bqplot
2-D plotting library for Project Jupyter
Introduction
bqplot is a 2-D visualization system for Jupyter, based on the constructs of the Grammar of Graphics.
Usage
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.
Goals
- 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:
Dependencies
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)numpypandas
Installation
Using pip:
$ pip install bqplot
Using conda
$ conda install -c conda-forge bqplot
To enable bqplot for JupyterLab version 1 or 2 (not needed for JupyterLab 3.0):
$ jupyter labextension install @jupyter-widgets/jupyterlab-manager bqplot
For a development installation (requires npm (version >= 3.8) and node (version >= 4.0)):
$ 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
yarn run build
Then refreshing the JupyterLab/Jupyter Notebook is enough to reload the changes.
Loading bqplot
# In a Jupyter notebook
import bqplot
That's it! You're ready to go!
Examples
Using the pyplot API
Using the bqplot internal object model
Documentation
To get started with using bqplot, check out the full documentation
https://bqplot.readthedocs.io/
Install a previous bqplot version (Only for JupyterLab <= 2)
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:
back-end (Python) |
front-end (JavaScript) |
|---|---|
| 0.12.14 | 0.5.14 |
| 0.12.13 | 0.5.13 |
| 0.12.12 | 0.5.12 |
| 0.12.11 | 0.5.11 |
| 0.12.10 | 0.5.10 |
| 0.12.9 | 0.5.9 |
| 0.12.8 | 0.5.8 |
| 0.12.7 | 0.5.7 |
| 0.12.6 | 0.5.6 |
| 0.12.4 | 0.5.4 |
| 0.12.3 | 0.5.3 |
| 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 |
Development
See our contributing guidelines to know how to contribute and set up a development environment.
License
This software is licensed under the Apache 2.0 license. See the LICENSE file for details.
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