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_2009.csv
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data/real/AVG_2009.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,0.009656,0.990344,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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A,0.000000,0.104447,0.876365,0.019188,0.000000,0.000000,0.000000,0.000000
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BBB,0.000000,0.000000,0.068251,0.856864,0.000000,0.071886,0.003000,0.000000
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BB,0.000000,0.000000,0.000000,0.000000,0.672167,0.165050,0.018339,0.144445
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B,0.000000,0.000000,0.000000,0.000000,0.000000,0.738601,0.130341,0.131057
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CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.020000,0.646357,0.327643
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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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