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utm-department-analysis

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rmp data ranking

// repository documentation

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# UTM Department Data Analysis (Demo Only)

This project demonstrates how to analyze and visualize rating data using Bayesian averaging, based on data that was collected from publicly available pages on [RateMyProfessors](https://www.ratemyprofessors.com/).  
Only analysis logic and example plots are retained for educational purposes.

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## Project Structure

- `system_class.py`:  
  Defines core classes including `University`, `Department`, `ProfData`, and `CourseUnderProf`.

- `analysis.py`:  
  Contains statistical functions and Bayesian scoring logic, as well as plotting utilities.

- `main.py`:  
  Main script to run analysis and generate plots (no longer includes any scraping or data fetching).

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## Current Status

- Code for analysis, Bayesian ranking, and visualization
- Sample output plots generated from previously available data (shown below)

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## Sample Visualizations

These plots are **examples** only, based on previously generated data that has now been removed:

![Difficulty Ranking Chart](https://raw.githubusercontent.com/Jackymn25/utm-professor-analysis-rmp/main/plots/pic_2.png)

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## Usage (With Your Own Data)

If you have your own JSON-formatted professor data (not provided here), you can place it in the `data/` directory:

- The expected filename is `all_prof_data.json`
- Run the main script:

First set up environment

```bash
pip install -r requirements.txt

```bash
python main.py

utm-department-analysis

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