plotly

Build interactive Plotly charts with Express and Graph Objects workflows.

6|1|Updated Nov 26, 2025

Search Tags:#interactive #visualization #plotly #export #data-visualization #plotly-express #graph-objects

Ready to run

npx skills add https://github.com/CodingKaiser/kaiser-skills --skill plotly-codingkaiser

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: plotly
Source: https://github.com/CodingKaiser/kaiser-skills/tree/main/plotly
Command: npx skills add https://github.com/CodingKaiser/kaiser-skills --skill plotly-codingkaiser

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the challenge of building interactive Plotly visualizations.

Core Features & Use Cases

Express-ready charts: Quickly create scatter, line, bar, histogram, box, violin, and other common visualizations from data frames.
Graph Objects control: Fine-grained customization for multi-trace figures, annotations, and complex layouts.
Export capability: Publish figures to HTML for interactive viewing or export as PNG/SVG/PDF when Kaleido is available.

Quick Start

Install the library: pip install plotly
Import and load data: import plotly.express as px; df = ...
Create a basic chart: fig = px.scatter(df, x="x", y="y", color="category")
Display the figure: fig.show()

Frequently Asked Questions about plotly

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I create interactive data visualizations with Plotly from a dataframe?▼

You can create interactive Plotly visualizations by importing plotly.express and passing a dataframe to chart functions like px.scatter, specifying x, y, and color parameters to generate interactive figures ready for display.

What is the difference between Plotly Express and Graph Objects for building charts?▼

Plotly Express generates common statistical charts quickly from dataframes, while Graph Objects provides fine-grained customization for complex layouts, multi-trace figures, and detailed annotations in interactive visualizations.

How do I export Plotly figures to static PNG or SVG files?▼

To export Plotly figures as static PNG or SVG files, you need optional Kaleido support installed in your Python environment, which enables static image exports alongside interactive HTML publishing.

Can I build scientific charts like heatmaps and network graphs using Plotly?▼

Yes, Plotly supports building scientific and statistical interactive visualizations including heatmaps, network graphs, UpSet plots, scatter, and bar charts through both Express and Graph Objects workflows.

Do I need to install Kaleido to view interactive Plotly charts in HTML?▼

No, Kaleido is only required for exporting static PNG, SVG, or PDF files; interactive Plotly visualizations can be published and viewed directly in HTML without needing the Kaleido package.