Matplotlib Jupyter Extension

0.10.0 · active · verified Sat Apr 11

ipympl is a Matplotlib Jupyter Extension that leverages the Jupyter interactive widgets framework to enable interactive features of Matplotlib within Jupyter Notebooks, JupyterLab, Google Colab, and VSCode notebooks. It provides a proper Jupyter interactive widget for figure canvases, allowing them to be positioned in interactive widget layouts. The library is actively maintained with regular releases, currently at version 0.10.0.

Warnings

breaking For JupyterLab versions 1 or 2, `ipympl` requires manual installation of the `jupyter-matplotlib` labextension and specific version compatibility. For JupyterLab >= 3, installation via pip/conda is usually sufficient as the extension is automatically handled. Ensure your `ipympl` and `jupyter-matplotlib` versions are compatible.
Fix: Upgrade to JupyterLab 3+ or refer to the official ipympl documentation's 'Compatibility Table' for specific `jupyter-matplotlib` versions required for older JupyterLab installations. For older JupyterLab versions, e.g., `conda install -c conda-forge nodejs jupyter labextension install @jupyter-widgets/jupyterlab-manager jupyter-matplotlib` might be needed.
gotcha ipympl comprises both a Python (backend) and a JavaScript (frontend) component. In certain complex environments (e.g., custom Jupyter deployments, mixing environments), a version mismatch between these components can lead to non-interactive plots or errors. Always ensure both frontend and backend are from the same installation environment.
Fix: Verify that `pip list` or `conda list` shows `ipympl` in your active kernel's environment. If issues persist, check the browser's developer console for JavaScript errors related to Jupyter widgets.
gotcha When using `ipympl` in Google Colab, you must explicitly enable the custom widget manager before activating the Matplotlib backend, otherwise plots will not be interactive.
Fix: Add `from google.colab import output; output.enable_custom_widget_manager()` at the beginning of your Colab notebook, before `%matplotlib ipympl`.

Install

pip install ipympl PyPI
conda install -c conda-forge ipympl Conda

Imports

%matplotlib ipympl
```
%matplotlib ipympl
```
ipympl is activated via a Jupyter magic command, not a direct Python import. '%matplotlib widget' also works.

Quickstart

This quickstart demonstrates how to activate the ipympl backend using the Jupyter magic command and create a basic interactive Matplotlib plot. Run this code in a Jupyter Notebook or JupyterLab environment to see the interactive features.

import matplotlib.pyplot as plt
import numpy as np

%matplotlib ipympl

fig, ax = plt.subplots()
x = np.linspace(0, 2 * np.pi, 100)
y = np.sin(3 * x)
ax.plot(x, y)
plt.show()

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