Repository files navigation

plotly.py

Latest Release
User forum
PyPI Downloads
License
Maintained by Plotly

Quickstart

pip install plotly==5.23.0

Inside Jupyter (installable with pip install "jupyterlab>=3" "ipywidgets>=7.6"):

importplotly.expressaspxfig=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 ✨

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==5.23.0

or conda.

conda install -c plotly plotly=5.23.0

JupyterLab Support

For use in JupyterLab, install the jupyterlab and ipywidgets packages using pip:

pip install "jupyterlab>=3" "ipywidgets>=7.6"

or conda:

conda install "jupyterlab>=3" "ipywidgets>=7.6"

The instructions above apply to JupyterLab 3.x. For JupyterLab 2 or earlier, run the following commands to install the required JupyterLab extensions (note that this will require node to be installed):

# JupyterLab 2.x renderer support
jupyter labextension install jupyterlab-plotly@5.23.0 @jupyter-widgets/jupyterlab-manager

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

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"

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

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

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 ✨ This project now includes Plotly Express!

Resources

Code of conduct

Contributing

Security policy

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
Skip to content

Repository files navigation

plotly.py

Latest Release
User forum
PyPI Downloads
License
Maintained by Plotly

Quickstart

pip install plotly==5.23.0

Inside Jupyter (installable with pip install "jupyterlab>=3" "ipywidgets>=7.6"):

importplotly.expressaspxfig=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 ✨

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==5.23.0

or conda.

conda install -c plotly plotly=5.23.0

JupyterLab Support

For use in JupyterLab, install the jupyterlab and ipywidgets packages using pip:

pip install "jupyterlab>=3" "ipywidgets>=7.6"

or conda:

conda install "jupyterlab>=3" "ipywidgets>=7.6"

The instructions above apply to JupyterLab 3.x. For JupyterLab 2 or earlier, run the following commands to install the required JupyterLab extensions (note that this will require node to be installed):

# JupyterLab 2.x renderer support
jupyter labextension install jupyterlab-plotly@5.23.0 @jupyter-widgets/jupyterlab-manager

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

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"

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

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

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 ✨ This project now includes Plotly Express!

Resources

Code of conduct

Contributing

Security policy

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

Repository files navigation

plotly.py

Latest Release
User forum
PyPI Downloads
License
Maintained by Plotly

Quickstart

pip install plotly==5.23.0

Inside Jupyter (installable with pip install "jupyterlab>=3" "ipywidgets>=7.6"):

importplotly.expressaspxfig=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 ✨

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==5.23.0

or conda.

conda install -c plotly plotly=5.23.0

JupyterLab Support

For use in JupyterLab, install the jupyterlab and ipywidgets packages using pip:

pip install "jupyterlab>=3" "ipywidgets>=7.6"

or conda:

conda install "jupyterlab>=3" "ipywidgets>=7.6"

The instructions above apply to JupyterLab 3.x. For JupyterLab 2 or earlier, run the following commands to install the required JupyterLab extensions (note that this will require node to be installed):

# JupyterLab 2.x renderer support
jupyter labextension install jupyterlab-plotly@5.23.0 @jupyter-widgets/jupyterlab-manager

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

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"

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

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

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 ✨ This project now includes Plotly Express!

Resources

Code of conduct

Contributing

Security policy

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

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plotly.py

Latest Release
User forum
PyPI Downloads
License
Maintained by Plotly

Quickstart

pip install plotly==5.23.0

Inside Jupyter (installable with pip install "jupyterlab>=3" "ipywidgets>=7.6"):

importplotly.expressaspxfig=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 ✨

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==5.23.0

or conda.

conda install -c plotly plotly=5.23.0

JupyterLab Support

For use in JupyterLab, install the jupyterlab and ipywidgets packages using pip:

pip install "jupyterlab>=3" "ipywidgets>=7.6"

or conda:

conda install "jupyterlab>=3" "ipywidgets>=7.6"

The instructions above apply to JupyterLab 3.x. For JupyterLab 2 or earlier, run the following commands to install the required JupyterLab extensions (note that this will require node to be installed):

# JupyterLab 2.x renderer support
jupyter labextension install jupyterlab-plotly@5.23.0 @jupyter-widgets/jupyterlab-manager

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

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"

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

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

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 ✨ This project now includes Plotly Express!

Resources

Code of conduct

Contributing

Security policy

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
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plotly.py

Latest Release
User forum
PyPI Downloads
License
Maintained by Plotly

Quickstart

pip install plotly==5.23.0

Inside Jupyter (installable with pip install "jupyterlab>=3" "ipywidgets>=7.6"):

importplotly.expressaspxfig=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 ✨

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==5.23.0

or conda.

conda install -c plotly plotly=5.23.0

JupyterLab Support

For use in JupyterLab, install the jupyterlab and ipywidgets packages using pip:

pip install "jupyterlab>=3" "ipywidgets>=7.6"

or conda:

conda install "jupyterlab>=3" "ipywidgets>=7.6"

The instructions above apply to JupyterLab 3.x. For JupyterLab 2 or earlier, run the following commands to install the required JupyterLab extensions (note that this will require node to be installed):

# JupyterLab 2.x renderer support
jupyter labextension install jupyterlab-plotly@5.23.0 @jupyter-widgets/jupyterlab-manager

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

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"

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

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

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 ✨ This project now includes Plotly Express!

Resources

Code of conduct

Contributing

Security policy

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

Repository files navigation

plotly.py

Latest Release
User forum
PyPI Downloads
License
Maintained by Plotly

Quickstart

pip install plotly==5.23.0

Inside Jupyter (installable with pip install "jupyterlab>=3" "ipywidgets>=7.6"):

importplotly.expressaspxfig=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 ✨

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==5.23.0

or conda.

conda install -c plotly plotly=5.23.0

JupyterLab Support

For use in JupyterLab, install the jupyterlab and ipywidgets packages using pip:

pip install "jupyterlab>=3" "ipywidgets>=7.6"

or conda:

conda install "jupyterlab>=3" "ipywidgets>=7.6"

The instructions above apply to JupyterLab 3.x. For JupyterLab 2 or earlier, run the following commands to install the required JupyterLab extensions (note that this will require node to be installed):

# JupyterLab 2.x renderer support
jupyter labextension install jupyterlab-plotly@5.23.0 @jupyter-widgets/jupyterlab-manager

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

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"

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

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

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 ✨ This project now includes Plotly Express!

Resources

Code of conduct

Contributing

Security policy

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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plotly.py

Latest Release
User forum
PyPI Downloads
License
Maintained by Plotly

Quickstart

pip install plotly==5.23.0

Inside Jupyter (installable with pip install "jupyterlab>=3" "ipywidgets>=7.6"):

importplotly.expressaspxfig=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 ✨

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==5.23.0

or conda.

conda install -c plotly plotly=5.23.0

JupyterLab Support

For use in JupyterLab, install the jupyterlab and ipywidgets packages using pip:

pip install "jupyterlab>=3" "ipywidgets>=7.6"

or conda:

conda install "jupyterlab>=3" "ipywidgets>=7.6"

The instructions above apply to JupyterLab 3.x. For JupyterLab 2 or earlier, run the following commands to install the required JupyterLab extensions (note that this will require node to be installed):

# JupyterLab 2.x renderer support
jupyter labextension install jupyterlab-plotly@5.23.0 @jupyter-widgets/jupyterlab-manager

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

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"

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

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

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 ✨ This project now includes Plotly Express!

Resources

Code of conduct

Contributing

Security policy

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

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

Repository files navigation

plotly.py

Latest Release
User forum
PyPI Downloads
License
Maintained by Plotly

Quickstart

pip install plotly==5.23.0

Inside Jupyter (installable with pip install "jupyterlab>=3" "ipywidgets>=7.6"):

importplotly.expressaspxfig=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 ✨

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==5.23.0

or conda.

conda install -c plotly plotly=5.23.0

JupyterLab Support

For use in JupyterLab, install the jupyterlab and ipywidgets packages using pip:

pip install "jupyterlab>=3" "ipywidgets>=7.6"

or conda:

conda install "jupyterlab>=3" "ipywidgets>=7.6"

The instructions above apply to JupyterLab 3.x. For JupyterLab 2 or earlier, run the following commands to install the required JupyterLab extensions (note that this will require node to be installed):

# JupyterLab 2.x renderer support
jupyter labextension install jupyterlab-plotly@5.23.0 @jupyter-widgets/jupyterlab-manager

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

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"

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

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

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 ✨ This project now includes Plotly Express!

Resources

Code of conduct

Contributing

Security policy

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages