https://github.com/ryanbbrown/ut-grades-dashboard
https://github.com/ryanbbrown/ut-grades-dashboard
Last synced: 24 days ago
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- Host: GitHub
- URL: https://github.com/ryanbbrown/ut-grades-dashboard
- Owner: ryanbbrown
- Created: 2025-10-25T14:29:26.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2025-10-26T19:13:27.000Z (8 months ago)
- Last Synced: 2025-10-26T21:09:36.099Z (8 months ago)
- Language: HTML
- Size: 1.28 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# UT Austin Historical Course Grades Dashboard
An interactive dashboard for exploring historical grade distributions across courses at the University of Texas at Austin. Built using Altair. Live interactive dashboard [here](https://ryanbbrown.com/files/ut-grades-dashboard.html).
## Overview
This project processes 750,000+ grade records spanning 32 semesters (2010-2022) and creates an interactive, progressive Altair dashboard that allows users to:
- **Explore grade distributions by college and department** - Interactive scatterplot showing average grades across different course prefixes
- **Compare individual courses** - Filter by prefix to see specific courses with grade vs. enrollment trends
- **View detailed grade breakdowns** - Bar chart showing the full letter grade distribution for any selected course
Altair interactive charts are exported as html files; the data is embedded directly in the html, which makes the file large + slow with large datasets. To improve efficiency, the data for this dashboard is instead stored in a public Cloudflare R2 bucket and referenced by url in the html.
Note that this project was completed in May 2022 but only locally; this repo is just a quick cleanup + upload of the project.
## Installation + Usage
### Install
```bash
# Clone the repository
git clone
cd ut-grades-dashboard
# Install dependencies
uv sync
```
### Full Run
This will:
1. Process the raw data and create aggregated datasets
2. Generate the interactive dashboard at `output/ut-grades-dashboard.html`
```bash
uv run main.py
```
### Run Options
```bash
python main.py --help
Options:
--prepare-only # Only run data preparation step
--visualize-only # Only run visualization step (requires processed data to be present already)
--download-raw # Download the raw data to data/raw from public Cloudflare R2 buckets
--upload-processed # Upload processed datasets to S3-compatible storage; requires .env file
```