When should I use Plotly Express vs Graph Objects?

Use Plotly Express for rapid exploratory analysis and standard chart types using DataFrames. Switch to Graph Objects for complex multi-trace figures, custom trace types, and fine-grained layout control.

How do I export Plotly figures to static images?

The skill provides patterns for using fig.write_image(), which supports formats like PNG, PDF, and SVG (requires the Kaleido library), as well as fig.write_html() for interactive files.

Can this skill help with biological data visualization?

Yes, it includes patterns specifically for scientific needs like UpSet plots for set intersections and hierarchical clustered heatmaps, which are common in omics research.

Does it support network or graph visualizations?

Yes, it provides implementation patterns using NetworkX for calculating graph layouts (like spring or Kamada-Kawai) and rendering them with Plotly's scatter and line traces.

Plotly Scientific Visualization

Name: Plotly Scientific Visualization
Author: CodingKaiser

byCodingKaiser

Data Science & ML

Generates interactive statistical and scientific visualizations using Plotly Express and Graph Objects APIs.

About

This skill provides a comprehensive library of Plotly visualization patterns designed for data science and scientific research. It bridges the gap between quick exploratory analysis using Plotly Express and highly customized, multi-trace figures via the Graph Objects API. Users can leverage this skill to implement complex charts such as violin plots, hierarchical heatmaps, UpSet plots for set intersections, and network graphs with custom layouts. It is particularly useful for developers and researchers in fields like omics and bioinformatics who require publication-quality, interactive data representations.

Key Features

Ready-to-use patterns for correlation matrices and clustered heatmaps
Interactive figure exporting to HTML, PNG, PDF, and SVG formats
Specialized scientific visualizations like UpSet plots and NetworkX-based graphs
0 GitHub stars
Support for both high-level Plotly Express and low-level Graph Objects APIs
Advanced statistical charts including box, violin, and strip plots

Use Cases

Generating publication-ready figures for scientific journals
Exploratory Data Analysis (EDA) in bioinformatics and genomics
Developing interactive data dashboards for web applications

About

Key Features

Ready-to-use patterns for correlation matrices and clustered heatmaps
Interactive figure exporting to HTML, PNG, PDF, and SVG formats
Specialized scientific visualizations like UpSet plots and NetworkX-based graphs
0 GitHub stars
Support for both high-level Plotly Express and low-level Graph Objects APIs
Advanced statistical charts including box, violin, and strip plots

Use Cases

Generating publication-ready figures for scientific journals
Exploratory Data Analysis (EDA) in bioinformatics and genomics
Developing interactive data dashboards for web applications