2-D plotting library for Project Jupyter

bqplot is a 2-D visualization system for Jupyter, based on the constructs of the Grammar of Graphics.

In bqplot, every component of a plot is an interactive widget. This allows the user to integrate visualizations with other Jupyter interactive widgets to create integrated GUIs with a few lines of Python code.

You can follow the documentation on https://bqplot.github.io/bqplot

To try out bqplot interactively in your web browser, just click on the binder link:

This package depends on the following packages:

• ipywidgets (version >=7.0.0, <8.0)
• traitlets (version >=4.3.0, <5.0)
• traittypes (Version >=0.2.1, <0.3)
• numpy
• pandas

Using pip:

$ pip install bqplot

Using conda

$ conda install -c conda-forge bqplot

If you are using JupyterLab <=2:

$ jupyter labextension install @jupyter-widgets/jupyterlab-manager bqplot

For a development installation (requires JupyterLab (version >= 4) and yarn):

$ git clone https://github.com/bqplot/bqplot.git
$ cd bqplot
$ pip install -e .
$ jupyter nbextension install --py --overwrite --symlink --sys-prefix bqplot
$ jupyter nbextension enable --py --sys-prefix bqplot

Note for developers: the --symlink argument on Linux or OS X allows one to modify the JavaScript code in-place. This feature is not available with Windows.

For the experimental JupyterLab extension, install the Python package, make sure the Jupyter widgets extension is installed, and install the bqplot extension:

$ pip install "ipywidgets>=7.6"
$ jupyter labextension develop . --overwrite

Whenever you make a change of the JavaScript code, you will need to rebuild:

cd js
jlpm run build

Then refreshing the JupyterLab/Jupyter Notebook is enough to reload the changes.

You can install the dependencies necessary to run the tests with:

    conda env update -f test-environment.yml

And run it with for Python tests:

    pytest

And cd js to run the JS tests with:

jlpm run test

Every time you make a change on your tests it's necessary to rebuild the JS side:

jlpm run build

In order to install a previous bqplot version, you need to know which front-end version (JavaScript) matches with the back-end version (Python).

For example, in order to install bqplot 0.11.9, you need the labextension version 0.4.9.

$ pip install bqplot==0.11.9
$ jupyter labextension install [email protected]

Versions lookup table:

See our contributing guidelines to know how to contribute and set up a development environment.

This software is licensed under the Apache 2.0 license. See the LICENSE file for details.