Above is the fastest way to know what my team did 😃
The Why
Picking the right college is one of the most stressful decisions a high school student faces. Data is scattered across dozens of websites — rankings, acceptance rates, tuition, campus life — and comparing schools side-by-side requires hours of manual research. We wanted to change that by aggregating everything into one place and surfacing insights through visualizations.
The What
College Helper scrapes, cleans, and analyses college data so students can make more informed decisions. Key features:
- Web Scraping — Automated data collection from multiple college listing sites using Selenium and BeautifulSoup
- Data Cleaning & Analysis — Processed raw data with Pandas and NumPy to produce consistent, comparable metrics across schools
- Visualisations — Generated charts and graphs with Matplotlib to highlight trends in acceptance rates, tuition costs, and more
- Search & Filter — Allowed users to filter schools by criteria such as location, major, acceptance rate, and cost
Team
Built by Yifan Cheng, Skylar Du, Yashash Gaurav (Me), and Mark He — a CMU Data Focused Python (DFP) project.