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](https://collegescorecard.ed.gov/data/). 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](https://www.kaggle.com/benhamner/d/kaggle/college-scorecard/exploring-the-us-college-scorecard-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](https://collegescorecard.ed.gov/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](https://www.datacamp.com/courses/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.*