plotly-1-use-plotly-express-for-quick-plots
About
This skill teaches developers to use Plotly Express for rapid creation of standard plots from DataFrames with concise syntax. It also covers transitioning to Graph Objects for advanced customization and optimizing visualizations for large datasets or responsive design. Use this for quick exploratory data visualization before diving into detailed figure customization.
Quick Install
Claude Code
Recommendednpx skills add vamseeachanta/workspace-hub -a claude-code/plugin add https://github.com/vamseeachanta/workspace-hubgit clone https://github.com/vamseeachanta/workspace-hub.git ~/.claude/skills/plotly-1-use-plotly-express-for-quick-plotsCopy and paste this command in Claude Code to install this skill
GitHub Repository
Related Skills
d3js
OtherThis skill enables developers to create fully customized, interactive data visualizations using D3.js, offering complete control over SVG elements and data binding. It's ideal for building unique, complex charts with sophisticated transitions and interactions that standard libraries can't achieve. Use it when you need bespoke, data-driven visualizations rather than simple, pre-styled charts.
plotly-javascript-cdn
OtherThis skill provides the CDN script tag to embed Plotly.js directly into web projects for interactive data visualizations. It's ideal for developers needing quick client-side charting without build tools or npm dependencies. The skill also includes complementary installation commands for Python/R Plotly backends.
highcharts-theming
OtherThis skill enables developers to apply custom visual themes to Highcharts visualizations. It provides reference code for globally configuring colors, backgrounds, fonts, and other styling options using `Highcharts.setOptions()`. Use this skill when you need to maintain consistent branding or styling across multiple charts in your application.
plotly-with-pandas
OtherThis skill provides Plotly integration with Pandas for streamlined data visualization from DataFrames. It enables direct plotting from CSV data and includes NumPy compatibility for mathematical visualizations. Use it when working with tabular data in Jupyter environments where interactive charts are needed.