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Programming language: TypeScript
License: Apache License 2.0
Latest version: v0.12.19

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README

bqplot

Travis Documentation Binder Chat

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

[Wealth of Nations](./wealth-of-nations.gif)

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:

[Binder](docs/source/binder-logo.svg)

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

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 https://github.com/bqplot/bqplot.git
$ 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!

Examples

Using the pyplot API

Pyplot Screenshot

Using the bqplot internal object model

Bqplot Screenshot

Documentation

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

https://bqplot.readthedocs.io/

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 [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](CONTRIBUTING.md) 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](LICENSE) file for details.


*Note that all licence references and agreements mentioned in the bqplot README section above are relevant to that project's source code only.