An interactive data visualization exploring how Big Ten universities differ in the fields of study from which they graduate students. The project presents:
- A within-institution degree-output profile (treemap)
- A cross-institution comparison of degree shares for a selected field
Built for Love Data Week 2026 using publicly available IPEDS data.
The interactive visualization is hosted via GitHub Pages:
➡️ View the live project
https://joelswenddal.github.io/love-data-2026/
This project answers a simple but powerful question:
How do Big Ten universities differ in what they teach?
Rather than ranking institutions by raw counts, the visualization emphasizes composition:
- What share of an institution’s degrees fall into each broad field of study?
- How does that share compare across institutions for a single CIP2 area?
The project uses CIP2 fields of study (two-digit Classification of Instructional Programs codes) to provide a high-level, comparable view across universities.
├── css/
│ └── styles.css # Application styling
│
├── js/
│ └── app.js # Main visualization logic (Plotly + UI state)
│
├── data/
│ ├── raw/
│ │ └── ipeds/
│ │ └── Big10_CIP2_2024_20251227.xlsx # Original IPEDS extract
│ │
│ ├── processed/
│ │ └── ipeds/
│ │ ├── big10_cip2_2024_treemap.csv # Processed CSV
│ │ └── big10_cip2_2024_treemap.json # JSON used by the web app
│ │
│ └── sample-data-set.json # Small sample dataset for testing
│
├── scripts/
│ └── final_build_research_bigten.ipynb # Data processing & build notebook
│
├── requirements.txt # Python dependencies
├── index.html # Application entry point
├── README.md # Project documentation
├── .gitignore
└── app_event_flow_js.png # Event-flow / interaction diagram
- IPEDS Completions Survey
- Academic Year 2023–2024
IPEDS Data Center → Custom Data Files download tool https://nces.ed.gov/ipeds/use-the-data
- Data retrieved from IPEDS aggregated at CIP2 level as CSV and opened in Excel file
- Python cleaning to create user-friendly names and grouping variables (eg. 'Degree Group'). Filtered to Award levels in focus.
- Exported to CSV and JSON formats
- JSON consumed directly by the web application
- All data preparation steps are documented in the Jupyter notebook located in /scripts/.
- Each tile represents a CIP2 field of study
- Tile area is proportional to degree completions under the current filters
- Percentages reflect share of total completions for that institution
- Displays the share of completions in a selected CIP2 field
- Each bar represents:
(CIP2 completions) ÷ (total completions)
- Filters (Major, Degree group, Award level) are applied consistently across institutions
- This chart is intended for relative comparison, not raw counts
- Major 1 (Primary)
- Major 2
- All (combined)
- Bachelors
- Graduate
- All
- Award-level detail within the selected Degree group
- “All” reflects all included awards for that group
- Doctoral awards are limited to Research/Scholarship classifications
- Colors are mapped deterministically by CIP2 code for consistency across sessions (Color does not imply ranking or magnitude.)
- The comparison chart shows shares, not counts (Use hover tooltips for numerator and denominator values.)
- Counts may differ slightly from institution-published figures due to:
- Reporting windows
- Classification updates
- IPEDS data revisions
- Non-CIP-mapped awards are excluded by design
- The processed data files used by the visualization are available in the repository
- The full source code for the web application is included in this repository
- The project is designed to be fully reproducible using the included notebook
This visualization was created by Joel Swenddal in a personal capacity as a staff submission for Love Data Week 2026.
Although the author is a staff member at the University of Illinois Urbana-Champaign, the content does not represent the views of UIUC, the Big Ten Conference, or any affiliated institution.
Questions or feedback may be directed to the author.
This project uses publicly available data and is shared for educational and research purposes.