Welcome to the DataTransformationChecker repository! This Python-based utility is designed to help you test and visualize data transformations with ease. Whether you are working on normality tests, transformation methods, or visual analysis tools, this tool has got you covered.
- Normality Tests: Includes Shapiro-Wilk and Lilliefors tests to check the normality of your data.
- Transformation Methods: Offers a variety of transformation methods such as Box-Cox and Yeo-Johnson transformations.
- Visual Analysis Tools: Visualize your data through histogram and Q-Q plots for better understanding.
- Clone the repository to your local machine.
- Install the required dependencies.
- Load your dataset into the tool.
- Choose the transformation method you want to apply.
- Run the tests and visualize the results.
Download the application here.
- box-cox-transformation
- data
- datatransformation
- kolmogorov-smirnov
- lillie-test
- normalization
- shapiro-wilk
- spss
- transformation
- yeo-johnson-transformations
- Fork the repository.
- Check the Releases section for the latest updates.
- Start exploring the powerful data transformation capabilities.
- Check out the official documentation for detailed instructions.
- Visit our website for tutorials and FAQs.
For any queries or issues, please raise a GitHub issue. Our team will assist you promptly.
We welcome contributions from the community. Feel free to submit pull requests or suggest new features.
This project is licensed under the MIT License - see the LICENSE file for details.
Explore the world of data transformations with the DataTransformationChecker tool. Transform your data with confidence and achieve meaningful insights effortlessly. Download the application now! 🚀📈