With PyGWalker, you can create dynamic dashboards and reports right within your Jupyter Notebook, all while harnessing the user-friendly features reminiscent of Tableau’s visual analytics platform and  interface. Say hello to an intuitive and efficient workflow as you explore and communicate your data-driven stories with the ease and flexibility that PyGWalker provides.

A look at the project

1. Create interactive visualisations: Learn how to use PyGWalker’s capabilities to create interactive visualisations. Understand different chart types and customisation options, and learn how to create compelling visual representations of your data.
2. Build dynamic dashboards and reports: Discover how to assemble interactive dashboards and reports within PyGWalker. Learn how to combine multiple visualisations, add interactivity, and effectively present your data-driven insights.
3. Perform advanced data manipulation and transformation: Explore advanced data manipulation and transformation techniques using PyGWalker. Learn how to handle missing data, perform calculations, and apply complex data transformations within the PyGWalker environment.
4. Collaborate and share: Understand how to collaborate with others using PyGWalker. Learn how to share notebooks and dashboards, export visualisations, and effectively communicate your findings to stakeholders.

What you’ll need