An open-source, interactive data visualization library for Python
pip install plotly==5.15.0
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.
plotly.py is an interactive, open-source, and browser-based graphing library for Python :sparkles:
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
- Code of Conduct
- Version 4 Migration Guide
- New! Announcing Dash 1.0
- Community forum
plotly.py may be installed using pip...
pip install plotly==5.15.0
conda install -c plotly plotly=5.15.0
For use in JupyterLab, install the
pip install "jupyterlab>=3" "ipywidgets>=7.6"
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@example.com @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
pip install "notebook>=5.3" "ipywidgets>=7.5"
conda install "notebook>=5.3" "ipywidgets>=7.5"
Static Image Export
plotly.py supports static image export,
using either the
package (recommended, supported as of
plotly version 4.9) or the orca
command line utility (legacy as of
plotly version 4.9).
kaleido package has no dependencies and can be installed
pip install -U kaleido
conda install -c conda-forge python-kaleido
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
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
plotly-geo package. This package can be installed using pip...
pip install plotly-geo==1.0.0
conda install -c plotly plotly-geo=1.0.0
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.
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