You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
41 lines
1.5 KiB
41 lines
1.5 KiB
# SpreadSheetSwarm
|
|
|
|
*Structured approach to data management and operations in spreadsheet-like format*
|
|
|
|
**Swarm Type**: `SpreadSheetSwarm`
|
|
|
|
## Overview
|
|
|
|
The SpreadSheetSwarm provides a structured approach to data management and operations, ideal for tasks involving data analysis, transformation, and systematic processing in a spreadsheet-like structure. This architecture organizes agents to work on data in a tabular format with clear rows, columns, and processing workflows.
|
|
|
|
Key features:
|
|
- **Structured Data Processing**: Organizes work in spreadsheet-like rows and columns
|
|
- **Systematic Operations**: Sequential and methodical data handling
|
|
- **Data Transformation**: Efficient processing of structured datasets
|
|
- **Collaborative Analysis**: Multiple agents working on different data aspects
|
|
|
|
## Use Cases
|
|
|
|
- Financial data analysis and reporting
|
|
- Customer data processing and segmentation
|
|
- Inventory management and tracking
|
|
- Research data compilation and analysis
|
|
|
|
## API Usage
|
|
|
|
### Basic SpreadSheetSwarm Example
|
|
|
|
|
|
|
|
## Best Practices
|
|
|
|
- Structure data in clear, logical formats before processing
|
|
- Use systematic, step-by-step analysis approaches
|
|
- Ideal for quantitative analysis and reporting tasks
|
|
- Ensure data validation before proceeding with analysis
|
|
|
|
## Related Swarm Types
|
|
|
|
- [SequentialWorkflow](sequential_workflow.md) - For ordered data processing
|
|
- [ConcurrentWorkflow](concurrent_workflow.md) - For parallel data analysis
|
|
- [HierarchicalSwarm](hierarchical_swarm.md) - For complex data projects |