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Matplotlib Jupyter Integration

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matplotlib/ipympl

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Test StatusLatest PyPI versionLatest conda-forge versionLatest npm versionBinderGitter

Leveraging the Jupyter interactive widgets framework,ipympl enables the interactive features of matplotlib in the Jupyter notebook and in JupyterLab.

Besides, the figurecanvas element is a proper Jupyter interactive widget which can be positioned in interactive widget layouts.

Usage

To enable theipympl backend, simply use thematplotlib Jupytermagic:

%matplotlib ipympl

Documentation

See the documentation at:https://matplotlib.org/ipympl/

Example

See theexample notebook for more!

matplotlib screencast

Installation

With conda:

conda install -c conda-forge ipympl

With pip:

pip install ipympl

Use in JupyterLab

If you want to use ipympl in JupyterLab, we recommend using JupyterLab >= 3.

If you use JupyterLab 2, you still need to install the labextension manually:

conda install -c conda-forge nodejsjupyter labextension install @jupyter-widgets/jupyterlab-manager jupyter-matplotlib

Install an old JupyterLab extension

If you are using JupyterLab 1 or 2, you will need to install the rightjupyter-matplotlib version, according to theipympl andjupyterlab versions you installed.For example, if you installed ipympl0.5.1, you need to install jupyter-matplotlib0.7.0, and this version is only compatible with JupyterLab1.

conda install -c conda-forge ipympl==0.5.1jupyter labextension install @jupyter-widgets/jupyterlab-manager jupyter-matplotlib@0.7.0

Versions lookup table:

ipympljupyter-matplotlibJupyterLabMatplotlib
0.9.5-70.11.5-7>=2,<5>=3.5.0
0.9.3-40.11.3-4>=2,<53.4.0>=
0.9.0-20.11.0-2>=2,<53.4.0>= <3.7
0.8.80.10.x>=2,<53.3.1>= <3.7
0.8.0-70.10.x>=2,<53.3.1>=, <3.6
0.7.00.9.0>=2,<53.3.1>=
0.6.x0.8.x>=2,<53.3.1>=, <3.4
0.5.80.7.4>=1,<33.3.1>=, <3.4
0.5.70.7.3>=1,<33.2.*
.........
0.5.30.7.2>=1,<3
0.5.20.7.1>=1,<2
0.5.10.7.0>=1,<2
0.5.00.6.0>=1,<2
0.4.00.5.0>=1,<2
0.3.30.4.2>=1,<2
0.3.20.4.1>=1,<2
0.3.10.4.0>=0<2

For a development installation (requires nodejs):

Create a dev environment that has nodejs installed. The instructions here usemamba but youcan also use conda.

mamba env create --file dev-environment.ymlconda activate ipympl-dev

Install the Python Packge

pip install -e.

When developing your extensions, you need to manually enable your extensions with thenotebook / lab frontend. For lab, this is done by the command:

jupyter labextension develop --overwrite.jlpm build

For classic notebook, you need to run:

jupyter nbextension install --py --symlink --sys-prefix --overwrite ipympljupyter nbextensionenable --py --sys-prefix ipympl

How to see your changes

Typescript:

If you use JupyterLab to develop then you can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the widget.

# Watch the source directory in one terminal, automatically rebuilding when neededjlpm watch# Run JupyterLab in another terminaljupyter lab

After a change wait for the build to finish and then refresh your browser and the changes should take effect.

Python:

If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.


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