I recently explored PyGWalker, a Python library designed to enhance data analysis and visualization workflows within Jupyter Notebooks. PyGWalker, playfully pronounced like "Pig Walker," serves as a Python binding of Graphic Walker, an open-source alternative to visualization tools like Tableau. This integration allows for a more interactive data exploration experience directly within a notebook environment.
As I learn more about data analysis I find that the initial exploration of the dataset is very important. Therefore I am always looking for libraries that can help me better understand the dataset that I am working with.
As they say: "Garbage in Garbage out"
I came across a medium artikel and explored the combination of Streamlit and PygWalker a bit. The code examples are copied form the medium artikel and the PygWalker github repo.
Overall interesting library. I try it out at work today for sure. I will stick with the Jupiter Notebook application for now. It look like a good tool to add to the initial data exploration toolkit.