data-analyst

Data Analyst Skill 📊

Turn your AI agent into a data analysis powerhouse.

Query databases, analyze spreadsheets, create visualizations, and generate insights that drive decisions.

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What This Skill Does

✅ SQL Queries — Write and execute queries against databases ✅ Spreadsheet Analysis — Process CSV, Excel, Google Sheets data ✅ Data Visualization — Create charts, graphs, and dashboards ✅ Report Generation — Automated reports with insights ✅ Data Cleaning — Handle missing data, outliers, formatting ✅ Statistical Analysis — Descriptive stats, trends, correlations

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Quick Start

1. Configure your data sources in TOOLS.md:

### Data Sources
- Primary DB: [Connection string or description]
- Spreadsheets: [Google Sheets URL / local path]
- Data warehouse: [BigQuery/Snowflake/etc.]

1. Set up your workspace:

./scripts/data-init.sh

1. Start analyzing!

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SQL Query Patterns

Common Query Templates

Basic Data Exploration

-- Row count
SELECT COUNT(*) FROM table_name;

-- Sample data
SELECT * FROM table_name LIMIT 10;

-- Column statistics
SELECT 
    column_name,
    COUNT(*) as count,
    COUNT(DISTINCT column_name) as unique_values,
    MIN(column_name) as min_val,
    MAX(column_name) as max_val
FROM table_name
GROUP BY column_name;

Time-Based Analysis

-- Daily aggregation
SELECT 
    DATE(created_at) as date,
    COUNT(*) as daily_count,
    SUM(amount) as daily_total
FROM transactions
GROUP BY DATE(created_at)
ORDER BY date DESC;

-- Month-over-month comparison
SELECT 
    DATE_TRUNC('month', created_at) as month,
    COUNT(*) as count,
    LAG(COUNT(*)) OVER (ORDER BY DATE_TRUNC('month', created_at)) as prev_month,
    (COUNT(*) - LAG(COUNT(*)) OVER (ORDER BY DATE_TRUNC('month', created_at))) / 
        NULLIF(LAG(COUNT(*)) OVER (ORDER BY DATE_TRUNC('month', created_at)), 0) * 100 as growth_pct
FROM transactions
GROUP BY DATE_TRUNC('month', created_at)
ORDER BY month;