- Add generate_icicle_chart_indication() to pathway_analyzer.py
- Variant that uses indication_df instead of directory_df
- Groups by Trust → Search_Term → Drug → Pathway
- Accepts indication_df mapping UPID → Indication_Group
- Add process_indication_pathway_for_date_filter() to pathway_pipeline.py
- Processes indication-based pathway for a single date filter
- Uses generate_icicle_chart_indication() for hierarchy building
- Add extract_indication_fields() to pathway_pipeline.py
- Extracts trust_name, search_term, drug_sequence from ids column
- Similar to extract_denormalized_fields() but for indication charts
- Update convert_to_records() with chart_type parameter
- Includes chart_type column in output records
- Supports "directory" and "indication" values
- Add ChartType type alias (Literal["directory", "indication"])
- Update __all__ exports with new functions
Tested full refresh pipeline end-to-end with real Snowflake data:
- Fixed trust filter to read Name column from defaultTrusts.csv
- Fixed Decimal type handling in calculate_cost_per_patient_per_annum
- Fixed array handling in convert_to_records for average_administered
- Added required reference CSV files to data/ directory
- Configured Snowflake connection (account, warehouse, user)
Results:
- Snowflake fetch: 656,695 records in ~7s
- Transformations: 519,848 records after UPID/drug/directory
- Pathway nodes: 293 for all_6mo (8 trusts, 14 directories)
- Total processing time: ~6.2 minutes
Create data_processing/pathway_pipeline.py with:
- DateFilterConfig dataclass for date filter configuration
- DATE_FILTER_CONFIGS with 6 pre-defined combinations
- compute_date_ranges() for computing actual dates from config
- fetch_and_transform_data() for Snowflake fetch + transformations
- process_pathway_for_date_filter() using existing generate_icicle_chart()
- extract_denormalized_fields() to parse trust/directory/drugs from ids
- convert_to_records() for SQLite insertion
- process_all_date_filters() convenience function
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Andrew Charlwood