csv-data-summarizer
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
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CSV Data Summarizer
This Skill analyzes CSV files and provides comprehensive summaries with statistical insights and visualizations.
When to Use This Skill
Claude should use this Skill whenever the user:
- Uploads or references a CSV file
- Asks to summarize, analyze, or visualize tabular data
- Requests insights from CSV data
- Wants to understand data structure and quality
How It Works
⚠️ CRITICAL BEHAVIOR REQUIREMENT ⚠️
DO NOT ASK THE USER WHAT THEY WANT TO DO WITH THE DATA. DO NOT OFFER OPTIONS OR CHOICES. DO NOT SAY "What would you like me to help you with?" DO NOT LIST POSSIBLE ANALYSES.
IMMEDIATELY AND AUTOMATICALLY:
- Run the comprehensive analysis
- Generate ALL relevant visualizations
- Present complete results
- NO questions, NO options, NO waiting for user input
THE USER WANTS A FULL ANALYSIS RIGHT AWAY - JUST DO IT.
Automatic Analysis Steps:
The skill intelligently adapts to different data types and industries by inspecting the data first, then determining what analyses are most relevant.
- Load and inspect the CSV file into pandas DataFrame
- Identify data structure - column types, date columns, numeric columns, categories
- Determine relevant analyses based on what's actually in the data:
- Sales/E-commerce data (order dates, revenue, products): Time-series trends, revenue analysis, product performance
- Customer data (demographics, segments, regions): Distribution analysis, segmentation, geographic patterns
- Financial data (transactions, amounts, dates): Trend analysis, statistical summaries, correlations
- Operational data (timestamps, metrics, status): Time-series, performance metrics, distributions
- Survey data (categorical responses, ratings): Frequency analysis, cross-tabulations, distributions
- Generic tabular data: Adapts based on column types found