visualization▌

Transform and visualize interior spaces using each::sense. This skill takes photos of existing rooms and generates redesigned versions with different styles, furniture, colors, and layouts.

Create publication-ready scientific figures with matplotlib, seaborn, and plotly. \n \n Supports multi-panel layouts, error bars, significance markers, and journal-specific styling for Nature, Science, Cell, and PLOS \n Includes colorblind-safe palettes (Okabe-Ito, viridis) and grayscale compatibility testing to ensure accessibility \n Provides pre-configured style presets and export utilities for PDF, EPS, TIFF at correct DPI (300–1200 depending on figure type) \n Covers typography, resolution,

Intelligently selects from 26 chart types and generates visualization images from structured data. \n \n Covers 26 chart types across time series, comparisons, hierarchies, maps, relationships, and specialized visualizations (radar, funnel, sankey, network graphs, and more) \n Requires Node.js 18.0.0 or higher; generates charts by invoking a JavaScript script with JSON payload containing data, title, theme, and style parameters \n Workflow: analyze user data to select appropriate chart type, ext

Chart selection guidance, Python code patterns, and design principles for effective data visualizations. \n \n Comprehensive chart selection table covering 13+ chart types with guidance on when to use each and common anti-patterns to avoid (pie charts, 3D, dual-axis) \n Ready-to-use Python code examples for line charts, bar charts, histograms, heatmaps, small multiples, and interactive Plotly visualizations with professional styling \n Design principles covering color theory (sequential, divergi

Builds real-time incident response dashboards in Splunk, Elastic, or Grafana to provide SOC analysts and leadership with situational awareness during active incidents, tracking affected systems, containment status, IOC spread, and response timeline. Use when IR teams need unified visibility during incident coordination and post-incident reporting.

Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python.

Low-level plotting library for full customization, ideal for scientific workflows and publication-quality visualizations.

MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing.

Create professional research posters in LaTeX using beamerposter, tikzposter, or baposter.

Create professional infographics using Nano Banana Pro AI with smart iterative refinement and quality review.