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_2023.csv
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data/real/AVG_2023.csv
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,AAA,AA,A,BBB,BB,B,CCC,D
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AAA,0.985058,0.014942,0.000000,0.000000,0.000000,0.000000,0.000000,0.000000
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AA,0.012441,0.967654,0.019175,0.000346,0.000192,0.000192,0.000000,0.000000
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A,0.000000,0.046798,0.925196,0.017851,0.000981,0.008194,0.000000,0.000981
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BBB,0.000000,0.000324,0.122103,0.840895,0.015282,0.011434,0.002997,0.006966
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BB,0.000000,0.000000,0.007813,0.059788,0.747704,0.087134,0.009682,0.087879
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B,0.000000,0.000000,0.000000,0.009755,0.004878,0.688927,0.121575,0.174865
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CCC,0.000000,0.000000,0.001000,0.002000,0.003000,0.017235,0.714467,0.262298
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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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