plotly/plotly.py
An open-source, interactive graphing library for Python (includes Plotly Express) :sparkles:
repo name | plotly/plotly.py |
repo link | https://github.com/plotly/plotly.py |
homepage | https://plot.ly/python/ |
language | Python |
size (curr.) | 112667 kB |
stars (curr.) | 6181 |
created | 2013-11-21 |
license | MIT License |
plotly.py
Quickstart
pip install plotly==4.5.4
Inside Jupyter notebook (installable with pip install "notebook>=5.3" "ipywidgets>=7.2"
):
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
Overview
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 hosted online using Chart Studio Cloud.
Contact us for consulting, dashboard development, application integration, and feature additions.
- Online Documentation
- Contributing
- Changelog
- Code of Conduct
- Version 4 Migration Guide
- New! Announcing Dash 1.0
- Community
Installation
plotly.py may be installed using pip…
pip install plotly==4.5.4
or conda.
conda install -c plotly plotly=4.5.4
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"
JupyterLab Support (Python 3.5+)
For use in JupyterLab, install the jupyterlab
and ipywidgets
packages using pip…
pip install jupyterlab==1.2 "ipywidgets==7.5"
or conda.
conda install jupyterlab=1.2
conda install "ipywidgets=7.5"
Then run the following commands to install the required JupyterLab extensions (note that this will require node
to be installed):
# Avoid "JavaScript heap out of memory" errors during extension installation
# (OS X/Linux)
export NODE_OPTIONS=--max-old-space-size=4096
# (Windows)
set NODE_OPTIONS=--max-old-space-size=4096
# Jupyter widgets extension
jupyter labextension install @jupyter-widgets/jupyterlab-manager@1.1 --no-build
# FigureWidget support
jupyter labextension install plotlywidget@1.5.4 --no-build
# and jupyterlab renderer support
jupyter labextension install jupyterlab-plotly@1.5.4 --no-build
# Build extensions (must be done to activate extensions since --no-build is used above)
jupyter lab build
# Unset NODE_OPTIONS environment variable
# (OS X/Linux)
unset NODE_OPTIONS
# (Windows)
set NODE_OPTIONS=
Static Image Export
plotly.py supports static image export using the to_image
and write_image
functions in the plotly.io
package. This functionality requires the
installation of the plotly orca command line utility and the
psutil
Python package.
These dependencies can both be installed using conda:
conda install -c plotly plotly-orca psutil
Or, psutil
can be installed using pip…
pip install psutil
and orca can be installed according to the instructions in the orca README.
Troubleshooting
Wrong Executable found
If you get an error message stating that the orca
executable that was found is not valid, this may be because another executable with the same name was found on your system. Please specify the complete path to the Plotly-Orca binary that you downloaded (for instance in the Miniconda folder) with the following command:
plotly.io.orca.config.executable = '/home/your_name/miniconda3/bin/orca'
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
Chart Studio support
The chart-studio
package 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==1.0.0
or conda
conda install -c plotly chart-studio=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.