https://www.icpsr.umich.edu/web/ICPSR/studies/38579/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38579/terms
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.
https://www.icpsr.umich.edu/web/ICPSR/studies/38569/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38569/terms
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.
https://zipatlas.com/zip-code-database-download.htm#licensehttps://zipatlas.com/zip-code-database-download.htm#license
School Enrollment By Detailed Level Of School Report based on US Census and American Community Survey Data.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
U.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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
U.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically
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)
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
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
https://zipatlas.com/zip-code-database-download.htm#licensehttps://zipatlas.com/zip-code-database-download.htm#license
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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
economics_education_statistics_zipcode
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.)
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.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
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.
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
description: Number of Job Corps enrollees by home state and zip code; abstract: Number of Job Corps enrollees by home state and zip code
https://www.icpsr.umich.edu/web/ICPSR/studies/38579/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38579/terms
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.