This package changes how Pandas and Polars DataFrames are rendered in Python notebooks and applications. With itables you can display your tables as interactive DataTables that you can sort, paginate, scroll or filter.

ITables is just about how tables are displayed. You can turn it on and off in just two lines, with no other impact on your data workflow.

Since v2.6.0, ITables has no dependencies. It works out of the box with Pandas or Polars in Jupyter, Dash, Streamlit, or Marimo--you only need these packages installed. The Jupyter Widget is the sole exception, requiring anywidget. With Narwhals installed, ITables can also display DataFrames from other libraries like cuDF, Modin or PyArrow.

Browse the documentation to see examples of Pandas or Polars DataFrames rendered as interactive DataTables.

Install the itables package with either

or

Activate the interactive mode for all series and dataframes in Jupyter with

and then render any DataFrame as an interactive table that you can sort, search and explore:

If you prefer to render only selected DataFrames as interactive tables, call itables.init_notebook_mode(all_interactive=False), then use itables.show to show just one Series or DataFrame as an interactive table:

ITables works in all the usual Jupyter Notebook environments, including Jupyter Notebook, Jupyter Lab, Jupyter nbconvert (i.e. the tables are still interactive in the HTML export of a notebook), Jupyter Book, Google Colab and Kaggle.

You can also use ITables in Quarto HTML documents, and in RISE presentations.

ITables works well in VS Code, both in Jupyter Notebooks and in interactive Python sessions.

ITables is also available as

• a Jupyter Widget
• a Dash component
• a Streamlit component,
• and it also works in Shiny applications.

ITables is developed by Marc Wouts on GitHub, under an MIT license.

ITables is a wrapper for datatables.net which is developed by Allan Jardine (sponsor him!), also under an MIT license.