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plotly

Name: plotly
Author: K-Dense Inc.

Safe

Create Interactive Visualizations with Plotly

Also available from: davila7

Data visualization often requires complex code and lacks interactivity for exploration. This skill provides comprehensive guidance for creating interactive, publication-quality charts with Plotly, featuring hover tooltips, zoom, pan, and 40+ chart types for dashboards and data analysis.

Supports: Claude Codex Code(CC)

📊 71 Adequate

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Test it

Using "plotly". Create a simple scatter plot of x and y data

Expected outcome:

Code snippet showing px.scatter() with basic parameters, fig.show() for display, and explanation of interactive features like zoom and hover

Using "plotly". How do I export my Plotly chart to HTML?

Expected outcome:

Code example using fig.write_html() with explanation of file path parameter and embedded vs CDN options for JavaScript libraries

Using "plotly". Build a 3D surface plot

Expected outcome:

Code using go.Surface() with mesh grid data, camera angle configuration, and color scale customization instructions

Security Audit

Safe

v5 • 1/21/2026

This is a legitimate documentation skill for the Plotly visualization library. All 342 static findings are false positives from the pattern scanner detecting markdown code block delimiters as shell commands, documentation text as malicious keywords, and legitimate API references as threats. No actual security risks present.

Files scanned

5,815

Lines analyzed

findings

Total audits

No security issues found

Audited by: claude View Audit History →

Quality Score

Architecture

100

Maintainability

Content

Community

100

Security

Spec Compliance

What You Can Build

Dashboard Development

Build interactive dashboards for business intelligence with real-time data exploration capabilities including filtering, zooming, and hover details.

Scientific Data Visualization

Create publication-quality charts for research papers, presentations, and reports with precise control over styling and layout.

Exploratory Data Analysis

Quickly visualize data distributions, correlations, and patterns with interactive charts for hypothesis generation and data quality assessment.

Try These Prompts

Basic Chart Creation

Create a scatter plot showing the relationship between temperature and sales using Plotly Express

Multi-Series Line Chart

Generate an interactive line chart comparing monthly revenue across three product categories with hover tooltips

Custom Styled Visualization

Build a histogram with custom colors, bin sizes, and annotations showing data distribution with mean and median lines

Advanced Multi-Plot Layout

Create a dashboard with subplots containing a scatter plot, bar chart, and heatmap arranged in a grid layout with shared color scales

Best Practices

Use Plotly Express for quick standard visualizations and Graph Objects for fine-grained control over complex custom charts
Enable responsive sizing with fig.update_layout for charts that adapt to different screen sizes and container dimensions
Optimize large datasets by aggregating data or using sampling techniques before visualization to maintain interactivity performance

Avoid

Avoid using Graph Objects for simple charts when Plotly Express can achieve the same result with less code
Do not create overly complex charts with too many traces or data points that make interaction slow or confusing
Never hardcode chart dimensions without considering responsive design for different display environments

Frequently Asked Questions

When should I use Plotly Express versus Graph Objects?

Use Plotly Express for quick standard visualizations with pandas DataFrames. Use Graph Objects when you need precise control over individual components or chart types not available in Plotly Express.

How do I make my charts work in Jupyter notebooks?

Plotly charts display automatically in Jupyter notebooks when you call fig.show(). Ensure you have the notebook renderer installed with pip install notebook.

Can I export Plotly charts to static images?

Yes, install kaleido with pip install kaleido, then use fig.write_image for PNG, PDF, or SVG export. HTML export works without additional dependencies.

How do I customize chart colors and themes?

Use the color parameter in Plotly Express or update_traces for individual series. Apply built-in themes with fig.update_layout or create custom color scales.

What is the difference between show and write methods?

The show method displays charts interactively in supported environments. Write methods like write_html and write_image save charts to files for sharing or embedding.

Does this skill require internet connection?

No, Plotly works offline. Charts can be exported with embedded JavaScript libraries for offline viewing without external CDN dependencies.