square miles)

    County

    County identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)

    CountyName

    County Name

    Pop3P_e

    # Population ages 3 and over, 2017

    Pop3P_m

    # Population ages 3 and over, 2017 (MOE)

    InSchool_e

    # Population 3 years and over enrolled in school, 2017

    InSchool_m

    # Population 3 years and over enrolled in school, 2017 (MOE)

    InPreSchool_e

    # Enrolled in nursery school, preschool, 2017

    InPreSchool_m

    # Enrolled in nursery school, preschool, 2017 (MOE)

    pInPreSchool_e

    % Enrolled in nursery school, preschool, 2017

    pInPreSchool_m

    % Enrolled in nursery school, preschool, 2017 (MOE)

    InKindergarten_e

    # Enrolled in kindergarten, 2017

    InKindergarten_m

    # Enrolled in kindergarten, 2017 (MOE)

    pInKindergarten_e

    % Enrolled in kindergarten, 2017

    pInKindergarten_m

    % Enrolled in kindergarten, 2017 (MOE)

    InElementary_e

    # Enrolled in elementary school (grades 1-8), 2017

    InElementary_m

    # Enrolled in elementary school (grades 1-8), 2017 (MOE)

    pInElementary_e

    % Enrolled in elementary school (grades 1-8), 2017

    pInElementary_m

    % Enrolled in elementary school (grades 1-8), 2017 (MOE)

    InHS_e

    # Enrolled in high school (grades 9-12), 2017

    InHS_m

    # Enrolled in high school (grades 9-12), 2017 (MOE)

    pInHS_e

    % Enrolled in high school (grades 9-12), 2017

    pInHS_m

    % Enrolled in high school (grades 9-12), 2017 (MOE)

    InCollegeGradSch_e

    # Enrolled in college or graduate school, 2017

    InCollegeGradSch_m

    # Enrolled in college or graduate school, 2017 (MOE)

    last_edited_date

    Last date the feature was edited by ARC

    Source: U.S. Census Bureau, Atlanta Regional Commission

    Date: 2013-2017

    For additional information, please visit the Census ACS website.

  5. Census Data Explorer | USDA-FNS Farm to School Census

    • agdatacommons.nal.usda.gov
    bin
    Updated Feb 16, 2024
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    USDA Farm to School Program (2024). Census Data Explorer | USDA-FNS Farm to School Census [Dataset]. https://agdatacommons.nal.usda.gov/articles/dataset/Census_Data_Explorer_USDA-FNS_Farm_to_School_Census/25234120
    Explore at:
    binAvailable download formats
    Dataset updated
    Feb 16, 2024
    Dataset provided by
    United States Department of Agriculturehttp://usda.gov/
    Food and Nutrition Servicehttps://www.fns.usda.gov/
    Authors
    USDA Farm to School Program
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    The Farm to School Census measures USDA's progress toward improving access to local foods in schools. The web-based interface allows users to run customized searches using data from the Farm to School Census. From a total of 18,104 public, private, and charter school districts in the target list frame, 12,585 schools and school districts completed usable responses for a response rate of 70%. Visualizations display national and state level data, and explanatory notes for each portion of the survey questionnaire are provided. Users can focus their search by location/state/school district/zip code, participation level, local food purchased category (fruit, vegetables, fluid milk, other dairy, meat/poultry, eggs, seafood, plant-based protein, grains/flour, baked goods, herbs), and sources (purchased directly or through intermediary). Resources in this dataset:Resource Title: Census Data Explorer | USDA-FNS Farm to School Census. File Name: Web Page, url: https://farmtoschoolcensus.fns.usda.gov/census-results/census-data-explorer This searchable database allows users to run customized searches using data from the Farm to School Census.

  6. a

    School Enrollment (by Zip Code) 2019

    • opendata.atlantaregional.com
    • gisdata.fultoncountyga.gov
    • +1more
    Updated Feb 26, 2021
    + more versions
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    Georgia Association of Regional Commissions (2021). School Enrollment (by Zip Code) 2019 [Dataset]. https://opendata.atlantaregional.com/datasets/school-enrollment-by-zip-code-2019
    Explore at:
    Dataset updated
    Feb 26, 2021
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau.For a deep dive into the data model including every specific metric, see the Infrastructure Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.Naming conventions:Prefixes: None Countp Percentr Ratem Mediana Mean (average)t Aggregate (total)ch Change in absolute terms (value in t2 - value in t1)pch Percent change ((value in t2 - value in t1) / value in t1)chp Change in percent (percent in t2 - percent in t1)s Significance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computed Suffixes: _e19 Estimate from 2014-19 ACS_m19 Margin of Error from 2014-19 ACS_00_v19 Decennial 2000, re-estimated to 2019 geography_00_19 Change, 2000-19_e10_v19 2006-10 ACS, re-estimated to 2019 geography_m10_v19 Margin of Error from 2006-10 ACS, re-estimated to 2019 geography_e10_19 Change, 2010-19The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2015-2019). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2015-2019Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the manifest: https://www.arcgis.com/sharing/rest/content/items/3d489c725bb24f52a987b302147c46ee/data

  7. w

    High School (ONLY) Educational Attainment per zip code

    • data.wu.ac.at
    csv, json, xml
    Updated Mar 25, 2013
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    US Census Bureau (2013). High School (ONLY) Educational Attainment per zip code [Dataset]. https://data.wu.ac.at/odso/bronx_lehman_cuny_edu/aDhxYi1ydTQ0
    Explore at:
    json, xml, csvAvailable download formats
    Dataset updated
    Mar 25, 2013
    Dataset provided by
    US Census Bureau
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    American Community Survey data on school/education level attainment per zip code for the Bronx for the survey period of 2007-2011. Circle color = population of 18-24 year olds. Size = percentage of that population that has only a high school level education. (Graduated High school, went no further)

  8. Economics & Education Statistics - Zip Code

    • data-sccphd.opendata.arcgis.com
    Updated Feb 21, 2018
    + more versions
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    Santa Clara County Public Health (2018). Economics & Education Statistics - Zip Code [Dataset]. https://data-sccphd.opendata.arcgis.com/datasets/economics-education-statistics-zip-code
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    Dataset updated
    Feb 21, 2018
    Dataset provided by
    Santa Clara County Public Health Departmenthttps://publichealth.sccgov.org/
    Authors
    Santa Clara County Public Health
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Zip Code; Median household income; Unemployed (ages GE 16); Families below 185% FPL; Children (ages 0-17) below 185% FPL; Children (ages 3-4) enrolled in preschool or nursery school; Less than high school; High school graduate; Some college or associates degree; College graduate or higher; High school graduate or less. Percentages unless otherwise noted. Source information provided at: https://www.sccgov.org/sites/phd/hi/hd/Documents/City%20Profiles/Methodology/Neighborhood%20profile%20methodology_082914%20final%20for%20web.pdf

  9. z

    Sex By School Enrollment By Type Of School By Age For The Population 3 Years...

    • zipatlas.com
    Updated Dec 18, 2023
    + more versions
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    Zip Atlas Inc (2023). Sex By School Enrollment By Type Of School By Age For The Population 3 Years And Over [Dataset]. https://zipatlas.com/zip-code-database-premium.htm
    Explore at:
    Dataset updated
    Dec 18, 2023
    Dataset authored and provided by
    Zip Atlas Inc
    License

    https://zipatlas.com/zip-code-database-download.htm#licensehttps://zipatlas.com/zip-code-database-download.htm#license

    Description

    Sex By School Enrollment By Type Of School By Age For The Population 3 Years And Over Report based on US Census and American Community Survey Data.

  10. a

    School Enrollment (by Zip Code) 2015

    • opendata.atlantaregional.com
    Updated Jun 1, 2018
    + more versions
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    Georgia Association of Regional Commissions (2018). School Enrollment (by Zip Code) 2015 [Dataset]. https://opendata.atlantaregional.com/datasets/cf90898bef9c43a0b945e930bb1d65d2
    Explore at:
    Dataset updated
    Jun 1, 2018
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from using data from American Community Survey 5-year estimates for 2011-2015 to show school enrollment by level of school, by zip code in the Atlanta region.

    The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number. ACS data presented here represent combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2011-2015). Therefore, these data do not represent any one specific point in time or even one specific year. For further explanation of ACS estimates and methodology, click here.

    Attributes:

    ZIP = Zip code (text)

    ZIP_dbl = Zip code (numeric)

    Total_Population_2010 = Total Population, 2010 Census

    Total_Population_2011_2015_ACS = Total Population, 2011-2015 American Community Survey (ACS)

    Pop_3yrsOlder_Enrolld_in_School = #, Population 3 years and over enrolled in school

    Nursery_school_preschool = #, Enrolled in nursery school, preschool

    Pct_Nursery_Preschool = %, Enrolled in nursery school, preschool

    Kindergarten = #, Enrolled in kindergarten

    Percent_Kindergarten = %, Enrolled in kindergarten

    Elementary_school_grades_1_8 = #, Enrolled in elementary school (grades 1-8)

    Percent_ElemSchool_grades_1_8 = %, Enrolled in elementary school (grades 1-8)

    High_school_grades_9_12 = #, Enrolled in high school (grades 9-12)

    Percent_HS_grades_9_12 = %, Enrolled in high school (grades 9-12)

    College_or_graduate_school = #, Enrolled in college or graduate school

    Percent_College_or_grad_school = %, Enrolled in college or graduate school

    last_edited_date = Last date the feature was edited by ARC

    Source: U.S. Census Bureau, Atlanta Regional Commission

    Date: 2011-2015

  11. Public School Characteristics - All US Districts

    • kaggle.com
    Updated Aug 10, 2024
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    The Bumpkin (2024). Public School Characteristics - All US Districts [Dataset]. https://www.kaggle.com/datasets/thebumpkin/public-school-characteristics-all-us-districts/suggestions?status=pending&yourSuggestions=true
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 10, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    The Bumpkin
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    The dataset includes detailed information on 100,000 school districts, covering attributes such as school names, locations, and enrollment figures. Key columns provide data on geographic details (city, state, ZIP code), charter status, grade levels, and school types. It also includes demographic breakdowns by race and ethnicity, as well as enrollment counts for each grade. Additional information includes student eligibility for free or reduced lunch and full-time equivalent staff. This dataset is useful for analyzing educational trends, resource allocation, and demographic patterns across various school districts.

    This data is for the 2022-2023 school year.

  12. a

    School Enrollment (by Zip Code) 2018

    • opendata.atlantaregional.com
    Updated Mar 4, 2020
    + more versions
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    Georgia Association of Regional Commissions (2020). School Enrollment (by Zip Code) 2018 [Dataset]. https://opendata.atlantaregional.com/maps/cbd0fd8f43b1492083801e6fe8de89f7
    Explore at:
    Dataset updated
    Mar 4, 2020
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission using data from the U.S. Census Bureau.

    The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

    The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2014-2018). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

    For a deep dive into the data model including every specific metric, see the Infrastructure Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics.

    For further explanation of ACS estimates and margin of error, visit Census ACS website.

    Naming conventions:

    Prefixes:

    None

    Count

    p

    Percent

    r

    Rate

    m

    Median

    a

    Mean (average)

    t

    Aggregate (total)

    ch

    Change in absolute terms (value in t2 - value in t1)

    pch

    Percent change ((value in t2 - value in t1) / value in t1)

    chp

    Change in percent (percent in t2 - percent in t1)

    s

    Significance flag for change: 1 = statistically significant with a 90% Confidence Interval, 0 = not statistically significant, blank = cannot be computed

    Suffixes:

    _e18

    Estimate from 2014-18 ACS

    _m18

    Margin of Error from 2014-18 ACS

    _00_v18

    Decennial 2000 in 2018 geography boundary

    _00_18

    Change, 2000-18

    _e10_v18

    Estimate from 2006-10 ACS in 2018 geography boundary

    _m10_v18

    Margin of Error from 2006-10 ACS in 2018 geography boundary

    _e10_18

    Change, 2010-18

  13. a

    Historical Case Rates by High School District

    • data-maricopa.opendata.arcgis.com
    • data.gilbertaz.gov
    • +2more
    Updated Oct 8, 2020
    + more versions
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    Maricopa County Enterprise GIS (2020). Historical Case Rates by High School District [Dataset]. https://data-maricopa.opendata.arcgis.com/maps/historical-case-rates-by-high-school-district
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    Dataset updated
    Oct 8, 2020
    Dataset authored and provided by
    Maricopa County Enterprise GIS
    Area covered
    Description

    Cumulation of the weekly release of COVID-19 data for Maricopa County by High School District. Includes COVID Case Rate per 100k population as viewed on the Maricopa County School Reopening Dashboard map by week. For more information about the data, visit: https://www.maricopa.gov/5594/School-Metrics.

  14. a

    School Enrollment 2023 (all geographies, statewide)

    • opendata.atlantaregional.com
    • gisdata.fultoncountyga.gov
    • +2more
    Updated Feb 21, 2025
    + more versions
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    Georgia Association of Regional Commissions (2025). School Enrollment 2023 (all geographies, statewide) [Dataset]. https://opendata.atlantaregional.com/maps/c50facde31074c61a26c05be88c6a9fe
    Explore at:
    Dataset updated
    Feb 21, 2025
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Description

    These data were developed by the Research & Analytics Department at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable.For a deep dive into the data model including every specific metric, see the ACS 2019-2023. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e23Estimate from 2019-23 ACS_m23Margin of Error from 2019-23 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_23Change, 2010-23 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLineStatistical (buffer)BeltLineStatisticalSub (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)County (statewide)CCDIST = County Commission Districts (statewide where applicable)CCSUPERDIST = County Commission Superdistricts (DeKalb)Georgia House (statewide)Georgia Senate (statewide)HSSA = High School Statistical Area (11 county region)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)State of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2019-2023). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2019-2023Open Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://opendata.atlantaregional.com/documents/182e6fcf8201449086b95adf39471831/about

  15. O

    Economics & Education Statistics - Zip Code

    • data.sccgov.org
    application/rdfxml +5
    Updated Apr 26, 2019
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    (2019). Economics & Education Statistics - Zip Code [Dataset]. https://data.sccgov.org/dataset/Economics-Education-Statistics-Zip-Code/63fc-ujyc
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    csv, json, xml, application/rdfxml, tsv, application/rssxmlAvailable download formats
    Dataset updated
    Apr 26, 2019
    Description

    economics_education_statistics_zipcode

  16. GreatSchools (Phila. only)

    • catalog.data.gov
    • data.wu.ac.at
    Updated Mar 31, 2025
    + more versions
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    GreatSchools.org (2025). GreatSchools (Phila. only) [Dataset]. https://catalog.data.gov/dataset/greatschools-phila-only
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    Dataset updated
    Mar 31, 2025
    Dataset provided by
    GreatSchoolshttp://greatschools.org/
    Area covered
    Philadelphia
    Description

    GreatSchools is an online database of school locations and relevant information, including metrics submitted by school districts and government agencies and school reviews submitted by individual users. Schools within the database include public, charter, and private schools Users can search for schools by name, district, county, or zip code to view an overall rating and metrics, including test scores, demographics (enrollment), and area statistics. Through registration, users can submit their own reviews, receive grade-by-grade tips, and participate in/access reserved articles and features on education-related topics. Users can also access school/education data by structuring customized data request processes (API). Free registration entails interactivity and extra privileges (comment/review capability; participation in community forum, customized, detailed grade-by-grade tips; and in-depth article access.)

  17. a

    Historical Case Rates by Elementary School District

    • data-maricopa.opendata.arcgis.com
    • data.gilbertaz.gov
    • +2more
    Updated Oct 8, 2020
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    Maricopa County Enterprise GIS (2020). Historical Case Rates by Elementary School District [Dataset]. https://data-maricopa.opendata.arcgis.com/datasets/historical-case-rates-by-elementary-school-district
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    Dataset updated
    Oct 8, 2020
    Dataset authored and provided by
    Maricopa County Enterprise GIS
    Area covered
    Description

    Cumulation of the weekly release of COVID-19 data for Maricopa County by Elementary School District. Includes COVID Case Rate per 100k population as viewed on the Maricopa County School Reopening Dashboard map by week. For more information about the data, visit: https://www.maricopa.gov/5594/School-Metrics.

  18. C

    DRCOG Census Data

    • data.colorado.gov
    • data.wu.ac.at
    application/rdfxml +5
    Updated Jan 23, 2018
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    US Census (2018). DRCOG Census Data [Dataset]. https://data.colorado.gov/w/a5w5-9fce/c48n-6dwv?cur=5Fc0SNCdQXT
    Explore at:
    application/rssxml, xml, csv, application/rdfxml, json, tsvAvailable download formats
    Dataset updated
    Jan 23, 2018
    Dataset authored and provided by
    US Census
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Block Groups. Blocks. Combined Statistical Areas. Subdivisions. Census Designated Places. School Districts. Zip Codes. And more. All data from the United States Census, clipped to the DRCOG region.

  19. w

    2018 Pre-K School Directory

    • data.wu.ac.at
    • data.cityofnewyork.us
    • +2more
    csv, json, rdf, xml
    Updated Jan 18, 2018
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    City of New York (2018). 2018 Pre-K School Directory [Dataset]. https://data.wu.ac.at/schema/data_gov/NGE5YjUzZTUtYWZhZi00YjdjLWFhMzMtZmY3N2Y0YzY4ZWVj
    Explore at:
    csv, json, xml, rdfAvailable download formats
    Dataset updated
    Jan 18, 2018
    Dataset provided by
    City of New York
    Description

    These data are collected to inform families applying to Pre-K for All of the programs available. This is a spreadsheet version of the exact data points printed in the borough-level directories and the online PDFs. Each record represents a school participating in Pre-K for All. The information for each school is collected by the Department of Early Childhood Education (Department of Education). The "Who Got Offers" section of the spreadsheet is calculated by the Office of Student Enrollment (Department of Education) based on results from Round 1 of the Fall 2017 admissions process. This spreadsheet is simply a different representation of the same material produced in the printed and widely distributed Pre-K directories. This spreadsheet should not be used to identify current programs, as the directory was printed in December 2017 and schools are subject to change. For the most updated list of Pre-K for All schools, use the UPK Sites Directory compiled by the Department of Early Childhood Education.

    Disclaimer: The following columns were added to this directory to meet the Geo-spatial Standards of Local Law 108 of 2015

    • Postcode / Zip code • Latitude • Longitude • Community Board • Council District • Census tract • BIN • BBL • NTA

  20. d

    Job Corps Student Enrollment by State and Zip Code.

    • datadiscoverystudio.org
    • cloud.csiss.gmu.edu
    • +1more
    Updated Mar 1, 2017
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    (2017). Job Corps Student Enrollment by State and Zip Code. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/d3b69459de2b4c7e9406f1e842e846f6/html
    Explore at:
    Dataset updated
    Mar 1, 2017
    Description

    description: Number of Job Corps enrollees by home state and zip code; abstract: Number of Job Corps enrollees by home state and zip code

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Close
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Gomez-Lopez, Iris; Kim, Min Hee; Li, Mao; Sylvers, Dominique; Esposito, Michael; Clarke, Philippa; Chenoweth, Megan (2022). National Neighborhood Data Archive (NaNDA): Neighborhood-School Gap by Census Tract and ZIP Code Tabulation Area, United States, 2009-2010 and 2015-2016 [Dataset]. http://doi.org/10.3886/ICPSR38579.v2
Organization logo

National Neighborhood Data Archive (NaNDA): Neighborhood-School Gap by Census Tract and ZIP Code Tabulation Area, United States, 2009-2010 and 2015-2016

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r, sas, delimited, spss, stata, asciiAvailable download formats
Dataset updated
Nov 14, 2022
Dataset provided by
Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
Authors
Gomez-Lopez, Iris; Kim, Min Hee; Li, Mao; Sylvers, Dominique; Esposito, Michael; Clarke, Philippa; Chenoweth, Megan
License

https://www.icpsr.umich.edu/web/ICPSR/studies/38579/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38579/terms

Time period covered
2009 - 2010
Area covered
United States
Description

This study contains measures of neighborhood-school gap for 2009-2010 and 2015-2016. Neighborhood-school gap (NS gap) refers to the discrepancy between the demographics of a public school and its surrounding community. For example, if 60 percent of a school's student body is Black, but 30 percent of the neighborhood population is Black, the school has a positive Black neighborhood-school gap. These datasets measure gaps in race and poverty between elementary school student populations and the census tracts and ZIP code tabulation areas (ZCTAs) that those elementary schools serve. Data is at the census tract and ZCTA level. Supplemental data containing component variables used to calculate NS gap at the school and block group level is also available.

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