data-analysis
Executive-grade data analysis with pandas/polars and McKinsey-quality visualizations. Use when analyzing data, building dashboards, creating investor presentations, or calculating SaaS metrics.
npx skills add majiayu000/claude-skill-registry --skill data-analysis-skill-scientiacapital-skills-2 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
<objective> Enable executive-grade data analysis for VC, PE, and C-suite presentations. Covers data ingestion from any format, SaaS metrics calculations (MRR, LTV, CAC, churn), cohort retention analysis, McKinsey-quality visualizations with Plotly, and Streamlit dashboards. </objective> <quick_start> **Universal data loader:** ```python df = load_data("file.csv") # Supports CSV, Excel, JSON, Parquet, PDF, PPTX ``` **SaaS metrics:** ```python metrics = calculate_saas_metrics(df) # MRR, ARR, LTV, CAC, churn retention = cohort_retention_analysis(df) # Retention matrix ``` **McKinsey-style charts:** Action titles ("Q4 Revenue Exceeded Target by 23%"), not descriptive titles </quick_start> <success_criteria> Analysis is successful when: - Data loaded and cleaned (dropna, dedup, type conversion) - Metrics calculated correctly (MRR, ARR, LTV:CAC, churn, cohort retention) - Charts follow McKinsey principles: action titles, data-ink ratio >80%, one message per chart - Executive colors used (#003366 primary, #2E7D32 positive, #C62828 negative) - Streamlit dashboard runs without errors - NO OPENAI: Use Claude for narrative generation if needed </success_criteria> <core_content> Executive-grad
- Quick Reference
- Data Ingestion Patterns
- Universal Data Loader
- PDF Table Extraction
- PowerPoint Data Extraction
- Data Wrangling Patterns
- Polars for Performance (30x faster than pandas)
- Common Transformations
- SaaS Metrics Calculations
- Core Metrics
- Cohort Analysis
- Executive Visualization
- McKinsey/BCG Chart Principles
- Plotly Executive Charts
What does the data-analysis skill do?
Executive-grade data analysis with pandas/polars and McKinsey-quality visualizations. Use when analyzing data, building dashboards, creating investor presentations, or calculating SaaS metrics.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill data-analysis-skill-scientiacapital-skills-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.