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name: data-analysis description: Analyze datasets using pandas, generate reports, and create visualizations version: 1.0.0 author: cintegrity

Data Analysis Skill

Expert guidance for analyzing datasets, generating insights, and creating reports.

Analysis Approach

When analyzing data, follow this systematic approach:

1. Understand the question - What specific insight is needed?
2. Load and inspect - Get the data, check columns, row counts, data types
3. Aggregate and query - Group, sum, filter to answer the question
4. Format results - Present findings clearly with context
5. Save deliverables - Output reports in the requested format

Common Analysis Patterns

Revenue/Sales Analysis

• Group by region, product, time period
• Calculate totals, averages, percentages
• Compare across dimensions

Data Quality Checks

• Count missing values per column
• Identify outliers (values > 3 std from mean)
• Check for duplicates

Time Series

• Group by date/month/quarter
• Calculate period-over-period changes
• Identify trends and seasonality

Report Structure

A good analysis report includes:

# [Title]

## Summary
- Key finding 1
- Key finding 2

## Details
[Breakdown by dimension with numbers]

## Methodology
[Brief description of approach]

Workflow Templates

See scripts/analyze_csv.py for a reusable workflow pattern. See references/examples.md for common query patterns.