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refactor: move bundled skills tree to repo root skills/
- Relocate runtime/skills -> skills/; runtime_skills_root() prefers oclaw/skills with fallback to legacy runtime/skills for unmigrated trees. - session-bootstrap hook handler resolves repo root via PROJECT_ROOT. - Update architecture/migration docs and in-tree skill references. Co-authored-by: Cursor <cursoragent@cursor.com>
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skills/tushare-finance/reference/接口文档/Shibor报价数据.md
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skills/tushare-finance/reference/接口文档/Shibor报价数据.md
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# Shibor报价数据
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**文档ID**: 150
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**原始链接**: https://tushare.pro/document/2?doc_id=150
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---
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## Shibor报价数据
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接口：shibor_quote描述：Shibor报价数据限量：单次最大4000行数据，总量不限制，可通过设置开始和结束日期分段获取积分：用户积累120积分可以调取，具体请参阅积分获取办法
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输入参数
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<table>
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<thead>
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<tr>
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<th>名称</th>
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<th>类型</th>
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<th>必选</th>
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<th>描述</th>
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</tr>
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</thead>
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<tbody><tr>
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<td>date</td>
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<td>str</td>
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<td>N</td>
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<td>日期 (日期输入格式：YYYYMMDD，下同)</td>
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</tr>
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<tr>
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<td>start_date</td>
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<td>str</td>
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<td>N</td>
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<td>开始日期</td>
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</tr>
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<tr>
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<td>end_date</td>
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<td>str</td>
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<td>N</td>
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<td>结束日期</td>
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</tr>
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<tr>
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<td>bank</td>
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<td>str</td>
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<td>N</td>
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<td>银行名称 （中文名称，例如 农业银行）</td>
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</tr>
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</tbody></table>
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输出参数
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<table>
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<thead>
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<tr>
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<th>名称</th>
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<th>类型</th>
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<th>默认显示</th>
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<th>描述</th>
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</tr>
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</thead>
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<tbody><tr>
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<td>date</td>
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<td>str</td>
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<td>Y</td>
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<td>日期</td>
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</tr>
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<tr>
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<td>bank</td>
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<td>str</td>
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<td>Y</td>
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<td>报价银行</td>
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</tr>
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<tr>
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<td>on_b</td>
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<td>float</td>
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<td>Y</td>
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<td>隔夜_Bid</td>
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</tr>
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<tr>
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<td>on_a</td>
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<td>float</td>
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<td>Y</td>
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<td>隔夜_Ask</td>
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</tr>
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<tr>
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<td>1w_b</td>
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<td>float</td>
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<td>Y</td>
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<td>1周_Bid</td>
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</tr>
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<tr>
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<td>1w_a</td>
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<td>float</td>
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<td>Y</td>
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<td>1周_Ask</td>
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</tr>
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<tr>
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<td>2w_b</td>
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<td>float</td>
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<td>Y</td>
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<td>2周_Bid</td>
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</tr>
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<tr>
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<td>2w_a</td>
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<td>float</td>
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<td>Y</td>
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<td>2周_Ask</td>
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</tr>
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<tr>
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<td>1m_b</td>
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<td>float</td>
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<td>Y</td>
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<td>1月_Bid</td>
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</tr>
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<tr>
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<td>1m_a</td>
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<td>float</td>
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<td>Y</td>
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<td>1月_Ask</td>
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</tr>
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<tr>
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<td>3m_b</td>
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<td>float</td>
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<td>Y</td>
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<td>3月_Bid</td>
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</tr>
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<tr>
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<td>3m_a</td>
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<td>float</td>
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<td>Y</td>
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<td>3月_Ask</td>
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</tr>
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<tr>
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<td>6m_b</td>
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<td>float</td>
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<td>Y</td>
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<td>6月_Bid</td>
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</tr>
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<tr>
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<td>6m_a</td>
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<td>float</td>
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<td>Y</td>
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<td>6月_Ask</td>
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</tr>
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<tr>
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<td>9m_b</td>
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<td>float</td>
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<td>Y</td>
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<td>9月_Bid</td>
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</tr>
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<tr>
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<td>9m_a</td>
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<td>float</td>
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<td>Y</td>
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<td>9月_Ask</td>
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</tr>
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<tr>
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<td>1y_b</td>
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<td>float</td>
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<td>Y</td>
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<td>1年_Bid</td>
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</tr>
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<tr>
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<td>1y_a</td>
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<td>float</td>
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<td>Y</td>
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<td>1年_Ask</td>
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</tr>
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</tbody></table>
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接口调用
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```
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pro = ts.pro_api()
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df = pro.shibor_quote(start_date='20180101', end_date='20181101')
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```
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数据样例
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```
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date bank on_b on_a 1w_b 1w_a 2w_b 2w_a 1m_b 1m_a \
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0 20181101 民生银行 2.540 2.540 2.65 2.65 2.67 2.67 2.680 2.680
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1 20181101 国开行 2.570 2.570 2.71 2.71 2.75 2.75 2.690 2.690
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2 20181101 邮储银行 2.550 2.550 2.72 2.72 2.72 2.72 2.690 2.690
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3 20181101 广发银行 2.560 2.560 2.66 2.66 2.68 2.68 2.720 2.720
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4 20181101 华夏银行 2.550 2.550 2.72 2.72 2.73 2.73 2.690 2.690
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5 20181101 汇丰中国 2.550 2.550 2.65 2.65 2.68 2.68 2.690 2.690
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6 20181101 上海银行 2.560 2.560 2.70 2.70 2.73 2.73 2.690 2.690
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7 20181101 北京银行 2.570 2.570 2.67 2.67 2.65 2.65 2.600 2.600
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8 20181101 浦发银行 2.560 2.560 2.75 2.75 2.65 2.65 2.700 2.700
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9 20181101 兴业银行 2.530 2.530 2.65 2.65 2.60 2.60 2.500 2.500
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10 20181101 光大银行 2.540 2.540 2.65 2.65 2.70 2.70 2.720 2.720
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11 20181101 中信银行 2.550 2.550 2.65 2.65 2.70 2.70 2.700 2.700
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12 20181101 招商银行 2.540 2.540 2.67 2.67 2.65 2.65 2.700 2.700
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13 20181101 交通银行 2.540 2.540 2.68 2.68 2.72 2.72 2.690 2.690
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14 20181101 建设银行 2.530 2.530 2.67 2.67 2.68 2.68 2.720 2.720
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15 20181101 中国银行 2.540 2.540 2.65 2.65 2.66 2.66 2.680 2.680
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16 20181101 农业银行 2.550 2.550 2.70 2.70 2.75 2.75 2.760 2.760
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17 20181101 工商银行 2.500 2.500 2.68 2.68 2.70 2.70 2.720 2.720
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18 20181031 民生银行 2.310 2.310 2.72 2.72 2.73 2.73 2.730 2.730
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19 20181031 国开行 2.370 2.370 2.75 2.75 2.76 2.76 2.690 2.690
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20 20181031 邮储银行 2.350 2.350 2.73 2.73 2.72 2.72 2.670 2.670
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3m_b 3m_a 6m_b 6m_a 9m_b 9m_a 1y_b 1y_a
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0 2.960 2.960 3.290 3.290 3.510 3.510 3.550 3.550
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1 2.970 2.970 3.320 3.320 3.530 3.530 3.570 3.570
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2 2.960 2.960 3.300 3.300 3.500 3.500 3.550 3.550
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3 3.000 3.000 3.250 3.250 3.500 3.500 3.550 3.550
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4 2.970 2.970 3.300 3.300 3.510 3.510 3.550 3.550
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5 2.970 2.970 3.300 3.300 3.500 3.500 3.550 3.550
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6 2.960 2.960 3.300 3.300 3.510 3.510 3.550 3.550
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7 3.000 3.000 3.400 3.400 3.550 3.550 3.600 3.600
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8 2.960 2.960 3.300 3.300 3.500 3.500 3.550 3.550
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9 2.950 2.950 3.100 3.100 3.400 3.400 3.500 3.500
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10 3.000 3.000 3.300 3.300 3.500 3.500 3.550 3.550
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11 3.000 3.000 3.300 3.300 3.550 3.550 3.550 3.550
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12 3.100 3.100 3.300 3.300 3.550 3.550 3.550 3.550
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13 2.970 2.970 3.300 3.300 3.510 3.510 3.560 3.560
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14 3.000 3.000 3.260 3.260 3.500 3.500 3.550 3.550
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15 2.940 2.940 3.280 3.280 3.480 3.480 3.520 3.520
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16 3.000 3.000 3.300 3.300 3.500 3.500 3.550 3.550
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17 2.880 2.880 3.240 3.240 3.420 3.420 3.470 3.470
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18 2.970 2.970 3.300 3.300 3.500 3.500 3.550 3.550
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19 2.960 2.960 3.320 3.320 3.520 3.520 3.560 3.560
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20 2.960 2.960 3.300 3.300 3.500 3.500 3.550 3.550
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```
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