100+ datasets found
  1. College enrollment in public and private institutions in the U.S. 1965-2031

    • statista.com
    • thefarmdosupply.com
    Updated Mar 25, 2025
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    Statista (2025). College enrollment in public and private institutions in the U.S. 1965-2031 [Dataset]. https://www.statista.com/statistics/183995/us-college-enrollment-and-projections-in-public-and-private-institutions/
    Explore at:
    Dataset updated
    Mar 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    There were approximately 18.58 million college students in the U.S. in 2022, with around 13.49 million enrolled in public colleges and a further 5.09 million students enrolled in private colleges. The figures are projected to remain relatively constant over the next few years.

    What is the most expensive college in the U.S.? The overall number of higher education institutions in the U.S. totals around 4,000, and California is the state with the most. One important factor that students – and their parents – must consider before choosing a college is cost. With annual expenses totaling almost 78,000 U.S. dollars, Harvey Mudd College in California was the most expensive college for the 2021-2022 academic year. There are three major costs of college: tuition, room, and board. The difference in on-campus and off-campus accommodation costs is often negligible, but they can change greatly depending on the college town.

    The differences between public and private colleges Public colleges, also called state colleges, are mostly funded by state governments. Private colleges, on the other hand, are not funded by the government but by private donors and endowments. Typically, private institutions are  much more expensive. Public colleges tend to offer different tuition fees for students based on whether they live in-state or out-of-state, while private colleges have the same tuition cost for every student.

  2. 2022 USA Undergrad College Rankings & More

    • kaggle.com
    Updated Mar 20, 2022
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    Neel Gajare (2022). 2022 USA Undergrad College Rankings & More [Dataset]. https://www.kaggle.com/datasets/neelgajare/2022-usa-college-rankings-more
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 20, 2022
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Neel Gajare
    Description

    Context

    This dataset contains the US News rankings of the best American universities of undergraduate programs. This is how US News ranks the colleges: "We calculated 10 distinct overall rankings where colleges and universities were grouped by their academic missions. For each ranking, the sum of weighted, normalized values across 17 indicators of academic quality determine each school's overall score and, by extension, its overall rank. The top performer(s) in each ranking displays an overall score of 100. Others' overall scores are on a 0-99 scale reflecting the distance from their ranking's top-performing school(s). Those placing outside the top 75% display their ranking's bottom quartile range (e.g., No. 90-120) instead of their individual ranks (e.g., No. 102)."

    Content

    This dataset contains the rankings of 392 American universities based on their undergraduate programs. It also contains the tuitions and enrollment numbers of each university. 2 colleges don't have tuition data, so it is labelled -1.

    Acknowledgements

    We acknowledge US News for providing these rankings.

    Inspiration

    As a high schooler applying to undergraduate programs in America, it would be useful to know which colleges are best, and to compare tuitions and enrollment numbers.

  3. d

    2017-18 - 2021-22 Demographic Snapshot

    • catalog.data.gov
    • data.cityofnewyork.us
    Updated Nov 29, 2024
    + more versions
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    data.cityofnewyork.us (2024). 2017-18 - 2021-22 Demographic Snapshot [Dataset]. https://catalog.data.gov/dataset/2017-18-2021-22-demographic-snapshot
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    Dataset updated
    Nov 29, 2024
    Dataset provided by
    data.cityofnewyork.us
    Description

    "Enrollment counts are based on the October 31 Audited Register for the 2017-18 to 2019-20 school years. To account for the delay in the start of the school year, enrollment counts are based on the November 13 Audited Register for 2020-21 and the November 12 Audited Register for 2021-22. * Please note that October 31 (and November 12-13) enrollment is not audited for charter schools or Pre-K Early Education Centers (NYCEECs). Charter schools are required to submit enrollment as of BEDS Day, the first Wednesday in October, to the New York State Department of Education." Enrollment counts in the Demographic Snapshot will likely exceed operational enrollment counts due to the fact that long-term absence (LTA) students are excluded for funding purposes. Data on students with disabilities, English Language Learners, students' povery status, and students' Economic Need Value are as of the June 30 for each school year except in 2021-22. Data on SWDs, ELLs, Poverty, and ENI in the 2021-22 school year are as of March 7, 2022. 3-K and Pre-K enrollment totals include students in both full-day and half-day programs. Four-year-old students enrolled in Family Childcare Centers are categorized as 3K students for the purposes of this report. All schools listed are as of the 2021-22 school year. Schools closed before 2021-22 are not included in the school level tab but are included in the data for citywide, borough, and district. Programs and Pre-K NYC Early Education Centers (NYCEECs) are not included on the school-level tab. Due to missing demographic information in rare cases at the time of the enrollment snapshot, demographic categories do not always add up to citywide totals. Students with disabilities are defined as any child receiving an Individualized Education Program (IEP) as of the end of the school year (or March 7 for 2021-22). NYC DOE "Poverty" counts are based on the number of students with families who have qualified for free or reduced price lunch, or are eligible for Human Resources Administration (HRA) benefits. In previous years, the poverty indicator also included students enrolled in a Universal Meal School (USM), where all students automatically qualified, with the exception of middle schools, D75 schools and Pre-K centers. In 2017-18, all students in NYC schools became eligible for free lunch. In order to better reflect free and reduced price lunch status, the poverty indicator does not include student USM status, and retroactively applies this rule to previous years. "The school’s Economic Need Index is the average of its students’ Economic Need Values. The Economic Need Index (ENI) estimates the percentage of students facing economic hardship. The 2014-15 school year is the first year we provide ENI estimates. The metric is calculated as follows: * The student’s Economic Need Value is 1.0 if: o The student is eligible for public assistance from the NYC Human Resources Administration (HRA); o The student lived in temporary housing in the past four years; or o The student is in high school, has a home language other than English, and entered the NYC DOE for the first time within the last four years. * Otherwise, the student’s Economic Need Value is based on the percentage of families (with school-age children) in the student’s census tract whose income is below the poverty level, as estimated by the American Community Survey 5-Year estimate (2020 ACS estimates were used in calculations for 2021-22 ENI). The student’s Economic Need Value equals this percentage divided by 100. Due to differences in the timing of when student demographic, address and census data were pulled, ENI values may vary, slightly, from the ENI values reported in the School Quality Reports. In previous years, student census tract data was based on students’ addresses at the time of ENI calculation. Beginning in 2018-19, census tract data is based on students’ addresses as of the Audited Register date of the g

  4. d

    USA College Student Database - ASL Marketing

    • datarade.ai
    Updated Dec 19, 2019
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    ASL Marketing (2019). USA College Student Database - ASL Marketing [Dataset]. https://datarade.ai/data-products/college-student-data
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    Dataset updated
    Dec 19, 2019
    Dataset authored and provided by
    ASL Marketing
    Area covered
    United States
    Description

    Data product is provided by ASL Marketing. It contains current college students who are attending colleges and universities nationwide. Connect with this market by: Class Year Field of Study Home/School address College Attending Ethnicity School Type Region Sports Conference Gender eSports Email

  5. C

    Pittsburgh American Community Survey 2015, School Enrollment

    • data.wprdc.org
    csv, txt
    Updated Jun 7, 2024
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    City of Pittsburgh (2024). Pittsburgh American Community Survey 2015, School Enrollment [Dataset]. https://data.wprdc.org/dataset/pittsburgh-american-community-survey-2015-school-enrollment
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    txt, csvAvailable download formats
    Dataset updated
    Jun 7, 2024
    Dataset authored and provided by
    City of Pittsburgh
    License

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

    Area covered
    Pittsburgh
    Description

    School enrollment data are used to assess the socioeconomic condition of school-age children. Government agencies also require these data for funding allocations and program planning and implementation.

    Data on school enrollment and grade or level attending were derived from answers to Question 10 in the 2015 American Community Survey (ACS). People were classified as enrolled in school if they were attending a public or private school or college at any time during the 3 months prior to the time of interview. The question included instructions to “include only nursery or preschool, kindergarten, elementary school, home school, and schooling which leads to a high school diploma, or a college degree.” Respondents who did not answer the enrollment question were assigned the enrollment status and type of school of a person with the same age, sex, race, and Hispanic or Latino origin whose residence was in the same or nearby area.

    School enrollment is only recorded if the schooling advances a person toward an elementary school certificate, a high school diploma, or a college, university, or professional school (such as law or medicine) degree. Tutoring or correspondence schools are included if credit can be obtained from a public or private school or college. People enrolled in “vocational, technical, or business school” such as post secondary vocational, trade, hospital school, and on job training were not reported as enrolled in school. Field interviewers were instructed to classify individuals who were home schooled as enrolled in private school. The guide sent out with the mail questionnaire includes instructions for how to classify home schoolers.

    Enrolled in Public and Private School – Includes people who attended school in the reference period and indicated they were enrolled by marking one of the questionnaire categories for “public school, public college,” or “private school, private college, home school.” The instruction guide defines a public school as “any school or college controlled and supported primarily by a local, county, state, or federal government.” Private schools are defined as schools supported and controlled primarily by religious organizations or other private groups. Home schools are defined as “parental-guided education outside of public or private school for grades 1-12.” Respondents who marked both the “public” and “private” boxes are edited to the first entry, “public.”

    Grade in Which Enrolled – From 1999-2007, in the ACS, people reported to be enrolled in “public school, public college” or “private school, private college” were classified by grade or level according to responses to Question 10b, “What grade or level was this person attending?” Seven levels were identified: “nursery school, preschool;” “kindergarten;” elementary “grade 1 to grade 4” or “grade 5 to grade 8;” high school “grade 9 to grade 12;” “college undergraduate years (freshman to senior);” and “graduate or professional school (for example: medical, dental, or law school).”

    In 2008, the school enrollment questions had several changes. “Home school” was explicitly included in the “private school, private college” category. For question 10b the categories changed to the following “Nursery school, preschool,” “Kindergarten,” “Grade 1 through grade 12,” “College undergraduate years (freshman to senior),” “Graduate or professional school beyond a bachelor’s degree (for example: MA or PhD program, or medical or law school).” The survey question allowed a write-in for the grades enrolled from 1-12.

    Question/Concept History – Since 1999, the ACS enrollment status question (Question 10a) refers to “regular school or college,” while the 1996-1998 ACS did not restrict reporting to “regular” school, and contained an additional category for the “vocational, technical or business school.” The 1996-1998 ACS used the educational attainment question to estimate level of enrollment for those reported to be enrolled in school, and had a single year write-in for the attainment of grades 1 through 11. Grade levels estimated using the attainment question were not consistent with other estimates, so a new question specifically asking grade or level of enrollment was added starting with the 1999 ACS questionnaire.

    Limitation of the Data – Beginning in 2006, the population universe in the ACS includes people living in group quarters. Data users may see slight differences in levels of school enrollment in any given geographic area due to the inclusion of this population. The extent of this difference, if any, depends on the type of group quarters present and whether the group quarters population makes up a large proportion of the total population. For example, in areas that are home to several colleges and universities, the percent of individuals 18 to 24 who were enrolled in college or graduate school would increase, as people living in college dormitories are now included in the universe.

  6. d

    2020 - 2021 Diversity Report

    • catalog.data.gov
    • data.cityofnewyork.us
    • +1more
    Updated Nov 29, 2024
    + more versions
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    data.cityofnewyork.us (2024). 2020 - 2021 Diversity Report [Dataset]. https://catalog.data.gov/dataset/2020-2021-diversity-report
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    Dataset updated
    Nov 29, 2024
    Dataset provided by
    data.cityofnewyork.us
    Description

    Report on Demographic Data in New York City Public Schools, 2020-21Enrollment counts are based on the November 13 Audited Register for 2020. Categories with total enrollment values of zero were omitted. Pre-K data includes students in 3-K. Data on students with disabilities, English language learners, and student poverty status are as of March 19, 2021. Due to missing demographic information in rare cases and suppression rules, demographic categories do not always add up to total enrollment and/or citywide totals. NYC DOE "Eligible for free or reduced-price lunch” counts are based on the number of students with families who have qualified for free or reduced-price lunch or are eligible for Human Resources Administration (HRA) benefits. English Language Arts and Math state assessment results for students in grade 9 are not available for inclusion in this report, as the spring 2020 exams did not take place. Spring 2021 ELA and Math test results are not included in this report for K-8 students in 2020-21. Due to the COVID-19 pandemic’s complete transformation of New York City’s school system during the 2020-21 school year, and in accordance with New York State guidance, the 2021 ELA and Math assessments were optional for students to take. As a result, 21.6% of students in grades 3-8 took the English assessment in 2021 and 20.5% of students in grades 3-8 took the Math assessment. These participation rates are not representative of New York City students and schools and are not comparable to prior years, so results are not included in this report. Dual Language enrollment includes English Language Learners and non-English Language Learners. Dual Language data are based on data from STARS; as a result, school participation and student enrollment in Dual Language programs may differ from the data in this report. STARS course scheduling and grade management software applications provide a dynamic internal data system for school use; while standard course codes exist, data are not always consistent from school to school. This report does not include enrollment at District 75 & 79 programs. Students enrolled at Young Adult Borough Centers are represented in the 9-12 District data but not the 9-12 School data. “Prior Year” data included in Comparison tabs refers to data from 2019-20. “Year-to-Year Change” data included in Comparison tabs indicates whether the demographics of a school or special program have grown more or less similar to its district or attendance zone (or school, for special programs) since 2019-20. Year-to-year changes must have been at least 1 percentage point to qualify as “More Similar” or “Less Similar”; changes less than 1 percentage point are categorized as “No Change”. The admissions method tab contains information on the admissions methods used for elementary, middle, and high school programs during the Fall 2020 admissions process. Fall 2020 selection criteria are included for all programs with academic screens, including middle and high school programs. Selection criteria data is based on school-reported information. Fall 2020 Diversity in Admissions priorities is included for applicable middle and high school programs. Note that the data on each school’s demographics and performance includes all students of the given subgroup who were enrolled in the school on November 13, 2020. Some of these students may not have been admitted under the admissions method(s) shown, as some students may have enrolled in the school outside the centralized admissions process (via waitlist, over-the-counter, or transfer), and schools may have changed admissions methods over the past few years. Admissions methods are only reported for grades K-12. "3K and Pre-Kindergarten data are reported at the site level. See below for definitions of site types included in this report. Additionally, please note that this report excludes all students at District 75 sites, reflecting slightly lower enrollment than our total of 60,265 students

  7. A

    ‘U.S. News and World Report’s College Data’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Nov 12, 2021
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2021). ‘U.S. News and World Report’s College Data’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-u-s-news-and-world-reports-college-data-d469/99cb1bfc/?iid=010-329&v=presentation
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    Dataset updated
    Nov 12, 2021
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘U.S. News and World Report’s College Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/flyingwombat/us-news-and-world-reports-college-data on 30 September 2021.

    --- Dataset description provided by original source is as follows ---

    Context

    Statistics for a large number of US Colleges from the 1995 issue of US News and World Report.

    Content

    A data frame with 777 observations on the following 18 variables.

    Private A factor with levels No and Yes indicating private or public university

    Apps Number of applications received

    Accept Number of applications accepted

    Enroll Number of new students enrolled

    Top10perc Pct. new students from top 10% of H.S. class

    Top25perc Pct. new students from top 25% of H.S. class

    F.Undergrad Number of fulltime undergraduates

    P.Undergrad Number of parttime undergraduates

    Outstate Out-of-state tuition

    Room.Board Room and board costs

    Books Estimated book costs

    Personal Estimated personal spending

    PhD Pct. of faculty with Ph.D.’s

    Terminal Pct. of faculty with terminal degree

    S.F.Ratio Student/faculty ratio

    perc.alumni Pct. alumni who donate

    Expend Instructional expenditure per student

    Grad.Rate Graduation rate

    Source

    This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University.

    The dataset was used in the ASA Statistical Graphics Section’s 1995 Data Analysis Exposition.

    --- Original source retains full ownership of the source dataset ---

  8. US Dept of Education: College Scorecard

    • kaggle.com
    zip
    Updated Nov 9, 2017
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    Kaggle (2017). US Dept of Education: College Scorecard [Dataset]. https://www.kaggle.com/forums/f/810/us-dept-of-education-college-scorecard
    Explore at:
    zip(589617678 bytes)Available download formats
    Dataset updated
    Nov 9, 2017
    Dataset authored and provided by
    Kaggle
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    United States
    Description

    It's no secret that US university students often graduate with debt repayment obligations that far outstrip their employment and income prospects. While it's understood that students from elite colleges tend to earn more than graduates from less prestigious universities, the finer relationships between future income and university attendance are quite murky. In an effort to make educational investments less speculative, the US Department of Education has matched information from the student financial aid system with federal tax returns to create the College Scorecard dataset.

    Kaggle is hosting the College Scorecard dataset in order to facilitate shared learning and collaboration. Insights from this dataset can help make the returns on higher education more transparent and, in turn, more fair.

    Data Description

    Here's a script showing an exploratory overview of some of the data.

    college-scorecard-release-*.zip contains a compressed version of the same data available through Kaggle Scripts.

    It consists of three components:

    • All the raw data files released in version 1.40 of the college scorecard data
    • Scorecard.csv, a single CSV file with all the years data combined. In it, we've converted categorical variables represented by integer keys in the original data to their labels and added a Year column
    • database.sqlite, a SQLite database containing a single Scorecard table that contains the same information as Scorecard.csv

    New to data exploration in R? Take the free, interactive DataCamp course, "Data Exploration With Kaggle Scripts," to learn the basics of visualizing data with ggplot. You'll also create your first Kaggle Scripts along the way.

  9. US Data Science and Analytics Master's Programs

    • kaggle.com
    Updated Mar 26, 2024
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    Shahriar Kabir (2024). US Data Science and Analytics Master's Programs [Dataset]. https://www.kaggle.com/datasets/shahriarkabir/us-data-science-and-analytics-masters-programs
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 26, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Shahriar Kabir
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    This dataset provides comprehensive information about various Data Science and Analytics master's programs offered in the United States. It includes details such as the program name, university name, annual tuition fees, program duration, location of the university, and additional information about the programs.

    Column Descriptions:

    • Subject Name: The name or field of study of the master's program, such as Data Science, Data Analytics, or Applied Biostatistics.

    • University Name: The name of the university offering the master's program.

    • Per Year Fees: The tuition fees for the program, usually given in euros per year. For some programs, the fees may be listed as "full" or "full-time," indicating a lump sum for the entire program or for full-time enrollment, respectively.

    • About Program: A brief description or overview of the master's program, providing insights into its curriculum, focus areas, and any unique features.

    • Program Duration: The duration of the master's program, typically expressed in years or months.

    • University Location: The location of the university where the program is offered, including the city and state.

    • Program Name: The official name of the master's program, often indicating its degree type (e.g., M.Sc. for Master of Science) and format (e.g., full-time, part-time, online).

  10. g

    IES, Residence and migration of all freshmen students in degree-granting...

    • geocommons.com
    Updated May 27, 2008
    + more versions
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    US Department of Education (2008). IES, Residence and migration of all freshmen students in degree-granting institutions by state, USA, 2004 [Dataset]. http://geocommons.com/search.html
    Explore at:
    Dataset updated
    May 27, 2008
    Dataset provided by
    US Department of Education
    data
    Description

    This dataset explores Residence and migration of all freshmen students in degree-granting institutions, by state: Fall 2004 NOTE: Includes all first-time postsecondary students enrolled at reporting institutions. Degree-granting institutions grant associate's or higher degrees and participate in Title IV federal financial aid programs. SOURCE: U.S. Department of Education, National Center for Education Statistics, Integrated Postsecondary Education Data System (IPEDS), Spring 2005. (This table was prepared September 2005.) http://nces.ed.gov/programs/digest/d06/tables/dt06_207.asp Accessed on 12 November 2007

  11. s

    US Private Schools

    • data.smartidf.services
    • public.opendatasoft.com
    csv, excel, geojson +1
    Updated Jul 9, 2024
    + more versions
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    (2024). US Private Schools [Dataset]. https://data.smartidf.services/explore/dataset/us-private-schools/
    Explore at:
    geojson, excel, json, csvAvailable download formats
    Dataset updated
    Jul 9, 2024
    License

    https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain

    Area covered
    United States
    Description

    This Private Schools feature dataset is composed of private elementary and secondary education facilities in the United States as defined by the Private School Survey (PSS, https://nces.ed.gov/surveys/pss/), National Center for Education Statistics (NCES, https://nces.ed.gov), US Department of Education for the 2017-2018 school year. This includes all prekindergarten through 12th grade schools as tracked by the PSS. This feature class contains all MEDS/MEDS+ as approved by NGA. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the Place Keyword section of the metadata. This release includes the addition of 2675 new records, modifications to the spatial location and/or attribution of 19836 records, the removal of 254 records no longer applicable. Additionally, 10,870 records were removed that previously had a STATUS value of 2 (Unknown; not represented in the most recent PSS data) and duplicate records identified by ORNL.

  12. U.S. Education Datasets: Unification Project

    • kaggle.com
    Updated Apr 13, 2020
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    Roy Garrard (2020). U.S. Education Datasets: Unification Project [Dataset]. https://www.kaggle.com/datasets/noriuk/us-education-datasets-unification-project/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 13, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Roy Garrard
    Area covered
    United States
    Description

    Author's Note 2019/04/20: Revisiting this project, I recently discovered the incredibly comprehensive API produced by the Urban Institute. It achieves all of the goals laid out for this dataset in wonderful detail. I recommend that users interested pay a visit to their site.

    Context

    This dataset is designed to bring together multiple facets of U.S. education data into one convenient CSV (states_all.csv).

    Contents

    • states_all.csv: The primary data file. Contains aggregates from all state-level sources in one CSV.

    • output_files/states_all_extended.csv: The contents of states_all.csv with additional data related to race and gender.

    Column Breakdown

    Identification

    • PRIMARY_KEY: A combination of the year and state name.
    • YEAR
    • STATE

    Enrollment

    A breakdown of students enrolled in schools by school year.

    • GRADES_PK: Number of students in Pre-Kindergarten education.

    • GRADES_4: Number of students in fourth grade.

    • GRADES_8: Number of students in eighth grade.

    • GRADES_12: Number of students in twelfth grade.

    • GRADES_1_8: Number of students in the first through eighth grades.

    • GRADES 9_12: Number of students in the ninth through twelfth grades.

    • GRADES_ALL: The count of all students in the state. Comparable to ENROLL in the financial data (which is the U.S. Census Bureau's estimate for students in the state).

    The extended version of states_all contains additional columns that breakdown enrollment by race and gender. For example:

    • G06_A_A: Total number of sixth grade students.

    • G06_AS_M: Number of sixth grade male students whose ethnicity was classified as "Asian".

    • G08_AS_A_READING: Average reading score of eighth grade students whose ethnicity was classified as "Asian".

    The represented races include AM (American Indian or Alaska Native), AS (Asian), HI (Hispanic/Latino), BL (Black or African American), WH (White), HP (Hawaiian Native/Pacific Islander), and TR (Two or More Races). The represented genders include M (Male) and F (Female).

    Financials

    A breakdown of states by revenue and expenditure.

    • ENROLL: The U.S. Census Bureau's count for students in the state. Should be comparable to GRADES_ALL (which is the NCES's estimate for students in the state).

    • TOTAL REVENUE: The total amount of revenue for the state.

      • FEDERAL_REVENUE
      • STATE_REVENUE
      • LOCAL_REVENUE
    • TOTAL_EXPENDITURE: The total expenditure for the state.

      • INSTRUCTION_EXPENDITURE
      • SUPPORT_SERVICES_EXPENDITURE

      • CAPITAL_OUTLAY_EXPENDITURE

      • OTHER_EXPENDITURE

    Academic Achievement

    A breakdown of student performance as assessed by the corresponding exams (math and reading, grades 4 and 8).

    • AVG_MATH_4_SCORE: The state's average score for fourth graders taking the NAEP math exam.

    • AVG_MATH_8_SCORE: The state's average score for eight graders taking the NAEP math exam.

    • AVG_READING_4_SCORE: The state's average score for fourth graders taking the NAEP reading exam.

    • AVG_READING_8_SCORE: The state's average score for eighth graders taking the NAEP reading exam.

    Data Processing

    The original sources can be found here:

    # Enrollment
    https://nces.ed.gov/ccd/stnfis.asp
    # Financials
    https://www.census.gov/programs-surveys/school-finances/data/tables.html
    # Academic Achievement
    https://www.nationsreportcard.gov/ndecore/xplore/NDE
    

    Data was aggregated using a Python program I wrote. The code (as well as additional project information) can be found [here][1].

    Methodology Notes

    • Spreadsheets for NCES enrollment data for 2014, 2011, 2010, and 2009 were modified to place key data on the same sheet, making scripting easier.

    • The column 'ENROLL' represents the U.S. Census Bureau data value (financial data), while the column 'GRADES_ALL' represents the NCES data value (demographic data). Though the two organizations correspond on this matter, these values (which are ostensibly the same) do vary. Their documentation chalks this up to differences in membership (i.e. what is and is not a fourth grade student).

    • Enrollment data from NCES has seen a number of changes across survey years. One of the more notable is that data on student gender does not appear to have been collected until 2009. The information in states_all_extended.csv reflects this.

    • NAEP test score data is only available for certain years

    • The current version of this data is concerned with state-level patterns. It is the author's hope that future versions will allow for school district-level granularity.

    Acknowledgements

    Data is sourced from the U.S. Census Bureau and the National Center for Education Statistics (NCES).

    Licensing Notes

    The licensing of these datasets state that it must not be us...

  13. t

    SCHOOL ENROLLMENT - DP02_HIL_ZIP - Dataset - CKAN

    • portal.tad3.org
    Updated Jul 23, 2023
    + more versions
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    (2023). SCHOOL ENROLLMENT - DP02_HIL_ZIP - Dataset - CKAN [Dataset]. https://portal.tad3.org/dataset/school-enrollment-dp02_hil_zip
    Explore at:
    Dataset updated
    Jul 23, 2023
    License

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

    Description

    SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES SCHOOL ENROLLMENT - DP02 Universe - Population 3 Year and over enrolled in school Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 People were classified as enrolled in school if they were attending a public or private school or college at any time during the 3 months prior to the time of interview. The question included instructions to “include only nursery or preschool, kindergarten, elementary school, home school, and schooling which leads to a high school diploma, or a college degree.” Respondents who did not answer the enrollment question were assigned the enrollment status and type of school of a person with the same age, sex, race, and Hispanic or Latino origin whose residence was in the same or nearby area.

  14. d

    Statistical Forecasting Demographic Projection Report - Enrollment...

    • catalog.data.gov
    • data.cityofnewyork.us
    • +3more
    Updated Sep 2, 2023
    + more versions
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    data.cityofnewyork.us (2023). Statistical Forecasting Demographic Projection Report - Enrollment Projections - New York City Public Schools [Dataset]. https://catalog.data.gov/dataset/statistical-forecasting-demographic-projection-report-enrollment-projections-new-york-city
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    Dataset updated
    Sep 2, 2023
    Dataset provided by
    data.cityofnewyork.us
    Area covered
    New York
    Description

    Demographic projections performed by the Statistics Forecasting for elementary, middle and high school level students.

  15. V

    Virginia’s Community Colleges Academic data of Students (2017-2021)

    • data.virginia.gov
    csv
    Updated Apr 11, 2024
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    Datathon 2024 (2024). Virginia’s Community Colleges Academic data of Students (2017-2021) [Dataset]. https://data.virginia.gov/dataset/virginia-s-community-colleges-academic-data-of-students-2017-2021
    Explore at:
    csv(11206), csv(43851)Available download formats
    Dataset updated
    Apr 11, 2024
    Dataset authored and provided by
    Datathon 2024
    Description

    This dataset provides information for Academic Years 2017-2021 which included: By College and VCCS System:

    1) Annual Headcount and FTEs 2) Gender (categories are: Female & Male; Unknown may be inferred) 3) Ethnicity (categories are: American Indian & Alaskan Native, Asian, Black & African-American, Native Hawaiian & Pacific Islander, Hispanic, Two or More Races, Unknown/Not Specified, and White) 4) Age (categories are: 17 and Under, 18-19, 20-21, 22-24, 25-29, 30-34, 35-39, 40-49, 50-64, & 65 and Over) 5) 18-Month Outcomes for Dual-Enrolled High School Grads by Year (categories are: Total Grads, Continued in any Higher Ed program, Employed with no Higher Ed, and Unknown) 6) 18-Month Outcomes for VCCS Graduates by Year (categories are: Total Grads, Continued at VCCS, Transferred to a 4yr college, Employed with no Higher Ed, and Unknown)

    For Fiscal Years 2018-2021, by Service Area and VCCS System:

    1) Fast Forward Credentialers Employed by Fiscal Year (categories are: Total Distinct Students, Employed within 6 Months, Employed within 12 Months, and Employed within 18 Months)

    Notes:

    1) Headcounts are Unduplicated student counts. 2) One FTE represents 30 credit hours of classes taken by a student over an academic year and is calculated on an annual basis by taking the total credit hours taught divided by 30. 3) 2017 Fiscal Year Fast Forward data was not included as it was considered incomplete- the Fast Forward program began in 2017 and did not encompass all areas for the entire year.
    4) In Workforce (Fast Forward data) the service region for the Richmond Metro Area is called CCWA (Community College Workforce Alliance) and combines data for Brightpoint and J Sargeant Reynolds. 4a) Therefore, there are no Reynolds data entries for Fast Forward variables. All CCWA data is listed under Brightpoint for this portion of the data set.
    5) 18-Month Outcomes for Fast Forward Credentialers are cumulative (6 months to 12 months to 18 months)

  16. T

    United States - School Enrollment, Tertiary (% Gross)

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 28, 2017
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    TRADING ECONOMICS (2017). United States - School Enrollment, Tertiary (% Gross) [Dataset]. https://tradingeconomics.com/united-states/school-enrollment-tertiary-percent-gross-wb-data.html
    Explore at:
    excel, json, csv, xmlAvailable download formats
    Dataset updated
    May 28, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    School enrollment, tertiary (% gross) in United States was reported at 79.36 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - School enrollment, tertiary (% gross) - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

  17. U

    United States US: School Enrollment: Secondary: Male: % Net

    • ceicdata.com
    Updated Feb 15, 2025
    + more versions
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    CEICdata.com (2025). United States US: School Enrollment: Secondary: Male: % Net [Dataset]. https://www.ceicdata.com/en/united-states/education-statistics/us-school-enrollment-secondary-male--net
    Explore at:
    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2004 - Dec 1, 2015
    Area covered
    United States
    Variables measured
    Education Statistics
    Description

    United States US: School Enrollment: Secondary: Male: % Net data was reported at 89.513 % in 2015. This records an increase from the previous number of 87.832 % for 2014. United States US: School Enrollment: Secondary: Male: % Net data is updated yearly, averaging 87.442 % from Dec 1987 (Median) to 2015, with 21 observations. The data reached an all-time high of 89.513 % in 2015 and a record low of 85.450 % in 2002. United States US: School Enrollment: Secondary: Male: % Net data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Education Statistics. Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Secondary education completes the provision of basic education that began at the primary level, and aims at laying the foundations for lifelong learning and human development, by offering more subject- or skill-oriented instruction using more specialized teachers.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

  18. College enrollment rate in the U.S. from by family income quartile 2000-2020...

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). College enrollment rate in the U.S. from by family income quartile 2000-2020 [Dataset]. https://www.statista.com/statistics/782387/college-enrollment-by-family-income-quartile-us/
    Explore at:
    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2020, ** percent of high school graduates from families in the lowest income quartile in the United States enrolled in college. This was a decrease of *** percent from the previous year.

  19. High School and Beyond, 1980: A Longitudinal Survey of Students in the...

    • icpsr.umich.edu
    ascii, sas, spss
    Updated Jan 12, 2006
    + more versions
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    United States Department of Education. Institute of Education Sciences. National Center for Education Statistics (2006). High School and Beyond, 1980: A Longitudinal Survey of Students in the United States [Dataset]. http://doi.org/10.3886/ICPSR07896.v2
    Explore at:
    spss, ascii, sasAvailable download formats
    Dataset updated
    Jan 12, 2006
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States Department of Education. Institute of Education Sciences. National Center for Education Statistics
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/7896/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/7896/terms

    Time period covered
    1980
    Area covered
    United States
    Description

    This data collection contains information from the first wave of High School and Beyond (HSB), a longitudinal study of American youth conducted by the National Opinion Research Center on behalf of the National Center for Education Statistics (NCES). Data were collected from 58,270 high school students (28,240 seniors and 30,030 sophomores) and 1,015 secondary schools in the spring of 1980. Many items overlap with the NCES's NATIONAL LONGITUDINAL STUDY OF THE CLASS OF 1972 (ICPSR 8085). The HSB study's data are contained in eight files. Part 1 (School Data) contains data from questionnaires completed by high school principals about various school attributes and programs. Part 2 (Student Data) contains data from surveys administered to students. Included are questionnaire responses on family and religious background, perceptions of self and others, personal values, extracurricular activities, type of high school program, and educational expectations and aspirations. Also supplied are scores on a battery of cognitive tests including vocabulary, reading, mathematics, science, writing, civics, spatial orientation, and visualization. To gather the data in Part 3 (Parent Data), a subsample of the seniors and sophomores surveyed in HSB was drawn, and questionnaires were administered to one parent of each of 3,367 sophomores and of 3,197 seniors. The questionnaires contain a number of items in common with the student questionnaires, and there are a number of items in common between the parent-of-sophomore and the parent-of-senior questionnaires. This is a revised file from the one originally released in Autumn 1981, and it includes 22 new analytically constructed variables imputed by NCES from the original survey data gathered from parents. The new data are concerned primarily with the areas of family income, liabilities, and assets. Other data in the file concentrate on financing of post-secondary education, including numerous parent opinions and projections concerning the educational future of the student, anticipated financial aid, student's plans after high school, expected ages for student's marriage and childbearing, estimated costs of post-secondary education, and government financial aid policies. Also supplied are data on family size, value of property and other assets, home financing, family income and debts, and the age, sex, marital, and employment status of parents, plus current income and expenses for the student. Part 4 (Language Data) provides information on each student who reported some non-English language experience, with data on past and current exposure to and use of languages. In Parts 5-6, there are responses from 14,103 teachers about 18,291 senior and sophomore students from 616 schools. Students were evaluated by an average of four different teachers who had the opportunity to express knowledge or opinions of HSB students whom they had taught during the 1979-1980 school year. Part 5 (Teacher Comment Data: Seniors) contains 67,053 records, and Part 6 (Teacher Comment Data: Sophomores) contains 76,560 records. Questions were asked regarding the teacher's opinions of their student's likelihood of attending college, popularity, and physical or emotional handicaps affecting school work. The sophomore file also contains questions on teacher characteristics, e.g., sex, ethnic origin, subjects taught, and time devoted to maintaining order. The data in Part 7 (Twins and Siblings Data) are from students in the HSB sample identified as twins, triplets, or other siblings. Of the 1,348 families included, 524 had twins or triplets only, 810 contained non-twin siblings only, and the remaining 14 contained both types of siblings. Finally, Part 8 (Friends Data) contained the first-, second-, and third-choice friends listed by each of the students in Part 2, along with identifying information allowing links between friendship pairs.

  20. US Department of Education College Scorecard Data

    • datalumos.org
    Updated Mar 1, 2018
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    US Department of Education (2018). US Department of Education College Scorecard Data [Dataset]. http://doi.org/10.3886/E101721V1
    Explore at:
    Dataset updated
    Mar 1, 2018
    Dataset provided by
    United States Department of Educationhttps://ed.gov/
    Authors
    US Department of Education
    License

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

    Area covered
    United States
    Description

    The College Scorecard project is designed to increase transparency, putting the power in the hands of students and families to compare how well individual postsecondary institutions are preparing their students to be successful. This project provides data to help students and families compare college costs and outcomes as they weigh the tradeoffs of different colleges, accounting for their own needs and educational goals.

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Statista (2025). College enrollment in public and private institutions in the U.S. 1965-2031 [Dataset]. https://www.statista.com/statistics/183995/us-college-enrollment-and-projections-in-public-and-private-institutions/
Organization logo

College enrollment in public and private institutions in the U.S. 1965-2031

Explore at:
84 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Mar 25, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

There were approximately 18.58 million college students in the U.S. in 2022, with around 13.49 million enrolled in public colleges and a further 5.09 million students enrolled in private colleges. The figures are projected to remain relatively constant over the next few years.

What is the most expensive college in the U.S.? The overall number of higher education institutions in the U.S. totals around 4,000, and California is the state with the most. One important factor that students – and their parents – must consider before choosing a college is cost. With annual expenses totaling almost 78,000 U.S. dollars, Harvey Mudd College in California was the most expensive college for the 2021-2022 academic year. There are three major costs of college: tuition, room, and board. The difference in on-campus and off-campus accommodation costs is often negligible, but they can change greatly depending on the college town.

The differences between public and private colleges Public colleges, also called state colleges, are mostly funded by state governments. Private colleges, on the other hand, are not funded by the government but by private donors and endowments. Typically, private institutions are  much more expensive. Public colleges tend to offer different tuition fees for students based on whether they live in-state or out-of-state, while private colleges have the same tuition cost for every student.

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