Smart Chart Recommender

Pro v1.0.0 1 view

Get intelligent chart type recommendations based on your data structure and visualization goals, plus publication-ready visualizations with matplotlib/seaborn.

What You Get

Stop wasting hours experimenting with chart types. Get data-driven recommendations, publication-ready visualizations, and expert guidance on what to avoid - all tailored to your specific data and audience.

The Problem

Data analysts and business users waste significant time choosing chart types, often selecting inappropriate visualizations that mislead audiences or fail to communicate insights effectively. Without visualization expertise, they struggle to match chart types to data structures, audience needs, and communication goals.

The Solution

This skill analyzes your data structure (variable types, distributions, sample size) and combines it with your stated goals and audience to recommend 2-4 optimal chart types with detailed reasoning. It then generates publication-ready visualizations using professional styling, colorblind-friendly palettes, and best practices. Each recommendation explains WHY it works for your case, WHAT insights it reveals, WHEN to use it, and what chart types to AVOID.

How It Works

  1. 1 Understand visualization goals and audience context (comparison, distribution, correlation, composition, or trend analysis)
  2. 2 Analyze data structure including variable types, distributions, sample size, outliers, and missing data patterns
  3. 3 Generate 2-4 ranked chart recommendations based on data characteristics, goals, and audience sophistication
  4. 4 Create publication-ready visualizations using matplotlib/seaborn with professional styling and colorblind-friendly palettes
  5. 5 Provide interpretation guidance with key insights, customization suggestions, and actionable recommendations

What You'll Need

  • Dataset in CSV, Excel, or pandas-compatible format
  • Clear visualization goal (comparison, distribution, correlation, composition, or trend)
  • Audience context (technical stakeholders, executives, or general public)
  • Python environment with pandas, matplotlib, seaborn, scipy installed