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title: Transforming Data
sidebar_position: 4
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# Transforming Data

🚧 **Coming Soon** 🚧

Master data transformation techniques to prepare and optimize data for your visualization plugins.

## Topics to be covered:

- Data transformation pipeline architecture
- Understanding query results structure
- Implementing transform props functions
- Data aggregation and grouping
- Filtering and sorting operations
- Data type conversion and validation
- Handling missing and null values
- Performance optimization for large datasets
- Caching and memoization strategies
- Error handling in data transformations

## Transformation Patterns

### Data Preparation
- **Normalization** - Converting data to consistent formats
- **Aggregation** - Grouping and summarizing data
- **Pivoting** - Reshaping data for different chart types
- **Joining** - Combining multiple data sources
- **Filtering** - Removing irrelevant data points

### Chart-Specific Transformations
- **Time series** - Date parsing and time-based grouping
- **Geographic data** - Coordinate conversion and mapping
- **Hierarchical data** - Tree and nested structure handling
- **Network data** - Node and edge relationship processing
- **Statistical data** - Distribution and correlation analysis

### Performance Considerations
- Lazy evaluation and streaming
- Incremental data processing
- Client-side vs server-side transformations
- Memory management for large datasets
- Parallel processing techniques

## API Reference

- Transform props function signature
- Available utility functions
- Data structure interfaces
- Error handling patterns

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*This documentation is under active development. Check back soon for updates!*