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

The Pakistani Universities Analysis project processes and visualizes data on higher education in Pakistan. It uses an ETL pipeline to extract data from Kaggle, clean and transform it in Python, and load it into a MySQL database. The data is visualized in Tableau, showing sectors (public/private), establishment trends, and distribution.
https://github.com/hanan-nawaz/pakistani_universities_analysis

csv mysql pandas python tableau vscode

Last synced: 6 months ago
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The Pakistani Universities Analysis project processes and visualizes data on higher education in Pakistan. It uses an ETL pipeline to extract data from Kaggle, clean and transform it in Python, and load it into a MySQL database. The data is visualized in Tableau, showing sectors (public/private), establishment trends, and distribution.

• Host: GitHub
• URL: https://github.com/hanan-nawaz/pakistani_universities_analysis
• Owner: Hanan-Nawaz
• License: mit
• Created: 2024-08-25T10:18:32.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2024-08-26T07:44:27.000Z (almost 2 years ago)
• Last Synced: 2025-06-09T06:03:36.557Z (about 1 year ago)
• Topics: csv, mysql, pandas, python, tableau, vscode
• Language: Python
• Homepage: https://public.tableau.com/app/profile/abdul.hanan.nawaz/viz/Pakistani_Universities_Analysis/Dashboard1?publish=yes
• Size: 51.9 MB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Support: Supporting Material/.DS_Store

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README

          
# Pakistani Universities Analysis



## Project Overview

This project involves analyzing the data of Pakistani universities, focusing on various aspects such as the sector (public/private), establishment year, and distribution across provinces. The workflow of this project includes the following steps:

1. **Data Extraction**: 

   - Downloaded the Pakistani Universities dataset from Kaggle.

   - Imported the dataset into a Python environment.

2. **Data Transformation**:

   - Cleaned the dataset by dropping null values.

   - Performed date formatting.

   - Removed unnecessary columns.

3. **Data Loading**:

   - Loaded the cleaned data into a MySQL database, which serves as Data Warehouse.

   - Created a single table in the DW to store the data.

4. **Dashboarding in Tableau**:

   - Created visualizations to explore and present the data:

     - **Sector of Universities**: Displayed a bar chart of public and private universities.

     - **Universities Established Each Year**: Showcased a bar chart illustrating the number of universities established each year.

     - **Universities Table**: Provided a comprehensive table of all universities.

     - **Universities in Each Province**: Visualized the distribution of universities across different provinces in Pakistan.

   - **[View Tableau Dashboard](https://public.tableau.com/app/profile/abdul.hanan.nawaz/viz/Pakistani_Universities_Analysis/Dashboard1)**

## Project Workflow

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

## Screenshots

1. **ETL Process**:

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

   - ![ETL Success](https://github.com/Hanan-Nawaz/Pakistani_Universities_Analysis/blob/main/Supporting%20Material/terminal_image.png)

2. **Data Loading Confirmation**:

   - Screenshot of MySQL terminal showing `SELECT * FROM Uni_list LIMIT 10` query result, confirming data load.

   - ![MySQL Data Loaded](https://github.com/Hanan-Nawaz/Pakistani_Universities_Analysis/blob/main/Supporting%20Material/db.png)

2. **Tableau Dashboard**:

   - Screenshot of Tableau Dashboard.

   - ![Tableau Dashboard](https://github.com/Hanan-Nawaz/Pakistani_Universities_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 ETL script.

4. Import the Tableau dashboard to explore the visualizations.

## Technologies Used

- **Python** for data extraction and transformation.

- **MySQL** (as the Data Warehouse) for data storage.

- **Tableau** for data visualization.

## License

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