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Analyze data patterns, create visualizations, and generate insights from datasets using statistical methods and data science techniques
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Retrieves and analyzes content from user-provided URLs or search results using the WebFetch tool. Manages domain filtering and max_uses limits to prevent data exfiltration. Use when users provide URLs to fetch, when analyzing web pages, or when following up on search results.
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| name | data-analysis |
| description | Analyze data patterns, create visualizations, and generate insights from datasets using statistical methods and data science techniques |
Transform raw data into actionable insights. This skill helps you explore datasets, identify patterns, create visualizations, and generate statistical reports.
This skill enables you to:
Use this skill when you need to:
When using this skill:
Dataset: Customer transactions with 10,000 records
Analysis Steps:
Output:
# Customer Analysis Report
## Summary Statistics
- Total Revenue: $2.5M
- Average Order Value: $125
- Number of Customers: 3,450
- Date Range: 2023-01-01 to 2024-01-15
## Key Findings
1. Electronics category drives 42% of revenue
2. Top 20% of customers generate 80% of revenue (Pareto principle)
3. Strong seasonal pattern with peak in Q4
4. Average customer lifetime value: $1,200
## Recommendations
- Focus retention efforts on high-value customers
- Increase inventory for Q4 seasonal demand
- Cross-sell opportunities in Electronics + Home categories
Dataset: Daily pageviews, bounce rate, session duration
Key Metrics Analyzed:
Visualizations Generated:
| Scenario | Analysis Type | Key Metrics |
|---|---|---|
| Sales Data | Trend & Seasonal | Growth rate, Seasonality index |
| Customer Data | Segmentation | RFM score, Cohort analysis |
| Website Data | Behavior | Bounce rate, Conversion funnel |
| Time Series | Forecasting | Trend, Seasonality, Residuals |
| A/B Testing | Hypothesis Test | P-value, Effect size |
This skill uses:
The skill automatically:
For data analysis help:
assets/examples/datasets/scripts/references/