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This tool features a user-friendly GUI for validating datasets by calculating statistics for each attribute. Users receive analysis results and can define acceptable values for their data, enhancing data quality and ensuring accurate handling across various applications.

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KevinGarrison/PythonDataValidationTool

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Installing Dependencies from requirements.txt

Prerequisites

  • Ensure you have Python installed. You can download it from python.org.
  • Ensure you have pip installed. It usually comes with Python, but you can check by running:
    python -m pip --version

Installation Steps

  1. Navigate to the Project Directory Open a terminal or command prompt and navigate to the directory where requirements.txt is located:

    cd /path/to/project
  2. Create a Virtual Environment (Optional but Recommended) It's best practice to install dependencies in a virtual environment to avoid conflicts:

    python -m venv venv

    Activate the virtual environment:

    • On Windows:
      venv\Scripts\activate
    • On macOS/Linux:
      source venv/bin/activate
  3. Install Dependencies Run the following command to install all dependencies listed in requirements.txt:

    pip install -r requirements.txt
  4. Verify Installation To check if the dependencies were installed correctly, run:

    pip list

Troubleshooting

  • If you encounter permission issues, try running:
    pip install --user -r requirements.txt
  • If installation fails due to outdated pip, upgrade it with:
    pip install --upgrade pip

Deactivating the Virtual Environment

If you used a virtual environment, you can deactivate it by running:

 deactivate

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This tool features a user-friendly GUI for validating datasets by calculating statistics for each attribute. Users receive analysis results and can define acceptable values for their data, enhancing data quality and ensuring accurate handling across various applications.

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