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The interactive graphing library for Python (includes Plotly Express) :sparkles:

Home Page: https://plotly.com/python/

License: MIT License

Shell 0.01% Python 76.29% JavaScript 22.83% Batchfile 0.01% PostScript 0.86% TypeScript 0.02% CSS 0.01%

plotly.py's Introduction

plotly.py

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License

Quickstart

pip install plotly==4.8.2

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 โœจ

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.



Installation

plotly.py may be installed using pip...

pip install plotly==4.8.2

or conda.

conda install -c plotly plotly=4.8.2

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 "ipywidgets==7.5"

or conda.

conda install jupyterlab "ipywidgets=7.5"

Then run the following commands to install the required JupyterLab extensions (note that this will require node to be installed):

# 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.

Static Image Export with Kaleido

plotly.py supports static image export using the to_image and write_image functions in the plotly.io module. This functionality requires the kaleido package which can be installed using pip...

$ pip install -U kaleido

or conda.

$ conda install -c plotly python-kaleido

Static Image Export with Orca

While Kaleido is now the recommended image export approach because it is easier to install and more widely compatible, 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.

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.

plotly.py's People

Contributors

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