A powerful Python package for data imputation, designed to handle missing values in scientific datasets efficiently and accurately.
- Advanced imputation algorithms
- User-friendly GUI interface
- Support for various data formats
- Interactive Jupyter notebook integration
- Google Colab compatibility
We recommend using Anaconda for local installation:
# Clone the repository
git clone https://github.com/TheDecodeLab/python-imputation.git
cd python-imputation
# Create and activate conda environment
conda env create -f environment.yml
conda activate impute
# Install the package
python setup.py install
# Run the application
pympute 8501For a quick start with the GUI interface, you can use Google Colab and the sample data here :
Detailed usage instructions and examples can be found in the notebooks directory.
If you use Pympute in your research, please cite our work:
@article{pympute,
title={Pympute: Flexible imputation toolkit for electronic health records},
authors={Alireza Vafaei Sadr, Jiang Li, Wenke Hwang, Mohammed Yeasin, Ming Wang, Harold Lehmann, Ramin Zand, Vida Abedi},
journal={Scientific Repotrs},
year={2025},
DOI={10.1038/s41598-025-02276-5}
}Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.
For questions and support, please open an issue on GitHub or contact the maintainers.