Spaces:
Sleeping
Sleeping
File size: 2,277 Bytes
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DATA PREPROCESSING REPORT
Generated: 2025-12-13 05:37:32
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INPUT FILES:
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β resourceoptimization23.csv β 30 districts loaded
β equipment_dataset.csv β 36 equipment types loaded
OUTPUT FILES:
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β districts_master.csv β 30 rows Γ 22 columns
β equipment_inventory.csv β 36 rows
COMPUTED FEATURES:
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β Latitude & Longitude (geographic coordinates)
β Infrastructure_Score (0-1 scale)
β Vulnerability_Index (0-1 scale)
β Historical_Risk_Score (0-1 scale)
β Population_Exposure_Index (0-1 scale)
β Is_Coastal (binary flag)
β SDRF_Utilization_Rate
DATA QUALITY:
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β Missing values: Handled
β Duplicates: Removed (0 found)
β Data types: Validated
β Coordinates: All 30 districts mapped
DISTRICT STATISTICS:
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β’ Coastal districts: 8
β’ Inland districts: 22
β’ High vulnerability districts: 1
β’ Low infrastructure districts: 22
TOP 5 MOST VULNERABLE DISTRICTS:
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District Vulnerability_Index Flood_Zone
Kendrapara 0.800 Flood Zone
Ganjam 0.638 Flood Zone
Balasore 0.625 Flood Zone
Puri 0.600 Flood Zone
Jagatsinghpur 0.587 Flood Zone
TOP 5 BEST INFRASTRUCTURE:
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District Infrastructure_Score Cyclone_Shelters
Cuttack 0.993 80
Ganjam 0.946 100
Puri 0.920 95
Khordha 0.898 75
Kendrapara 0.879 110
RESOURCE CONSTRAINTS (from equipment data):
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β’ Total shelters available: 814
β’ Total equipment items: 132682
β’ High priority equipment types: 19
NEXT STEPS:
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1. Use districts_master.csv in your API
2. Update ResourceOptimizer to load this file
3. Run optimization endpoint: POST /optimize/resources
4. Verify risk scores and allocations
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