Table of Contents
Mwenkit is library created to house boilerplate code for different stages of a data science project lifecycle. The stages include data cleaning & wrangling, visualization, feature selection, hypothesis testing, modeling, evaluation and testing.
This is an example of how to list things you need to use the software and how to install them.
- npm
- Install PyPI package
pip install mwenkit
from mwenkit.<module_name> import <function_name>
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Run pylint mwenkit
- Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the MIT License. See LICENSE.txt for more information.
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