84 lines
2.8 KiB
Markdown
84 lines
2.8 KiB
Markdown
# CSV Data Summarizer - Resources
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---
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## 🌟 Connect & Learn More
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</div>
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---
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## Sample Data
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The `sample.csv` file contains example sales data with the following columns:
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- **date**: Transaction date
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- **product**: Product name (Widget A, B, or C)
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- **quantity**: Number of items sold
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- **revenue**: Total revenue from the transaction
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- **customer_id**: Unique customer identifier
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- **region**: Geographic region (North, South, East, West)
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## Usage Examples
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### Basic Summary
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```
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Analyze sample.csv
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```
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### With Custom CSV
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```
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Here's my sales_data.csv file. Can you summarize it?
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```
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### Focus on Specific Insights
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```
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What are the revenue trends in this dataset?
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```
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## Testing the Skill
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You can test the skill locally before uploading to Claude:
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```bash
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# Install dependencies
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pip install -r ../requirements.txt
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# Run the analysis
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python ../analyze.py sample.csv
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```
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## Expected Output
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The analysis will provide:
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1. **Dataset dimensions** - Row and column counts
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2. **Column information** - Names and data types
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3. **Summary statistics** - Mean, median, std dev, min/max for numeric columns
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4. **Data quality** - Missing value detection and counts
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5. **Visualizations** - Time-series plots when date columns are present
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## Customization
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To adapt this skill for your specific use case:
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1. Modify `analyze.py` to include domain-specific calculations
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2. Add custom visualization types in the plotting section
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3. Include validation rules specific to your data
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4. Add more sample datasets to test different scenarios
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