Overview
The Data Analysis skill helps Claude analyze datasets, identify patterns, compute statistics, and suggest visualizations for your data.
SKILL.md Template
---
name: analyze-data
description: Analyze data files and query results to extract insights. Use when working with CSV, JSON data, or database query outputs.
---
When analyzing data, perform these steps:
## 1. Data Overview
- Record count and field inventory
- Data types for each column
- Missing value assessment
- Unique value counts
## 2. Statistical Summary
For numeric fields:
- Mean, median, mode
- Min, max, range
- Standard deviation
- Quartiles (Q1, Q2, Q3)
For categorical fields:
- Value frequency distribution
- Top categories
- Cardinality
## 3. Pattern Detection
- Trends over time
- Correlations between fields
- Outliers and anomalies
- Clusters or groupings
## 4. Data Quality Issues
- Missing values
- Duplicates
- Inconsistent formats
- Invalid entries
## 5. Visualization Recommendations
Suggest appropriate charts:
- Time series → Line chart
- Categories → Bar/Pie chart
- Distributions → Histogram
- Relationships → Scatter plot
## Output Format
```markdown
# Data Analysis Report
## Overview
- Records: X
- Fields: Y
- Date range: Z
## Key Findings
1. [Most important insight]
2. [Second insight]
3. [Third insight]
## Detailed Statistics
[Tables with stats]
## Recommendations
[Action items based on findings]
## Example Output
```markdown
# Sales Data Analysis Report
## Overview
- **Records**: 15,432 transactions
- **Date range**: Jan 1 - Dec 31, 2024
- **Fields**: 12 columns
## Key Findings
1. **Revenue Peak**: Q4 accounts for 42% of annual revenue
2. **Top Product**: "Premium Widget" drives 28% of sales
3. **Growth Trend**: 15% YoY increase in average order value
## Statistical Summary
| Metric | Value |
|--------|-------|
| Total Revenue | $2.4M |
| Average Order | $156 |
| Median Order | $89 |
| Orders/Day | 42.3 |
## Category Distribution
| Category | Orders | Revenue | % of Total |
|----------|--------|---------|------------|
| Electronics | 5,230 | $980K | 41% |
| Software | 4,102 | $720K | 30% |
| Services | 6,100 | $700K | 29% |
## Data Quality Issues
- 23 records missing customer_id (0.15%)
- 5 duplicate order_ids detected
- 12 orders with negative quantities (refunds?)
## Visualization Recommendations
1. **Revenue over time**: Line chart, monthly aggregation
2. **Category breakdown**: Pie chart for revenue share
3. **Order value distribution**: Histogram with $25 bins
Usage
/analyze-data sales_2024.csv
Or ask naturally:
What patterns do you see in this customer data?
Supported Formats
- CSV files
- JSON data
- SQL query results
- Excel exports (converted to CSV)
- API response data