feat(data): parse 3-agency PDF transition matrices to CSV #task-290
- New: data/parse_pdf_matrices.py (KR/NICE/SCI PDF parser) - KR: text-based parser (space-separated numbers + dashes) - NICE: text-based parser (clean numeric format) - SCI: pdfplumber table extraction (column-position-aware) - WR redistribution, B이하→B mapping, CCC extrapolation from PD patterns - Modified: data/transition_matrices.py (added source='real' loader) - Modified: config.yaml (data.transition_source: 'real') - Modified: main.py (reads transition source from config) - Output: 112 CSV files (KR/NICE/SCI/AVG × 28 years)
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data/real/AVG_1998.csv
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data/real/AVG_1998.csv
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,AAA,AA,A,BBB,BB,B,CCC,D
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AAA,1.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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AA,0.000000,0.576715,0.338615,0.084670,0.000000,0.000000,0.000000,0.000000
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A,0.000000,0.000000,0.559352,0.440648,0.000000,0.000000,0.000000,0.000000
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BBB,0.000000,0.000000,0.017544,0.699909,0.207912,0.071635,0.003000,0.000000
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BB,0.000000,0.000000,0.000000,0.068283,0.515874,0.244982,0.027220,0.143640
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B,0.000000,0.000000,0.000000,0.000000,0.044442,0.476959,0.084169,0.394430
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CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.048887,0.353468,0.591645
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D,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000,1.000000
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