https://github.com/tameronline/htmlpro

https://github.com/tameronline/htmlpro

Last synced: about 8 hours ago
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• Host: GitHub
• URL: https://github.com/tameronline/htmlpro
• Owner: TamerOnLine
• License: other
• Created: 2024-10-24T13:39:42.000Z (23 days ago)
• Default Branch: main
• Last Pushed: 2024-10-24T13:42:21.000Z (23 days ago)
• Last Synced: 2024-10-25T16:29:18.787Z (21 days ago)
• Language: HTML
• Size: 193 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Security: SECURITY.md

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README

        
 

# Project Name

## Description

This project provides a clear and concise solution for a real-world problem involving efficient data processing and analysis using Python. It is built using popular libraries such as Pandas, NumPy, and Matplotlib, focusing on performance, scalability, and ease of use.

## Features

- **Data Loading**: Load datasets from various formats like CSV, Excel, or SQL databases efficiently.

- **Data Cleaning**: Perform comprehensive data cleaning operations, including handling missing values, data normalization, and feature engineering.

- **Data Visualization**: Create insightful visualizations using Matplotlib and Seaborn for data analysis and reporting.

- **Modular Design**: The project follows a modular design approach, making it easy to extend and integrate with other systems.

- **Unit Testing**: Built-in unit tests for all functions ensure code reliability and robustness.

## Installation

To get started with this project, follow these steps:

1. **Clone the repository**:

   \`\`\`bash

   git clone https://github.com/yourusername/repository_name.git

   cd repository_name

   \`\`\`

2. **Set up a virtual environment**:

   On Windows:

   \`\`\`bash

   python -m venv env

   env\Scripts\ctivate

   \`\`\`

   On Linux or macOS:

   \`\`\`bash

   python3 -m venv env

   source env/bin/activate

   \`\`\`

3. **Install dependencies**:

   \`\`\`bash

   pip install -r requirements.txt

   \`\`\`

4. **Run the application**:

   \`\`\`bash

   python main.py

   \`\`\`

5. **Run unit tests**:

   \`\`\`bash

   python -m unittest discover

   \`\`\`

## Usage

After installation, you can use this project by running the \`main.py\` file, which will initiate the data pipeline, performing data cleaning, analysis, and visualizations. Modify the configurations in the \`config.py\` file to customize the dataset or operations.

Example usage:

\`\`\`bash

python main.py --input data/input_file.csv --output results/output_file.csv

\`\`\`

## Contributing

If you'd like to contribute to this project, please follow these steps:

1. Fork the repository.

2. Create a new branch (\`git checkout -b feature_branch\`).

3. Make your changes and commit them (\`git commit -m 'Add new feature'\`).

4. Push to the branch (\`git push origin feature_branch\`).

5. Open a pull request.

## License

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

## Contact

For any questions or feedback, feel free to reach out to \`[email protected]\`.