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Frameworks & web · #plotly
Plotly Express lets you create polished, faceted scatter plots with a single line of code, but it hides performance and customization limits. Learn when to stay at the high‑level API and when to drop down to graph_objects for custom annotations, dual‑axes, and WebGL rendering.
Learn how to build an interactive scatter plot that maps a categorical variable to color, then export it as a stand‑alone HTML file for sharing or embedding. Follow the step‑by‑step guide, check the output, and know the limits.
Learn how Plotly’s make_subplots function creates a grid of plots with optional shared X or Y axes, reducing boilerplate layout code.
Learn how to render a fully interactive line chart from a pandas DataFrame using Plotly Express, including HTML export and troubleshooting.
Stop styling every Plotly chart by hand. Register a custom layout template once and apply it across notebooks, scripts, and Dash apps.
Add ordinary least squares trendlines to Plotly Express scatter plots, with limits and verification steps.
Replace Plotly’s default hover text with rich, custom tooltips using hovertemplate. A step‑by‑step example, trade‑offs, and cross‑language tips to make your charts more informative.
Create a Plotly Dash app that lets users filter a scatter plot via a dropdown. Follow our step‑by‑step guide, checklists, and recovery tips to build, debug, and deploy the app.
When Plotly’s scattergl shows blank points or sluggish zooming, the culprit is often WebGL buffer limits or inefficient updates. This diagnostic guide walks through symptom checks, fixes, and when to ask for help, ensuring a smooth 60 FPS interactive plot.
python
pandas