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https://mwouts.github.io/itables/

Pandas DataFrames as Interactive DataTables
https://mwouts.github.io/itables/

datatables jupyter pandas polars python quarto shiny visual-studio-code

Last synced: 2 months ago
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Pandas DataFrames as Interactive DataTables

Host: GitHub
URL: https://mwouts.github.io/itables/
Owner: mwouts
License: mit
Created: 2019-04-15T22:09:44.000Z (about 5 years ago)
Default Branch: main
Last Pushed: 2024-05-05T23:13:49.000Z (2 months ago)
Last Synced: 2024-05-06T00:23:32.133Z (2 months ago)
Topics: datatables, jupyter, pandas, polars, python, quarto, shiny, visual-studio-code
Language: Jupyter Notebook
Homepage: https://mwouts.github.io/itables/
Size: 24.9 MB
Stars: 673
Watchers: 11
Forks: 51
Open Issues: 25
Metadata Files:
- Readme: README.md
- Contributing: docs/contributing.md
- License: LICENSE
- Support: docs/supported_editors.md

Lists

awesome-python - mwouts.github.io/itables
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README

        ![ITables Logo](itables/logo/wide.svg)

![CI](https://github.com/mwouts/itables/actions/workflows/continuous-integration.yml/badge.svg?branch=main)

[![codecov.io](https://codecov.io/github/mwouts/itables/coverage.svg?branch=main)](https://codecov.io/github/mwouts/itables?branch=main)

[![Pypi](https://img.shields.io/pypi/v/itables.svg)](https://pypi.python.org/pypi/itables)

[![Conda Version](https://img.shields.io/conda/vn/conda-forge/itables.svg)](https://anaconda.org/conda-forge/itables)

[![pyversions](https://img.shields.io/pypi/pyversions/itables.svg)](https://pypi.python.org/pypi/itables)

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

This packages changes how Pandas and Polars DataFrames are rendered in Jupyter Notebooks.

With `itables` you can display your tables as interactive [DataTables](https://datatables.net/)

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.

The `itables` package only depends on `numpy`, `pandas` and `IPython`

which you must already have if you work with Pandas in Jupyter (add `polars`, `pyarrow` if you

work with Polars DataFrames).

## Documentation

Browse the [documentation](https://mwouts.github.io/itables/) to see

examples of Pandas or Polars DataFrames rendered as interactive DataTables.

## Quick start

Install the `itables` package with either

```shell

pip install itables

```

or

```shell

conda install itables -c conda-forge

```

Activate the interactive mode for all series and dataframes with

```python

from itables import init_notebook_mode

init_notebook_mode(all_interactive=True)

```

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

![df](docs/df_example.png)

If you prefer to render only selected DataFrames as interactive tables, use `itables.show` to show just one Series or DataFrame as an interactive table:

![show](docs/show_df.png)

Since `itables==1.0.0`, the [jQuery](https://jquery.com/) and [DataTables](https://datatables.net/) libraries and CSS

are injected in the notebook when you execute `init_notebook_mode` with its default argument `connected=False`.

Thanks to this the interactive tables will work even without a connection to the internet.

If you prefer to load the libraries dynamically (and keep the notebook lighter), use `connected=True` when you

execute `init_notebook_mode`.

## Supported environments

`itables` has been tested in the following editors:

- Jupyter Notebook

- Jupyter Lab

- Jupyter nbconvert (i.e. the tables are still interactive in the HTML export of a notebook)

- Jupyter Book

- Google Colab

- VS Code (for both Jupyter Notebooks and Python scripts)

- PyCharm (for Jupyter Notebooks)

- Quarto

- Shiny for Python