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/KR_2023.csv
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data/real/KR_2023.csv
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,AAA,AA,A,BBB,BB,B,CCC,D
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AAA,0.985975,0.014025,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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AA,0.024314,0.929246,0.044250,0.001037,0.000576,0.000576,0.000000,0.000000
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A,0.000000,0.140393,0.803316,0.043990,0.002942,0.006418,0.000000,0.002942
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BBB,0.000000,0.000972,0.210919,0.684066,0.045845,0.034301,0.003000,0.020897
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BB,0.000000,0.000000,0.023439,0.179363,0.441274,0.137580,0.015287,0.203057
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B,0.000000,0.000000,0.000000,0.029265,0.014633,0.366781,0.064726,0.524595
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CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.011706,0.195401,0.786893
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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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