ipychart

A Jupyter - Chart.js bridge enabling interactive data visualization in the Jupyter notebook.


Keywords
ipython, jupyter, widgets, chartjs, data-visualization, ipywidgets, javascript, jupyter-notebook, jupyter-notebook-extension, python
License
MIT
Install
pip install ipychart==0.2.2

Documentation


The power of Chart.js in Jupyter Notebooks

GitHub GitHub release (latest by date) Binder Awesome Chart.js

Installation

You can install ipychart from your terminal using pip or conda:

# using pip
$ pip install ipychart

# using conda
$ conda install -c conda-forge ipychart

Documentation

Usage

Create charts with Python in a very similar way to creating charts using Chart.js (create a bar chart using Chart.js). The charts created are fully configurable, interactive and modular and are displayed directly in the output of the the cells of your jupyter notebook environment:

Development Installation

For a development installation:

$ git clone https://github.com/nicohlr/ipychart.git
$ cd ipychart
$ conda install jupyterlab nodejs -c conda-forge
$ cd ipychart/js
$ npm install 
$ cd .. 
$ pip install -e .
$ jupyter nbextension install --py --symlink --sys-prefix ipychart
$ jupyter nbextension enable --py --sys-prefix ipychart

References

License

Ipychart is available under the MIT license.