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.

A curated dataset of Ivy League admissions metrics by class year and institution, including overall acceptance rate, Regular Decision acceptance rate, Early Decision/Action acceptance rate, % of class filled by early applicants, and application volumes.

This dataset includes various information like GRE score, TOEFL score, university rating, SOP (Statement of Purpose), LOR (Letter of Recommendation), CGPA, research and chance of admit. In this dataset, 400 entries are included.

GRE Scores ( out of 340 ) TOEFL Scores ( out of 120 ) University Rating ( out of 5 ) Statement of Purpose (SOP) and Letter of Recommendation (LOR) Strength ( out of 5 ) Undergraduate GPA ( out of 10 ) Research Experience ( either 0 or 1 ) Chance of Admit ( ranging from 0 to 1 ).

Ivy League universities are known to be incredibly selective in their admissions processes. Harvard University's acceptance rate for the Class of 2028 (students beginning university in the fall of 2024) was the most selective, with a **** percent acceptance rate, followed by Yale University with a *** percent acceptance rate.

This repository contains datasets and analysis code accompanying the paper "An Empirical Evaluation of Chinese College Admissions Reforms Through A Natural Experiment" by Chen, Jiang, and Kesten. The datasets contain the college admission data for a county in China's Sichuan Province for year 2008 and 2009. These include students' submitted rank-ordered lists of colleges and admission results. All variables are recoded to remove any identifiable information (including college and high school code). The analysis code can be used to replicate the tables and figures in the paper.

As of February 1, ********* applications were submitted to the most selective higher education institutions, who admit less than 25 percent of their applicants, during the 2023/24 academic year in the United States. In comparison, only ******* applications had been submitted to highly selective institutions who admit between 25 and 49 percent of their applicants.

College admissions is a competitive game. Few schools are as competitive as Yale University. Located in New Haven, CT, Yale College's most recent acceptance rate was in the low single digits. This raises two questions: How many applicants will be admitted going forward? What does it take to get into Yale?

This starter data set is a compilation of data made public by Yale's Office of Institutional Research. While the data are well suited to answering the first of our two research questions, additional variables are required to offer a credible answer to the second. Additional data are, thus, welcome.

In the academic year of 2023/24, around 21 million students were enrolled for undergraduate degrees in the United States. This was a slight increase from the previous year, when 20.6 million students were enrolled as undergraduates.

Dataset

This dataset was created by Varada Gupta

Released under MIT

Contents

The data here is from the report entitled Trends in Enrollment, Credit Attainment, and Remediation at Connecticut Public Universities and Community Colleges: Results from P20WIN for the High School Graduating Classes of 2010 through 2016. The report answers three questions: 1. Enrollment: What percentage of the graduating class enrolled in a Connecticut public university or community college (UCONN, the four Connecticut State Universities, and 12 Connecticut community colleges) within 16 months of graduation? 2. Credit Attainment: What percentage of those who enrolled in a Connecticut public university or community college within 16 months of graduation earned at least one year’s worth of credits (24 or more) within two years of enrollment? 3. Remediation: What percentage of those who enrolled in one of the four Connecticut State Universities or one of the 12 community colleges within 16 months of graduation took a remedial course within two years of enrollment? Notes on the data: School Credit: % Earning 24 Credits is a subset of the % Enrolled in 16 Months. School Remediation: % Enrolled in Remediation is a subset of the % Enrolled in 16 Months.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1556959%2F013e17fd6630de18102315b20ebba89b%2FSimulated%20College%20Headcount%20Data%20CODEBOOK.jpg?generation=1687210619889162&alt=media" alt="">

Context

There's a story behind every dataset and here's your opportunity to share yours.

Content

What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too.

Acknowledgements

We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

College Completion Dataset

Graduation Rates, Race, Efficiency Measures and More

By Jonathan Ortiz [source]

About this dataset

This College Completion dataset provides an invaluable insight into the success and progress of college students in the United States. It contains graduation rates, race and other data to offer a comprehensive view of college completion in America. The data is sourced from two primary sources – the National Center for Education Statistics (NCES)’ Integrated Postsecondary Education System (IPEDS) and Voluntary System of Accountability’s Student Success and Progress rate.

At four-year institutions, the graduation figures come from IPEDS for first-time, full-time degree seeking students at the undergraduate level, who entered college six years earlier at four-year institutions or three years earlier at two-year institutions. Furthermore, colleges report how many students completed their program within 100 percent and 150 percent of normal time which corresponds with graduation within four years or six year respectively. Students reported as being of two or more races are included in totals but not shown separately

When analyzing race and ethnicity data NCES have classified student demographics since 2009 into seven categories; White non-Hispanic; Black non Hispanic; American Indian/ Alaskan native ; Asian/ Pacific Islander ; Unknown race or ethnicity ; Non resident with two new categorize Native Hawaiian or Other Pacific Islander combined with Asian plus students belonging to several races. Also worth noting is that different classifications for graduate data stemming from 2008 could be due to variations in time frame examined & groupings used by particular colleges – those who can’t be identified from National Student Clearinghouse records won’t be subjected to penalty by these locations .

When it comes down to efficiency measures parameters like “Awards per 100 Full Time Undergraduate Students which includes all undergraduate completions reported by a particular institution including associate degrees & certificates less than 4 year programme will assist us here while we also take into consideration measures like expenditure categories , Pell grant percentage , endowment values , average student aid amounts & full time faculty members contributing outstandingly towards instructional research / public service initiatives .

When trying to quantify outcomes back up Median Estimated SAT score metric helps us when it is derived either on 25th percentile basis / 75th percentile basis with all these factors further qualified by identifying required criteria meeting 90% threshold when incoming students are considered for relevance . Last but not least , Average Student Aid equalizes amount granted by institution dividing same over total sum received against what was allotted that particular year .

All this analysis gives an opportunity get a holistic overview about performance , potential deficits &

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset contains data on student success, graduation rates, race and gender demographics, an efficiency measure to compare colleges across states and more. It is a great source of information to help you better understand college completion and student success in the United States.

In this guide we’ll explain how to use the data so that you can find out the best colleges for students with certain characteristics or focus on your target completion rate. We’ll also provide some useful tips for getting the most out of this dataset when seeking guidance on which institutions offer the highest graduation rates or have a good reputation for success in terms of completing programs within normal timeframes.

Before getting into specifics about interpreting this dataset, it is important that you understand that each row represents information about a particular institution – such as its state affiliation, level (two-year vs four-year), control (public vs private), name and website. Each column contains various demographic information such as rate of awarding degrees compared to other institutions in its sector; race/ethnicity Makeup; full-time faculty percentage; median SAT score among first-time students; awards/grants comparison versus national average/state average - all applicable depending on institution location — and more!

When using this dataset, our suggestion is that you begin by forming a hypothesis or research question concerning student completion at a given school based upon observable characteristics like financ...

This dataset offers a comprehensive overview of student enrollment across various academic programs, integrating a wide range of variables related to personal demographics, academic performance, and macroeconomic indicators. It includes attributes such as marital status, application mode, and age at enrollment, providing valuable insights into student diversity and application preferences.

The dataset further explores educational backgrounds, encompassing prior academic qualifications and parental education levels, which may influence students’ academic trajectories. Additional features such as attendance preferences, nationality, and special needs status contribute to a nuanced understanding of the student population.

Academic data is detailed through curricular units from both the first and second semesters, capturing information on credits, evaluation outcomes, approvals, and grades. Moreover, the inclusion of economic indicators—such as the unemployment rate, inflation rate, and GDP—enables analysis of potential correlations between economic conditions and educational outcomes.

A key component of the dataset is the 'Target' variable, which serves as the focal point for predictive modeling or classification tasks. This label may represent student success, dropout risk, or another critical educational outcome, offering significant value for researchers and data analysts.

Overall, this dataset supports in-depth exploration of the multifaceted relationship between student attributes, academic performance, and broader socio-economic contexts.

Montgomery College Student Enrollment Data Update Frequency: Annually

This dataset presents student information from a General Degree College, where subjects are selected according to high school performance. Included are categories, gender, year of passing, marks for the first choice subject, the first choice subject itself, marks for the second choice subject, and subsequent choices. 📊 Ideal for in-depth data analysis in Excel, this dataset offers insights into academic preferences and trends. Let's dive in and craft a compelling dashboard to unlock its full potential! 🚀

This dataset captures detailed enrollment information for Montgomery College students during the Fall term.

It includes demographics (gender, race, ethnicity, age group), academic program descriptions, campus attendance (Germantown, Rockville, Takoma Park), high school background, and geographic details such as city, county, state, and ZIP code.

Each row represents an individual student record, reflecting their educational path and location preferences.

From a data science or analytics perspective, various analyses can be performed:

• Trend Analysis: Track changes in student demographics or program enrollments over different Fall terms.
• Segmentation: Group students by age, race, status (full-time/part-time), or location to tailor interventions.
• Program Popularity: Determine which academic programs are most attractive to different student types.
• Geospatial Mapping: Use ZIP and city data to visualize student distribution and commuting patterns.

Overview

This comprehensive dataset provides detailed information on over 1,000 U.S. higher education institutions, combining admissions data, standardized test scores, tuition information, and student socioeconomic demographics. The dataset merges data from three sources: U.S. Department of Education's College Scorecard that was uploaded on April 23, 2025, Harvard's Opportunity Insights elite colleges and universities admissions paper, and Top 100 rankings for 2025 from U.S. News & World Report.

College and University Inclusion

The U.S. Department of Education's College Scorecard has data from over 6,400 colleges and universities across 3,306 features. Colleges and universities were included if the following values were not missing:

1. SAT average scores
2. Admissions rate
3. In-state tuition
4. Out-state tuition

Dataset Structure

Data type: Tabular Dimensions: 1,070 rows (institutions) x 37 variables

As of 2022, the average acceptance rate for four-year, not-for-profit colleges in the United States was ** percent, meaning these schools offered admission to ** percent of first-year applicants on average. In comparison, the average acceptance rate for public colleges was higher, at ** percent, while the acceptance rate for private colleges averaged only around ** percent.