NOTE

This is a fork of Plotly modified for use in Mode's native Python notebook environment.

To test work on Mode's fork of Plotly you will need to do the following:

1. ensure these Mode services are running:

• Jiffypop: https://github.com/mode/go-mono/tree/master/jiffypop
• Python 3 runtime: https://github.com/mode/runtime-images/tree/master/runtime-python3
• The following services in the JVM mono repo: https://github.com/mode/jvm-mono
  • DirectConnect
  • Credguard
  • Flamingo
  • Zookeeper

2. After saving changes to the Plotly repo, if your local Python3 Docker container is running stop and restart it:

• Restart the container with ./runtime-python3/bin/run-runtime-python3-image-0 in the runtime-images directory

3. Execute this command within the plotly.py directory to apply your changes to the Python runtime: docker cp ./packages/python/plotly/. $(docker container ps --filter name=runtime-python3 -q):/opt/conda/envs/python3/lib/python3.6/site-packages/

4. Click "Restart" in the web application notebook.

5. Verify you're running your local version of Plotly by executing this code in the notebook, which should print out '0+unknown':

import plotly
plotly.__version__

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plotly.py

Latest Release
User forum
PyPI Downloads
License

Quickstart

pip install plotly==5.24.1

Inside Jupyter (installable with pip install "jupyterlab>=3" "ipywidgets>=7.6"):

import plotly.express as px
fig = px.bar(x=["a", "b", "c"], y=[1, 3, 2])
fig.show()

See the Python documentation for more examples.

Overview

plotly.py is an interactive, open-source, and browser-based graphing library for Python ✨

Built on top of plotly.js, plotly.py is a high-level, declarative charting library. plotly.js ships with over 30 chart types, including scientific charts, 3D graphs, statistical charts, SVG maps, financial charts, and more.

plotly.py is MIT Licensed. Plotly graphs can be viewed in Jupyter notebooks, standalone HTML files, or integrated into Dash applications.

Contact us for consulting, dashboard development, application integration, and feature additions.

---

• Online Documentation
• Contributing to plotly
• Changelog
• Code of Conduct
• Version 4 Migration Guide
• New! Announcing Dash 1.0
• Community forum

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Installation

plotly.py may be installed using pip...

pip install plotly==5.24.1

or conda.

conda install -c plotly plotly=5.24.1

JupyterLab Support

For use in JupyterLab, install the jupyterlab and ipywidgets packages using pip:

pip install "jupyterlab>=3" "ipywidgets>=7.6"

or conda:

conda install "jupyterlab>=3" "ipywidgets>=7.6"

The instructions above apply to JupyterLab 3.x. For JupyterLab 2 or earlier, run the following commands to install the required JupyterLab extensions (note that this will require node to be installed):

# JupyterLab 2.x renderer support
jupyter labextension install [email protected] @jupyter-widgets/jupyterlab-manager

Please check out our Troubleshooting guide if you run into any problems with JupyterLab.

Jupyter Notebook Support

For use in the Jupyter Notebook, install the notebook and ipywidgets packages using pip:

pip install "notebook>=5.3" "ipywidgets>=7.5"

or conda:

conda install "notebook>=5.3" "ipywidgets>=7.5"

Static Image Export

plotly.py supports static image export, using either the kaleido package (recommended, supported as of plotly version 4.9) or the orca command line utility (legacy as of plotly version 4.9).

Kaleido

The kaleido package has no dependencies and can be installed using pip...

pip install -U kaleido

or conda.

conda install -c conda-forge python-kaleido

Orca

While Kaleido is now the recommended image export approach because it is easier to install and more widely compatible, static image export can also be supported by the legacy orca command line utility and the psutil Python package.

These dependencies can both be installed using conda:

conda install -c plotly plotly-orca==1.3.1 psutil

Or, psutil can be installed using pip...

pip install psutil

and orca can be installed according to the instructions in the orca README.

Extended Geo Support

Some plotly.py features rely on fairly large geographic shape files. The county choropleth figure factory is one such example. These shape files are distributed as a separate plotly-geo package. This package can be installed using pip...

pip install plotly-geo==1.0.0

or conda

conda install -c plotly plotly-geo=1.0.0

Migration

If you're migrating from plotly.py v3 to v4, please check out the Version 4 migration guide

If you're migrating from plotly.py v2 to v3, please check out the Version 3 migration guide

Copyright and Licenses

Code and documentation copyright 2019 Plotly, Inc.

Code released under the MIT license.

Docs released under the Creative Commons license.