Plotly Python Open Source Graphing Library Fundamentals

Plotly's Python graphing library makes interactive, publication-quality graphs online. Tutorials and tips about fundamental features of Plotly's python API.

Our recommended IDE for Plotly's Python graphing library is Dash Enterprise's Data Science Workspaces, which has both Jupyter notebook and Python code file support.
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• The Figure Data Structure
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• Creating and Updating Figures
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• Displaying Figures
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• Plotly Express
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• Analytical Apps with Dash
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• Static Image Export
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• Theming and templates
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• Version 4 Migration Guide
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• Orca Management
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• Configuration
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• Setting Graph Size
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• Formatting Ticks
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• Setting the Font, Title, Legend Entries, and Axis Titles
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• Axes
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• Legends
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• Multiple Axes
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• Subplots
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• Multiple Chart Types
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• Plotly Express Arguments
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• Styling Markers
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• Continuous Color Scales and Color Bars
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• Text and Annotations
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• Hover Text and Formatting
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• Images
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• Shapes
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• IPython vs Python
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• Troubleshooting
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• Built-in Continuous Color Scales
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• Discrete Colors
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• Styling Plotly Express Figures
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• Interactive HTML Export
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• Pandas Plotting Backend
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• Figure Factories
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• Plotly Express Wide-Form Support
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• Graph Objects
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• Introspecting Figures
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• Horizontal and Vertical Lines and Rectangles
  View Tutorial

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Plotly Express in Dash

Dash is the best way to build analytical apps in Python using Plotly figures. To run the app below, run pip install dash, click "Download" to get the code and run python app.py.

Get started with the official Dash docs and learn how to effortlessly style & deploy apps like this with Dash Enterprise.