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plotly.py

Latest Release
User forum
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License

Quickstart

pip install plotly==4.10.0

Inside Jupyter notebook (installable with pip install "notebook>=5.3" "ipywidgets>=7.2"):

importplotly.graph_objectsasgofig=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 ✨

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==4.10.0

or conda.

conda install -c plotly plotly=4.10.0

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 jupyterlab-plotly@4.10.0
# OPTIONAL: Jupyter widgets extension for FigureWidget support
jupyter labextension install @jupyter-widgets/jupyterlab-manager plotlywidget@4.10.0

Please check out our Troubleshooting guide if you run into any problems with JupyterLab.

Static Image Export

plotly.py supports static image export, using the 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 plotly python-kaleido

Orca

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

Or, 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 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.

About

The interactive graphing library for Python (includes Plotly Express) ✨

plotly.com/python/

Resources

Readme
MIT license

Code of conduct

Code of conduct

Contributing

Contributing
Activity

Stars

0 stars

Watchers

0 watching

Forks

0 forks
Report repository

Releases

Packages

Contributors

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GitHub - rysktky/plotly.py: The interactive graphing library for Python (includes Plotly Express) :sparkles: · GitHub
Skip to content
BranchesTags
Repository files navigation
plotly.py
Latest Release
User forum
PyPI Downloads
License
Quickstart
pip install plotly==4.10.0
Inside Jupyter notebook (installable with pip install "notebook>=5.3" "ipywidgets>=7.2"):
importplotly.graph_objectsasgofig=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 ✨
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==4.10.0

or conda.
conda install -c plotly plotly=4.10.0

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 jupyterlab-plotly@4.10.0
# OPTIONAL: Jupyter widgets extension for FigureWidget support
jupyter labextension install @jupyter-widgets/jupyterlab-manager plotlywidget@4.10.0

Please check out our Troubleshooting guide if you run into any problems with JupyterLab.
Static Image Export
plotly.py supports static image export,
using the 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 plotly python-kaleido

Orca
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

Or, 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
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.
About
The interactive graphing library for Python (includes Plotly Express) ✨
plotly.com/python/
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
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try {
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var __re = new RegExp('^' + ".*" + '
GitHub - rysktky/plotly.py: The interactive graphing library for Python (includes Plotly Express) :sparkles: · GitHub
Skip to content
BranchesTags
Repository files navigation
plotly.py
Latest Release
User forum
PyPI Downloads
License
Quickstart
pip install plotly==4.10.0
Inside Jupyter notebook (installable with pip install "notebook>=5.3" "ipywidgets>=7.2"):
importplotly.graph_objectsasgofig=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 ✨
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==4.10.0

or conda.
conda install -c plotly plotly=4.10.0

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 jupyterlab-plotly@4.10.0
# OPTIONAL: Jupyter widgets extension for FigureWidget support
jupyter labextension install @jupyter-widgets/jupyterlab-manager plotlywidget@4.10.0

Please check out our Troubleshooting guide if you run into any problems with JupyterLab.
Static Image Export
plotly.py supports static image export,
using the 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 plotly python-kaleido

Orca
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

Or, 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
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.
About
The interactive graphing library for Python (includes Plotly Express) ✨
plotly.com/python/
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Highlight search terms from Google/DuckDuckGo/Bing referrer
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var ref = document.referrer;
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(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - rysktky/plotly.py: The interactive graphing library for Python (includes Plotly Express) :sparkles: · GitHub
Skip to content
BranchesTags
Repository files navigation
plotly.py
Latest Release
User forum
PyPI Downloads
License
Quickstart
pip install plotly==4.10.0
Inside Jupyter notebook (installable with pip install "notebook>=5.3" "ipywidgets>=7.2"):
importplotly.graph_objectsasgofig=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 ✨
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==4.10.0

or conda.
conda install -c plotly plotly=4.10.0

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 jupyterlab-plotly@4.10.0
# OPTIONAL: Jupyter widgets extension for FigureWidget support
jupyter labextension install @jupyter-widgets/jupyterlab-manager plotlywidget@4.10.0

Please check out our Troubleshooting guide if you run into any problems with JupyterLab.
Static Image Export
plotly.py supports static image export,
using the 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 plotly python-kaleido

Orca
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

Or, 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
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.
About
The interactive graphing library for Python (includes Plotly Express) ✨
plotly.com/python/
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
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})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
GitHub - rysktky/plotly.py: The interactive graphing library for Python (includes Plotly Express) :sparkles: · GitHub
Skip to content
BranchesTags
Repository files navigation
plotly.py
Latest Release
User forum
PyPI Downloads
License
Quickstart
pip install plotly==4.10.0
Inside Jupyter notebook (installable with pip install "notebook>=5.3" "ipywidgets>=7.2"):
importplotly.graph_objectsasgofig=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 ✨
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==4.10.0

or conda.
conda install -c plotly plotly=4.10.0

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 jupyterlab-plotly@4.10.0
# OPTIONAL: Jupyter widgets extension for FigureWidget support
jupyter labextension install @jupyter-widgets/jupyterlab-manager plotlywidget@4.10.0

Please check out our Troubleshooting guide if you run into any problems with JupyterLab.
Static Image Export
plotly.py supports static image export,
using the 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 plotly python-kaleido

Orca
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

Or, 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
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.
About
The interactive graphing library for Python (includes Plotly Express) ✨
plotly.com/python/
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
}
}
// Try immediately
tryTheater();
// Try after navigation (SPA)
var lastUrl = location.href;
setInterval(function() {
if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
}
}, 1000);
// Also try on player load
var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - rysktky/plotly.py: The interactive graphing library for Python (includes Plotly Express) :sparkles: · GitHub
Skip to content
BranchesTags
Repository files navigation
plotly.py
Latest Release
User forum
PyPI Downloads
License
Quickstart
pip install plotly==4.10.0
Inside Jupyter notebook (installable with pip install "notebook>=5.3" "ipywidgets>=7.2"):
importplotly.graph_objectsasgofig=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 ✨
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==4.10.0

or conda.
conda install -c plotly plotly=4.10.0

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 jupyterlab-plotly@4.10.0
# OPTIONAL: Jupyter widgets extension for FigureWidget support
jupyter labextension install @jupyter-widgets/jupyterlab-manager plotlywidget@4.10.0

Please check out our Troubleshooting guide if you run into any problems with JupyterLab.
Static Image Export
plotly.py supports static image export,
using the 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 plotly python-kaleido

Orca
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

Or, 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
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.
About
The interactive graphing library for Python (includes Plotly Express) ✨
plotly.com/python/
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {
el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - rysktky/plotly.py: The interactive graphing library for Python (includes Plotly Express) :sparkles: · GitHub
Skip to content
BranchesTags
Repository files navigation
plotly.py
Latest Release
User forum
PyPI Downloads
License
Quickstart
pip install plotly==4.10.0
Inside Jupyter notebook (installable with pip install "notebook>=5.3" "ipywidgets>=7.2"):
importplotly.graph_objectsasgofig=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 ✨
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==4.10.0

or conda.
conda install -c plotly plotly=4.10.0

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 jupyterlab-plotly@4.10.0
# OPTIONAL: Jupyter widgets extension for FigureWidget support
jupyter labextension install @jupyter-widgets/jupyterlab-manager plotlywidget@4.10.0

Please check out our Troubleshooting guide if you run into any problems with JupyterLab.
Static Image Export
plotly.py supports static image export,
using the 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 plotly python-kaleido

Orca
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

Or, 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
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.
About
The interactive graphing library for Python (includes Plotly Express) ✨
plotly.com/python/
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
(function() {
var enabled = true;
function applyDarkMode() {
if (!enabled) return;
// Create style element if it doesn't exist
var style = document.getElementById('universal-dark-mode-style');
if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
// Dark mode CSS - inverts colors but preserves images/video
style.textContent = '
/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
/* Restore images, videos, iframes, canvas */
img, video, iframe, canvas, svg, picture, [style*="background-image"] {
filter: invert(1) hue-rotate(180deg) !important;
}
/* Preserve specific elements that should not be inverted */
.no-dark-mode, .no-dark-mode *,
[data-theme="light"], [data-theme="light"],
.ace_editor, .ace_editor *,
.CodeMirror, .CodeMirror *,
.monaco-editor, .monaco-editor *,
.markdown-body pre, .markdown-body pre *,
.highlight, .highlight *,
pre code, pre code * {
filter: none !important;
}
/* Fix common UI elements */
.modal, .popup, .dropdown-menu, .tooltip, .popover {
filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
}
/* Scrollbars */
::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
}
// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
if (enabled) {
applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
}
}
});
// Apply on load
applyDarkMode();
// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
GitHub - rysktky/plotly.py: The interactive graphing library for Python (includes Plotly Express) :sparkles: · GitHub
Skip to content
BranchesTags
Repository files navigation
plotly.py
Latest Release
User forum
PyPI Downloads
License
Quickstart
pip install plotly==4.10.0
Inside Jupyter notebook (installable with pip install "notebook>=5.3" "ipywidgets>=7.2"):
importplotly.graph_objectsasgofig=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 ✨
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==4.10.0

or conda.
conda install -c plotly plotly=4.10.0

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 jupyterlab-plotly@4.10.0
# OPTIONAL: Jupyter widgets extension for FigureWidget support
jupyter labextension install @jupyter-widgets/jupyterlab-manager plotlywidget@4.10.0

Please check out our Troubleshooting guide if you run into any problems with JupyterLab.
Static Image Export
plotly.py supports static image export,
using the 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 plotly python-kaleido

Orca
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

Or, 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
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.
About
The interactive graphing library for Python (includes Plotly Express) ✨
plotly.com/python/
Resources
Readme
MIT license
Code of conduct
Code of conduct
Contributing
Contributing
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages