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

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date,product,quantity,revenue,customer_id,region
2024-01-15,Widget A,5,129.99,C001,North
2024-01-16,Widget B,3,89.97,C002,South
2024-01-17,Widget A,7,181.98,C003,East
2024-01-18,Widget C,2,199.98,C001,North
2024-01-19,Widget B,4,119.96,C004,West
2024-01-20,Widget A,6,155.94,C005,South
2024-01-21,Widget C,1,99.99,C002,South
2024-01-22,Widget B,8,239.92,C006,East
2024-01-23,Widget A,3,77.97,C007,North
2024-01-24,Widget C,5,499.95,C003,East
2024-01-25,Widget B,2,59.98,C008,West
2024-01-26,Widget A,9,233.91,C004,West
2024-01-27,Widget C,3,299.97,C009,North
2024-01-28,Widget B,6,179.94,C010,South
2024-01-29,Widget A,4,103.96,C005,South
2024-01-30,Widget C,7,699.93,C011,East
2024-01-31,Widget B,5,149.95,C012,West
2024-02-01,Widget A,8,207.92,C013,North
2024-02-02,Widget C,2,199.98,C014,South
2024-02-03,Widget B,10,299.90,C015,East
1 date product quantity revenue customer_id region
2 2024-01-15 Widget A 5 129.99 C001 North
3 2024-01-16 Widget B 3 89.97 C002 South
4 2024-01-17 Widget A 7 181.98 C003 East
5 2024-01-18 Widget C 2 199.98 C001 North
6 2024-01-19 Widget B 4 119.96 C004 West
7 2024-01-20 Widget A 6 155.94 C005 South
8 2024-01-21 Widget C 1 99.99 C002 South
9 2024-01-22 Widget B 8 239.92 C006 East
10 2024-01-23 Widget A 3 77.97 C007 North
11 2024-01-24 Widget C 5 499.95 C003 East
12 2024-01-25 Widget B 2 59.98 C008 West
13 2024-01-26 Widget A 9 233.91 C004 West
14 2024-01-27 Widget C 3 299.97 C009 North
15 2024-01-28 Widget B 6 179.94 C010 South
16 2024-01-29 Widget A 4 103.96 C005 South
17 2024-01-30 Widget C 7 699.93 C011 East
18 2024-01-31 Widget B 5 149.95 C012 West
19 2024-02-01 Widget A 8 207.92 C013 North
20 2024-02-02 Widget C 2 199.98 C014 South
21 2024-02-03 Widget B 10 299.90 C015 East