https://github.com/hanan-nawaz/numl_faculty_analysis

This project analyzes faculty data from NUML's CS and SE departments, comparing the number of faculty, designations (e.g., Lecturers, Assistant and Associate Professors), and PhD qualifications. It also includes a detailed list of all faculty members with their designations, departments, and contact information.
https://github.com/hanan-nawaz/numl_faculty_analysis

csv dataengineering etl-pipeline python sql tableau-dashboards webscraping

Last synced: 12 months ago
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This project analyzes faculty data from NUML's CS and SE departments, comparing the number of faculty, designations (e.g., Lecturers, Assistant and Associate Professors), and PhD qualifications. It also includes a detailed list of all faculty members with their designations, departments, and contact information.

• Host: GitHub
• URL: https://github.com/hanan-nawaz/numl_faculty_analysis
• Owner: Hanan-Nawaz
• License: mit
• Created: 2024-08-28T08:04:21.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-12-03T09:29:49.000Z (over 1 year ago)
• Last Synced: 2025-01-26T15:33:40.995Z (about 1 year ago)
• Topics: csv, dataengineering, etl-pipeline, python, sql, tableau-dashboards, webscraping
• Language: Python
• Homepage: https://www.hanannawaz.me
• Size: 51.8 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Support: Supporting Material/.DS_Store

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README

          
# NUML Faculty Analysis



    



## Project Overview

This project involves analyzing the faculty data of NUML's Department of Computer Science (CS) and Department of Software Engineering (SE). The analysis focuses on comparing faculty members across various aspects such as:

- The number of faculty members in each department.

- Designation-wise comparison (e.g., Associate Professors, Assistant Professors, and Lecturers).

- PhD qualification comparison.

- Comprehensive list of all faculty members with their designations, department, and contact information.

The workflow of this project includes the following steps:

1. **Data Collection**:

   - Scraped faculty data from the NUML website for both CS and SE departments.

   - Organized data into a structured format.

2. **Data Transformation**:

   - Cleaned and formatted the data (e.g., handling missing fields, standardizing designations).

   - Categorized faculty members by their designations and departments.

3. **Data Analysis**:

   - Performed comparisons between the CS and SE departments on:

     - Total number of faculty members.

     - Designation distribution (Lecturers, Assistant Professors, Associate Professors).

     - Number of PhD-qualified faculty members.

4. **Visualization**:

   - Created visualizations to illustrate:

     - Faculty distribution in CS and SE departments.

     - Designation-wise comparison.

     - PhD qualification comparison.

     - List of all faculty members with their designations, departments, and contact details, color-coded as follows:

       - **Red**: Lecturer

       - **Yellow**: Associate Professor

       - **Orange**: Assistant Professor

## Project Workflow

![Workflow](https://github.com/Hanan-Nawaz/NUML_Faculty_Analysis/blob/main/Supporting%20Material/workflow.png)

## Screenshots

1. **ETL Process**:

   - Screenshot of VS Code terminal with "ETL Performed Successfully" message.

   - ![Cleaned Data](https://github.com/Hanan-Nawaz/NUML_Faculty_Analysis/blob/main/Supporting%20Material/termianl_extraction.png)

2. **Analysis Visualizations**:

   - Screenshot of Tableau Dashboard.

   - ![Faculty Distribution](https://github.com/Hanan-Nawaz/NUML_Faculty_Analysis/blob/main/Supporting%20Material/dashboard.png)

## Getting Started

To reproduce this project, follow these steps:

1. Clone the repository.

2. Install the required Python libraries.

3. Execute the data scraping and transformation script.

4. View the analysis and visualizations.

## Technologies Used

- **Python** for data scraping, transformation, and analysis.

- **Tableau** for creating visualizations.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.