The interactive graphing library for Python (includes Plotly Express) :sparkles:
Our recommended IDE for Plotly’s Python graphing library is Dash Enterprise’s Data Science Workspaces, which has both Jupyter notebook and Python code file support.
pip install plotly==4.14.3
Inside Jupyter (installable with
pip install "jupyterlab>=3" "ipywidgets>=7.6"):
import plotly.graph_objects as go fig = go.Figure() fig.add_trace(go.Scatter(y=[2, 1, 4, 3])) fig.add_trace(go.Bar(y=[1, 4, 3, 2])) fig.update_layout(title = 'Hello Figure') fig.show()
See the Python documentation for more examples.
Read about what's new in plotly.py v4
plotly.py is an interactive, open-source, and browser-based graphing library for Python :sparkles:
Built on top of plotly.js,
plotly.pyis 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.pyis MIT Licensed. Plotly graphs can be viewed in Jupyter notebooks, standalone HTML files, or hosted online using Chart Studio Cloud.
Contact us for consulting, dashboard development, application integration, and feature additions.
plotly.py may be installed using pip...
pip install plotly==4.14.3
conda install -c plotly plotly=4.14.3
For use in JupyterLab, install the
pip install jupyterlab>=3 "ipywidgets>=7.6"
conda install jupyterlab>=3 "ipywidgets>=7.6"
# Basic JupyterLab renderer support jupyter labextension install [email protected]
OPTIONAL: Jupyter widgets extension for FigureWidget support
jupyter labextension install @jupyter-widgets/jupyterlab-manager [email protected]
Please check out our Troubleshooting guide if you run into any problems with JupyterLab.
For use in the Jupyter Notebook, install the
pip install "notebook>=5.3" "ipywidgets>=7.5"
conda install "notebook>=5.3" "ipywidgets>=7.5"
plotly.py supports static image export, using either the
plotlyversion 4.9) or the orca command line utility (legacy as of
$ 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
These dependencies can both be installed using conda:
conda install -c plotly plotly-orca==1.3.1 psutil
psutilcan be installed using pip...
pip install psutil
and orca can be installed according to the instructions in the orca README.
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-geopackage. This package can be installed using pip...
pip install plotly-geo==1.0.0
conda install -c plotly plotly-geo=1.0.0
chart-studiopackage can be used to upload plotly figures to Plotly's Chart Studio Cloud or On-Prem service. This package can be installed using pip...
pip install chart-studio==1.1.0
conda install -c plotly chart-studio=1.1.0
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
Code and documentation copyright 2019 Plotly, Inc.
Code released under the MIT license.
Docs released under the Creative Commons license.