plotly

Plotly is a comprehensive Python graphing library designed for creating interactive, publication-quality visualizations. This skill provides the instructional framework necessary for Claude to generate complex charts, plots, and data-driven dashboards. It supports both high-level APIs like Plotly Express for rapid prototyping and low-level Graph Objects for granular control over every aspect of a visualization. Whether you are performing exploratory data analysis, presenting research findings, or building financial reports, this skill enables the creation of responsive plots that feature zoom, pan, and hover interactivity out of the box. Users can easily integrate these figures into larger web applications using Dash or export them as standalone HTML files, PNGs, PDFs, or SVGs for static reporting.

• Access to over 40+ chart types including scatter, line, bar, pie, heatmap, contour, 3D surface, and financial charts like candlestick or OHLC.

• Advanced statistical visualization capabilities including box plots, violin plots, histograms with marginal distributions, and trendline integration.

• Extensive layout and styling options such as custom themes (plotly_dark, plotly_white), subplot creation, and precise control over axes, legends, and annotation layers.

• Built-in interactivity features including range sliders for time series, lasso selection, animation frames, and custom hover template configuration.

• Direct compatibility with Pandas DataFrames for seamless data ingestion and transformation during the visualization process.

• Utilize Plotly Express for standard tasks requiring minimal code; switch to Graph Objects when complex layering or custom shapes are required.

• Ensure the kaleido library is installed to support static image exports (PNG, SVG, PDF).

• Combine Plotly figures with Dash to develop interactive web applications or monitoring dashboards.

• Handle geographic data effectively using built-in map projections, scatter maps, and choropleth support.

• Remember that Plotly Express functions return figure objects, which can be further modified using Graph Object update methods to add markers, lines, or annotations.