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Open Source Python Graphing & Data Visualization Library | Plotly
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Quick Reference Examples
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Open Source Python Graphing and Data Visualization Library

Plotly's Python graphing library makes interactive, publication-quality graphs. Examples of how to make line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, polar charts, and bubble charts.
Plotly.py is free and open source, and you can view the source, report issues, or contribute on GitHub.


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Fundamentals More Fundamentals »

Explore step-by-step tutorials and code examples for figure structures, updating figures, displaying figures, and framework integrations to master our Python graphing library.

Basic Charts More Basic Charts »

Find copy-pasteable code snippets and interactive demos to create standard Python charts, including scatter plots, line graphs, bar charts, pie charts, and bubble charts.

Statistical Charts More Statistical Charts »

Browse code tutorials and live previews for complex data analysis, featuring box plots, histograms, error bars, and 2D density plots.

Scientific Charts More Scientific Charts »

Access interactive examples and code snippets for domain-specific visualizations. Build heatmaps, contour plots, ternary plots, and log plots.

Financial Charts More Financial Charts »

Explore code guides and live examples for financial data, including candlestick charts, OHLC plots, waterfall diagrams, funnel charts, and time series lines to create interactive graphs in Python.

Maps More Maps »

Learn how to build interactive geographic visualizations with step-by-step code snippets for Mapbox integration, tile choropleth maps, lines on maps, and bubble maps.

Artificial Intelligence and Machine Learning More AI and ML »

Visualize machine learning models with tutorials for ML regression, kNN classification, ROC and PR curves, and PCA visualization.

Bioinformatics More Bioinformatics »

Access specialized charts for computational biology, including volcano plots, Manhattan plots, clustergrams, and alignment charts.

More Bioinformatics » 3D Charts More 3D Charts »

View high-performance code examples for 3D axes, 3D scatter plots, 3D surface plots, and 3D subplots to enhance your Python graphs.

Subplots

Find layout tutorials and code examples for combining multi-chart arrangements, map subplots, table subplots, and mixed layouts when plotting graphs in Python.

Jupyter Widgets Interaction

Learn how to connect your Python graph to interactive Jupyter environments using FigureWidget tutorials, interactive data analysis, and custom click events.

Add Custom Controls

Discover code snippets and tutorials for building interactive UI controls directly into your visualizations, including dropdown menus, custom buttons, sliders, and range selectors to upgrade your graph in Python.

Animations

Explore code tutorials and interactive demos for animating data points, building time-series sliders, and creating smooth transitions to build a dynamic Python graph.

Advanced

Take your interactive plots in Python to the next level with advanced Python graphing techniques, including plotting CSV data, generating random walks, peak finding, data smoothing, and rendering LaTeX.

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