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Plotting library for IPython/Jupyter notebooks
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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.


Wealth of Nations

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 simple lines of Python code.


  • provide a unified framework for 2-D visualizations with a pythonic API.
  • provide a sensible API for adding user interactions (panning, zooming, selection, etc)

Two APIs are provided

  • Users can build custom visualizations using the internal object model, which is inspired by the constructs of the Grammar of Graphics (figure, marks, axes, scales), and enrich their visualization with our Interaction Layer.
  • Or they can use the context-based API similar to Matplotlib's pyplot, which provides sensible default choices for most parameters.

Trying it online

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

To enable bqplot with Jupyter lab:

$ jupyter labextension install bqplot

For a development installation (requires npm (version >= 3.8) and node (version >= 4.0)):

$ git clone
$ cd bqplot
$ pip install -e .
$ jupyter nbextension install --py --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 bqplot
$ jupyter labextension install @jupyter-widgets/jupyterlab-manager # install the Jupyter widgets extension
$ jupyter labextension install bqplot

Loading bqplot

# In a Jupyter notebook
import bqplot

That's it! You're ready to go!


Using the pyplot API

Pyplot Screenshot

Using the bqplot internal object model

Bqplot Screenshot


To get started with using bqplot, check out the full documentation

Install a previous bqplot version

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 bqplot@0.4.9

Versions lookup table:

back-end (Python) front-end (JavaScript)
0.12.2 0.5.2
0.12.1 0.5.1
0.12.0 0.5.0
0.11.9 0.4.9
0.11.8 0.4.8
0.11.7 0.4.7
0.11.6 0.4.6
0.11.5 0.4.5
0.11.4 0.4.5
0.11.3 0.4.4
0.11.2 0.4.3
0.11.1 0.4.1
0.11.0 0.4.0
0.10.5 0.3.6
0.10.4 0.3.5
0.10.3 0.3.3
0.10.2 0.3.2
0.10.1 0.3.1
0.10.0 0.3.0
0.9.1 0.3.0beta
0.9.0 0.2.3


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

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