Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards. Supports both quick vis

Plotly Python graphing library for creating interactive, publication quality visualizations with 40+ chart types. Quick Start Install Plotly: Basic usage with Plotly Express (high level API): Choosing Between APIs Use Plotly Express (px) For quick, standard visualizations with sensible defaults: Working with pandas DataFrames Creating common chart types (scatter, line, bar, histogram, etc.) Need automatic color encoding and legends Want minimal code (1 5 lines) See [reference/plotly express.md](reference/plotly express.md) for complete guide. Use Graph Objects (go) For fine grained control and custom visualizations: Chart types not in Plotly Express (3D mesh, isosurface, complex financial charts) Building complex multi trace figures from scratch Need precise control over individual components Creating specialized visualizations with custom shapes and annotations See [reference/graph objects.md](reference/graph objects.md) for complete guide. Note: Plotly Express returns graph objects Figure, so you can combine approaches: Core Capabilities 1. Chart Types Plotly supports 40+ chart types organized into categories: Basic Charts: scatter, line, bar, pie, area, bubble Statistical Charts: histogram, box plot, violin, distribution, error bars Scientific Charts: heatmap, contour, ternary, image display Financial Charts: candlestick, OHLC, waterfall, funnel, time series Maps: scatter maps, choropleth, density maps (geographic visualization) 3D Charts: scatter3d, surface, mesh, cone, volume Specialized: sunburst, treemap, sankey, parallel coordinates, gauge For detailed examples and usage of all chart types, see [reference/chart types.md](reference/chart types.md). 2. Layouts and Styling Subplots: Create multi plot figures with shared axes: Templates: Apply coordinated styling: Customization: Control every aspect of appearance: Colors (discrete sequences, continuous scales) Fonts and text Axes (ranges, ticks, grids) Legends Margins and sizing Annotations and shapes For complete layout and styling options, see [reference/layouts styling.md](reference/layouts styling.md). 3. Interactivity Built in interactive features: Hover tooltips with customizable data Pan and zoom Legend toggling Box/lasso selection Rangesliders for time series Buttons and dropdowns Animations For complete interactivity guide, see [reference/export interactivity.md](reference/export interactivity.md). 4. Export Options Interactive HTML: Static Images (requires kaleido): For complete export options, see [reference/export interactivity.md](reference/export interactivity.md). Common Workflows Scientific Data Visualization Statistical Analysis Time Series and Financial Multi Plot Dashboards Integration with Dash For interactive web applications, use Dash (Plotly's web app framework): Reference Files [plotly express.md](reference/plotly express.md) High level API for quick visualizations [graph objects.md](reference/graph objects.md) Low level API for fine grained control [chart types.md](reference/chart types.md) Complete catalog of 40+ chart types with examples [layouts styling.md](reference/layouts styling.md) Subplots, templates, colors, customization [export interactivity.md](reference/export interactivity.md) Export options and interactive features Additional Resources Official documentation: https://plotly.com/python/ API reference: https://plotly.com/python api reference/ Community forum: https://community.plotly.com/