reinitialize tutorials for documentation as old tutorials died with U…

[jhnwu3]

This pull request adds a comprehensive, example-driven tutorial notebook for the pyhealth.data API. The notebook introduces users to the foundational classes (Event and Patient), demonstrates how to construct and query longitudinal patient records, and provides realistic usage examples with both synthetic and real-world datasets. The tutorial is structured to guide users through creating events, building patient records, querying events with various filters, and understanding integration with datasets like MIMIC-III.

Key additions and improvements:

PyHealth Data API Documentation and Examples:

• Introduces and explains the core concepts of Event and Patient classes, including their design, usage, and attribute access patterns.
• Provides step-by-step, runnable code examples for creating events, constructing patient records from polars DataFrames, and querying events using the get_events() method with time, type, and attribute filters.

Realistic and Advanced Usage Scenarios:

• Demonstrates building complex, longitudinal patient records with multiple event types and admissions, and shows advanced querying (e.g., tracking lab trends, filtering by diagnosis and lab values).
• Details the column naming conventions and efficient data storage strategies for heterogeneous clinical events.

Integration with Real Datasets:

• Shows how to load and explore real patient data using the MIMIC3Dataset, including how table…IUC purge