CSV Data Summarizer
Analyze CSV files and provide comprehensive summaries with statistical insights and visualizations.
Prerequisites
- •Python 3.8+
- •pandas, matplotlib, seaborn
Instructions
Critical Behavior
DO NOT ask what the user wants to do with the data. IMMEDIATELY run comprehensive analysis and present results.
Automatic Analysis Steps
- •Load and inspect CSV into pandas DataFrame
- •Identify data structure - column types, dates, numerics, categories
- •Determine relevant analyses based on data type:
- •Sales/E-commerce: Time-series, revenue, product performance
- •Customer data: Distributions, segmentation, geographic patterns
- •Financial data: Trends, summaries, correlations
- •Operational data: Time-series, metrics, distributions
- •Survey data: Frequencies, cross-tabulations
- •Generic: Adapts based on column types
Analysis Output
For each dataset, automatically generate:
- •
Data Overview
- •Shape, columns, types
- •Missing values summary
- •Memory usage
- •
Statistical Summary
- •Descriptive statistics
- •Distribution analysis
- •Correlation matrix
- •
Visualizations
- •Distribution plots
- •Time series (if dates present)
- •Category breakdowns
- •Correlation heatmaps
- •
Insights
- •Key findings
- •Anomalies detected
- •Recommendations
Guidelines
- •Run full analysis immediately - no questions
- •Adapt analysis to detected data type
- •Generate ALL relevant visualizations
- •Present complete results without waiting for input
- •Include actionable insights
Notes
- •Intelligently adapts to different industries
- •Inspects data first, then determines relevant analyses
- •No user input required - just provide the CSV
Source: coffeefuelbump/csv-data-summarizer-claude-skill