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An open-source, interactive data visualization library for Python

Project description

plotly.py

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Quickstart

pip install plotly

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 :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.



Installation

plotly.py may be installed using pip

pip install plotly

or conda.

conda install -c plotly plotly

Jupyter Widget Support

For use as a Jupyter widget, install jupyter and anywidget packages using pip:

pip install jupyter anywidget

or conda:

conda install jupyter anywidget

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

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

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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