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

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


To enable the ipympl backend, simply use the matplotlib Jupyter magic:

%matplotlib widget


See the example notebook for more!

matplotlib screencast


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 nodejs
jupyter 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 right jupyter-matplotlib version, according to the ipympl and jupyterlab versions you installed. For example, if you installed ipympl 0.5.1, you need to install jupyter-matplotlib 0.7.0, and this version is only compatible with JupyterLab 1.

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

Versions lookup table:

ipympl jupyter-matplotlib JupyterLab Matplotlib
0.5.8 0.7.4 1 or 2 3.3.1
0.5.7 0.7.3 1 or 2 3.2.*
... ... ...
0.5.3 0.7.2 1 or 2
0.5.2 0.7.1 1
0.5.1 0.7.0 1
0.5.0 0.6.0 1
0.4.0 0.5.0 1
0.3.3 0.4.2 1
0.3.2 0.4.1 1
0.3.1 0.4.0 0 or 1

For a development installation (requires nodejs):

Create a dev environment that has nodejs installed. The instructions here use mamba but you can also use conda.

mamba env create --file dev-environment.yml
conda activate ipympl-dev

Install the Python Packge

pip install -e .

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

jupyter labextension develop --overwrite .
npm run build

For classic notebook, you need to run:

jupyter nbextension install --py --symlink --sys-prefix ipympl
jupyter nbextension enable --py --sys-prefix ipympl

How to see your changes


You need to rebuild the JS when you make a code change:

cd js
yarn run watch

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


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