Datawaza streamlines common Data Science tasks. It's a collection of tools for data exploration, visualization, data cleaning, pipeline creation, hyper-parameter searching, model iteration, and evaluation. It builds upon core libraries like Pandas, Matplotlib, Seaborn, Scikit-Learn, TensorFlow, and PyTorch.

Open Source Library

You can find the Datawaza repo on Github, and the latest release on PyPi. The user guide is a Jupyter notebook that walks through how to use the Datawaza functions. It's probably the best place to start.

What is Waza?

Waza (技) means "technique" in Japanese. In martial arts like Aikido, it is paired with words like "suwari-waza" (sitting techniques) or "kaeshi-waza" (reversal techniques). So we've paired it with "data" to represent Data Science techniques: データ技 "data-waza".