ipyregulartable

Efficiently handles massive datasets, demonstrated with examples up to two billion rows, making it ideal for large-scale data exploration in Jupyter notebooks.

Supports in-place cell editing with event handling, enabling real-time data manipulation directly within notebooks, as shown in the edit events example.

Allows extensive CSS-based styling and theming, providing flexibility to match specific visual requirements for reports or dashboards, evidenced in the styling notebook.

Seamlessly works with Pandas Series and DataFrames, including pivot table visualizations, enhancing data analysis workflows without extra conversion steps.