Using the US College Scorecard, we seek to provide insights to students on their long-term prospects based off of their choice of schools. Using R, we perform analysis on the last 15 years of college scorecard data. We then encapsulate what we learned in the EDA phase into the ShinyDebt app, using R's Shiny framework for web applications.
The application source code.
Some cleaned data, as well as the publicly distributed College Scoreboard report.
R and Python notebooks where EDA snippets are included, showing relationships capitalized on in the ShinyDebt app.
Results of exploratory data analysis.
Quick EDA scripts.
@mackenziedg, @SJCaldwell, @Beau, and @Saad worked together on the EDA, data cleaning, variable creation, and shiny app development.