bqplot
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)numpy
pandas
Installation
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 >= 3) 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
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 |