bqplot 0.12.45
Interactive plotting for the Jupyter notebook, using d3.js and ipywidgets.
License: Apache
Requires Python: >=3.6
Keywords: ipython, jupyter, widgets, graphics, plotting, d3

# bqplot

[![Travis](https://travis-ci.com/bqplot/bqplot.svg?branch=master)](https://travis-ci.com/bqplot/bqplot)
[![Documentation](https://readthedocs.org/projects/bqplot/badge/?version=latest)](http://bqplot.readthedocs.org)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/bqplot/bqplot/stable?filepath=examples/Index.ipynb)
[![Chat](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/jupyter-widgets/Lobby)

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)](https://github.com/bqplot/bqplot/blob/master/examples/Applications/Wealth%20Of%20Nations/Bubble%20Chart.ipynb)

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.

## 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

- `Object Model`, which
  is inspired by the constructs of the Grammar of Graphics (figure, marks, axes,
  scales). This API is verbose but is fully customizable
- `pyplot`, which is a context-based API similar to Matplotlib's pyplot. `pyplot` 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)](https://mybinder.org/v2/gh/bqplot/bqplot/stable?filepath=examples/Index.ipynb)

### 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
```

##### Development installation

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.

##### Running tests

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

```bash
    conda env update -f test-environment.yml
```

And run it with for Python tests:

```bash
    pytest
```

And `cd js` to run the JS tests with:

```bash
yarn run test
```

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

```bash
yarn run build
```

## Examples

### Using the `pyplot` API

[![Pyplot Screenshot](/pyplot.png)](https://github.com/bqplot/bqplot/blob/master/examples/Basic%20Plotting/Pyplot.ipynb)

### Using the `Object Model` API

[![Bqplot Screenshot](/bqplot.png)](https://github.com/bqplot/bqplot/blob/master/examples/Advanced%20Plotting/Advanced%20Plotting.ipynb)

## Documentation

Full documentation is available at 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 bqplot@0.4.9
```

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.